Please help us test our new pre-print finding feature by giving the pre-print link a rating. A 5 star rating indicates the linked pre-print has the exact same content as the published article.
Please help us test our new pre-print finding feature by giving the pre-print link a rating. A 5 star rating indicates the linked pre-print has the exact same content as the published article.
Authors:
Haolan Chen;Peng Wang;Guojian Tang;
Pages: 3521 - 3530 Abstract: This work focuses on the attitude control problem for hypersonic morphing vehicles (HMVs) with uncertainties. A span-morphing HMV model is first established with lumped disturbances. Based on fixed-time technique, a disturbance observer with fuzzy logic system (FLS) is proposed to enhance the robustness by estimating the unmodeled dynamics and external disturbances in fixed settling time. The multivariable fixed-time sliding mode manifold is applied to the transformed control system, which guarantees a direct control input design from attitude command and decent tracking performance. Then, the control system degenerates into an autonomous system, and the closed-loop fixed-time stability is ensured via Lyapunov synthesis and homogeneity theory. Finally, simulation results are presented to demonstrate the effectiveness of the proposed control scheme. PubDate:
TUE, 14 FEB 2023 10:02:37 -04 Issue No:Vol. 59, No. 4 (2023)
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Authors:
Tianqu Liu;Jinping Sun;Guohua Wang;Xiaoyong Du;Weidong Hu;
Pages: 3797 - 3810 Abstract: The detection performances of MIMO radar can be improved by waveform diversity technology. The waveform diversity gain depends on the correlation side-lobe level of the orthogonal waveform set. Generally, peak side-lobe level (PSL) and integrated side-lobe level (ISL) are two most important performance metrics of the correlation side-lobe level. Few existing orthogonal waveform set design algorithms can minimize PSL and ISL simultaneously. To tackle this problem, this article first proposes a correlation side-lobe performance metric in the form of p-norm, denoted by p-ISL. Then, in order to minimize the p-ISL, this article develops a p-MM algorithm based on majorization–minimization (MM) framework, which transforms the complex p-order polynomial minimization problem into a series of low-order simple optimization problems. Numerical results show that the p-MM algorithm can effectively suppress the correlation side-lobe level and strike a good balance between the PSL and ISL metrics. Compared with the best PSL optimization algorithm based on primal dual method, the p-MM obtains about the same PSL and lower ISL values. Compared with multi-CAN, MM-Corr, ISL-New,and the other state-of-the-art ISL minimization algorithms, the p-MM obtains slightly higher ISL and much lower PSL. Briefly, the p-MM is able to obtain almost the best PSL and relatively low ISL values. PubDate:
THU, 30 MAR 2023 10:01:47 -04 Issue No:Vol. 59, No. 4 (2023)
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Authors:
Yueyang Liu;Qinglei Hu;Gang Feng;
Pages: 3835 - 3847 Abstract: This article investigates the reduced attitude control problem of a rigid spacecraft subject to elliptical pointing constraints and parameter uncertainties. Specifically, a diffeomorphic projection is proposed to map the constraints from 2-sphere to elliptical 2-sphere while with the pointing direction preserved. Then, the constrained reduced attitude control problem is transformed into a conventional obstacle avoidance problem on the 2-dimensional (2-D) Euclidean space via the elliptical stereographic projection. Benefiting from properties of the diffeomorphism and Kodischek–Rimon navigation functions, a sufficient condition to exclude local minima is obtained. A constrained adaptive reduced attitude controller is further developed and it is shown that almost asymptotical stability of the resulting closed-loop system can be ensured in the sense of a measure zero set. Finally, numerical examples are furnished to illustrate the effectiveness of the proposed controller. PubDate:
MON, 02 JAN 2023 10:03:36 -04 Issue No:Vol. 59, No. 4 (2023)
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Authors:
Javier Trujillo Rodriguez;Fabiola Colone;Pierfrancesco Lombardo;
Pages: 3871 - 3889 Abstract: In this article, we address the problem of the range-Doppler map evaluation in continuous wave radar exploiting orthogonal frequency division multiplexing (OFDM) signals. This stage is usually implemented by resorting to a suboptimal batches algorithm and a typical choice is to fragment the signal in batches with length equal to the OFDM symbol length and to apply at each batch an appropriate range compression strategy: typically, either matched filter (MF) or reciprocal filter (RF). The former provides the best performance against noise-limited scenarios, whereas the latter against clutter-limited scenarios, thanks to its high peak sidelobe level. Using “OFDM fragmentation” requires symbol synchronization and sets constraints on the coherent processing chain; moreover, we show that it provides a signal-to-noise ratio (SNR) loss both when using MF and RF. Therefore, we investigate the case of “non-OFDM fragmentation,” which does not require synchronization and avoids setting constraints on the processing chain. Specifically, we address the case of batch lengths longer than a single OFDM symbol that can potentially reduce the SNR loss at long ranges. We find that this is effective for the MF, but causes an even higher SNR loss for the direct application of the RF filter, which still provides a low level of sidelobes. Aiming at preserving the potential benefits of the RF over the MF against the clutter-limited scenarios, we propose some modified versions of the RF for the non-OFDM fragmentation case, which are shown to offer a tradeoff between SNR losses and sidelobes level control. The effectiveness of the proposed approaches is demonstrated both by providing theoretical performance prediction expressions and by using simulated analyses. To this purpose, a case study is considered for a passive radar exploiting digital video broadcasting – terrestrial transmissions. PubDate:
THU, 19 JAN 2023 10:01:49 -04 Issue No:Vol. 59, No. 4 (2023)
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Authors:
Hailong Kang;Jun Li;Qinghua Guo;Marco Martorella;Elisa Giusti;Jinjian Cai;
Pages: 3890 - 3906 Abstract: Sparse Bayesian learning (SBL) has found successful applications in interferometric inverse synthetic aperture radar (InISAR) imaging, especially in the presence of limited number of pulses or when using sparse apertures. SBL-based InISAR algorithms have been proven to be significantly superior to Fourier transform-based ones. However, the existing SBL-based algorithms are slow due to their high computational complexity. Moreover, there is also much room to improve in terms of imaging performance. In this article, leveraging the approximate message passing with unitary transformation (UAMP), we propose an InISAR imaging algorithm named UAMP joint sparse recovery (JSR), which is much faster and delivers notably higher imaging accuracy than the existing SBL-based algorithms. Specifically, we develop a type-2 joint sparse model for InISAR imaging and formulate it as a two-layer multiple measurement vectors joint sparse problem. Based on a factor graph representation, the message passing techniques are used to efficiently solve this problem, which leads to the UAMP-JSR algorithm. Results based on extensive simulations and experiments based on the real data collected by the Pisa Radar demonstrate the effectiveness and superiority of the proposed algorithm compared to existing algorithms. PubDate:
FRI, 06 JAN 2023 10:02:32 -04 Issue No:Vol. 59, No. 4 (2023)
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Authors:
Yu Wu;Tianjiao Liang;Jinzhan Gou;Chenggang Tao;Haifeng Wang;
Pages: 3924 - 3940 Abstract: Unmanned aerial vehicle (UAV) formation has been widely applied in various aspects, both for military and civil purposes. In this article, multiple UAV formations are deployed to perform different types of tasks, and the heterogeneous mission planning problem is studied. The problem is divided into two subproblems, i.e., task assignment and path planning. First, the task assignment is formulated into a combinatorial optimization problem. Different from the existing articles, appropriate UAVs need to be selected to build the formation and perform specific types of tasks. To obtain the task assignment scheme, a hybrid genetic and simulated annealing (HGSA) algorithm is proposed. In this algorithm, a feasible solution is guaranteed by the designed task-based strategy, and the diversity of solutions is ensured by the group-based solution remaining approach. In the path planning problem, an obstacle avoidance-enabled consensus (OAEC) algorithm is developed to form the UAV formation, which extends the application of the standard consensus algorithm. A multistep particle swarm optimization (MPSO) algorithm is combined with the consensus algorithm to generate a path for the UAV formation to reach each task point. The conflict among multiple UAV formations is resolved by adjusting their departure time. Furthermore, the task assignment scheme is modified by utilizing real path information on the flying distance between the UAVs and the task points. The simulation results demonstrate that the HGSA algorithm can build the UAV formations and assign the tasks to them while satisfying all the complicated constraints. The advantages of the OAEC algorithm and the MPSO algorithm in path planning are verified by comparison with relevant algorithms. PubDate:
THU, 05 JAN 2023 10:02:33 -04 Issue No:Vol. 59, No. 4 (2023)
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Authors:
Shrivathsan Narayanan;Okuary Osechas;
Pages: 3941 - 3952 Abstract: This article proposes a real-time capable tropospheric delay model for terrestrial radio navigation systems used for aviation. Its functional scope ranges from elevation angles below the local horizon to zenith. Flight experiments were carried out to quantify the improvement in service coverage achieved for measurements close to and below the local horizon, with aircraft distances in the order of 250 km. Mismodeling tropospheric delays at these elevation angles and aircraft distances can result in slant-range error several order of magnitude greater than the accuracy of terrestrial nav-aids, and adequately accounting them translates into improved accuracy and tighter integrity bounds. The proposed method uses a polynomial representation of the atmospheric refractivity instead of the traditional exponential distribution used in GNSS. The resulting method provides tropospheric corrections accurate to $\pm$ 0.5 cm for elevation angles above 5$^\circ$, and $\pm$ 15 cm at an elevation of 0.2$^{\circ }$. In addition, the proposed model offers a reduction in the horizontal position error in terms of an order of magnitude from 14 m (for uncompensated tropospheric delay) to below 1.6 cm for all flight segments, that will enable terrestrial systems to support increasingly demanding performance based navigation systems. PubDate:
WED, 11 JAN 2023 10:03:01 -04 Issue No:Vol. 59, No. 4 (2023)
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Authors:
Danyan Lin;Gang Wang;K. C. Ho;
Pages: 3953 - 3970 Abstract: Signal propagation speed may not be available in practical localization scenarios. This article addresses both the moving and stationary source localization problems by using frequency measurements when the signal propagation speed is unavailable. The task is fulfilled by exploiting the Doppler frequency shift coming from the relative motion between the source and a network of mobile sensors. Owing to the complicated nonlinear measurement model and the absence of the knowledge about signal propagation speed, it is difficult to conduct localization. To address this problem, we first transform the measurement model to a tractable form, from which to formulate a constrained weighted least squares (CWLS) problem. Afterwards, we propose two methods to solve the nonconvex CWLS problem. The first method relaxes the CWLS problem into a semidefinite programming problem by applying semidefinite relaxation (SDR). The second method adopts the alternating estimation procedure by utilizing the prior information about the nominal value of the signal propagation speed. Two subproblems are formulated and solved in an alternate manner, one in estimating the source position and velocity by applying SDR and the other the signal propagation speed by an explicit expression. Furthermore, we conduct the mean square error analysis to show that the CWLS solution is able to reach the Cramér–Rao lower bound performance. Simulation results validate the expected performance of the proposed methods. PubDate:
THU, 12 JAN 2023 10:02:03 -04 Issue No:Vol. 59, No. 4 (2023)
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Authors:
Zixuan Zheng;Peng Zhang;Jianping Yuan;
Pages: 3971 - 3981 Abstract: In this article, the nonzero-sum pursuit-evasion (PE) game control problem is studied for a class of linear spacecraft control systems subject to the complete information case and incomplete information case. The incomplete information includes the cost functions and the control inputs. In practical confrontation situations, due to the incomplete information constraints, it is impossible for the pursuer and the evader to build up the exact opposite cost function. Hence, a nonzero-sum game framework is utilized to describe the PE game problem of the double-spacecraft system. First of all, under the complete information case, the nonzero-sum PE game control strategy is designed by solving the coupled Riccati recursions. Then, aiming at the incomplete information case, a control gain estimator is established, which lays the foundation for the control strategy design of the pursuit spacecraft. On the basis of the estimated control gain, the pursuit control strategy is solved by using the standard discrete-time Riccati recursion. In order to further get rid of the system information, a Q-learning-based control gain is designed for the pursuit spacecraft. Finally, a numerical example on the PE spacecraft system is provided to verify the effectiveness of the proposed PE game control strategies. PubDate:
TUE, 10 JAN 2023 10:02:37 -04 Issue No:Vol. 59, No. 4 (2023)
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Authors:
Prayag Sharma;Prem Kumar;Radhakant Padhi;
Pages: 3982 - 3994 Abstract: A unified optimal guidance scheme is presented in this article for both midcourse and terminal phases combined. It minimizes the total deceleration resulting in enhanced range and/or higher impact velocity, while satisfying the terminal constraints on impact angle and miss distance. State-dependent terms are included in the cost function of the recently proposed generalized quasi-spectral-model predictive static programming (MPSP) and, because of its similarity with the pseudo-spectral philosophy, it is renamed as “pseudo-spectral MPSP.” Extensive simulation studies with different engagement scenarios illustrate the effectiveness of the proposed guidance to engage with incoming high-speed ballistic targets. PubDate:
WED, 18 JAN 2023 10:57:51 -04 Issue No:Vol. 59, No. 4 (2023)
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Authors:
Xing Fang;Jingjing Jiang;Wen-Hua Chen;
Pages: 3995 - 4004 Abstract: Autonomous emergency landing capability of fixed-wing aircraft is essential for opening airspace for civil unmanned aviation. This article proposes a goal-oriented control scheme to exploit wind information for the benefit of forced landing. Different from general disturbances in a classic control system, a favorable wind would help aircraft to glide to a selected landing site more easily so increase the level of safety while an adverse wind may render a selected landing site infeasible. We formulate the forced landing problem with wind preview information in the framework of economic model predictive control (EMPC), which aims to maximize the aircraft's final altitude when reaching a target region. A double-layer model predictive control (MPC) scheme is adopted to lessen the computational burden and to increase the prediction time window for practical implementation, where a piecewise-constant disturbance-preview-based EMPC maximizes the altitude at the upper level, and a linear MPC is employed at the lower level to track the reference signal optimized by the upper-level planner. Moreover, the effectiveness of the goal-oriented optimal control scheme is illustrated by several case studies, where an unmanned aircraft is gliding toward potential landing sites under various conditions. PubDate:
MON, 09 JAN 2023 10:04:05 -04 Issue No:Vol. 59, No. 4 (2023)
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Authors:
Wenjun Wu;Bo Tang;Xuyang Wang;
Pages: 4005 - 4017 Abstract: We investigate the constant-modulus (CM) waveform design for dual-function radar communication systems in the presence of clutter. To minimize the interference power and enhance the target acquisition performance, we use the signal-to-interference-plus-noise-ratio as the design metric. In addition, to ensure the quality of the service for each communication user, we enforce a constraint on the synthesis error of every communication signals. An iterative algorithm, which is based on cyclic optimization, Dinkinbach's transform, and alternating direction of method of multipliers, is proposed to tackle the encountered nonconvex optimization problem. Simulations illustrate that the CM waveforms synthesized by the proposed algorithm allow to suppress the clutter efficiently and control the synthesis error of communication signals to a low level. PubDate:
FRI, 06 JAN 2023 10:02:32 -04 Issue No:Vol. 59, No. 4 (2023)
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Authors:
Weinan Wu;Jie Xu;Yiming Sun;
Pages: 4018 - 4032 Abstract: The actual performance of a task-assignment method of unmanned aerial vehicles (UAVs) shows a considerable dependence on the path planning process coupled with it; however, this topic has been rarely studied in the existing literature. This article considers the problem of maximizing the task-assignment reward of a fleet of heterogeneous UAVs for a dynamic reconnaissance and confirmation task under constraints of critical time and multi-UAV tasks where the coupled path optimization objectives also need to be considered. The existing consensus-based bundle algorithm is extended with an effective method for managing the multitask and multiagent constraints. The proposed method can optimize the inherent coupling path using the Dubins path to reduce the differences between the estimated path and the actual path, shortening the operation time by adopting the distributed genetic algorithm. The proposed method is verified by the sample run tests of a disaster area reconnaissance and confirmation task and Monte Carlo comparison simulations with the two existing algorithms. The results verify both the practicality and advantages of the proposed method. PubDate:
TUE, 10 JAN 2023 10:02:37 -04 Issue No:Vol. 59, No. 4 (2023)
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Authors:
Qi Yu;Wanchun Chen;Wenbin Yu;
Pages: 4033 - 4048 Abstract: Approximate analytical solutions for the ascent trajectory of a solid-fuel launch vehicle are derived. To the best of the authors’ knowledge, the solutions are the ones achieving the highest accuracy in ascent-trajectory prediction under the condition of high angle-of-attack (AOA) maneuvers, where the magnitude of AOA can even be greater than 60° at high altitudes. As the first step of deriving the solutions, a reduced-order dynamics model with a normalized mass as the independent variable is put forward for longitudinal-plane flight. To further simplify the model, the sine of AOA is chosen as the key parameter for trajectory control and designed as a polynomial of the normalized mass. Meanwhile, an improved aerodynamic model with the sine of AOA as the independent variable is developed. Due to high AOA, the simplified dynamics model is still highly nonlinear and difficult to solve. To overcome this difficulty, by performing force analysis, several approximate polynomials and first-order Taylor series expansions are created to replace some highly nonlinear but relatively small terms in the dynamical equations, while the errors of the approximate formulae relative to the original nonlinear terms are retained and treated as minor perturbations. The benefit is that the modified dynamics model can be divided into two analytically solvable subsystems using a perturbation method. By solving the subsystems, the approximate analytical solutions for downrange, altitude, velocity, and flight-path angle (FPA) of the vehicle are obtained successfully. Simulation results verify that the proposed solutions are much more accurate than the existing solutions in the scenario of high AOA flight. PubDate:
TUE, 10 JAN 2023 10:02:37 -04 Issue No:Vol. 59, No. 4 (2023)
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Authors:
Xiaolong Su;Zhen Liu;Junpeng Shi;Panhe Hu;Tianpeng Liu;Xiang Li;
Pages: 4049 - 4062 Abstract: Recently, deep unfolded networks have been widely utilized in direction of arrival (DOA) estimation due to the reduced computational complexity and improved estimation accuracy. However, few consider the nested array for off-grid DOA estimation, where the estimated DOAs are not on the prespecified grids. In this article, we propose a deep unfolded FOCal underdetermined system solver network and a deep unfolded alternating direction method of multiplies to address the problem, which respectively aim to improve estimation accuracy and further reduce computational complexity. We first apply first-order Taylor expansion and vectorize the covariance matrix into a real-valued single snapshot for network input. We then train the proposed networks to obtain on-grid DOA spatial spectrum and off-grid values, where the off-grid DOA estimation is calculated by the peaks of off-grid DOA spatial spectrum and corresponding off-grid values. We demonstrate that the proposed networks with interpretable parameters can accelerate the convergence rate and achieve better generalization. Simulations verify the performance of proposed networks in comparison with the existing methods. PubDate:
TUE, 10 JAN 2023 10:02:37 -04 Issue No:Vol. 59, No. 4 (2023)
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Authors:
Pengfei Zhang;Yiqun Zhang;
Pages: 4063 - 4075 Abstract: Defensive formation of the pursuers is critical to the result of the two pursuers and one evader differential games. This article focuses on the horizontal defensive formation as well as the orthogonal defensive formation for the end game of homing missile interception, in which the payoff function is the minimal terminal miss of the pursuers. In particular, in the horizontal formation, it is proved that there exists an optimal initial distance between the two pursuers with a heuristic approach; in the orthogonal formation, it is deduced that the evader's optimal strategy depends on the maximum acceleration ratio of the evader and the pursuer. In addition, the two defensive formations are compared, implying that the horizontal formation gives a lesser miss than the orthogonal formation. Simulation results agree with the theoretical analysis. PubDate:
TUE, 10 JAN 2023 10:02:37 -04 Issue No:Vol. 59, No. 4 (2023)
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Authors:
Hoang D. Le;Hung D. Nguyen;Chuyen T. Nguyen;Anh T. Pham;
Pages: 4076 - 4091 Abstract: Space-air-ground integrated vehicular networks (SAGIVN) have been widely envisioned as a promising network architecture for sixth-generation to support the Internet of Vehicles (IoV). In SAGIVN, free-space optics (FSO)-based, high altitude platform relay-assisted low Earth orbit (LEO) satellite systems have recently attracted research efforts worldwide. Critical challenges in designing and implementing FSO-based SAGIVN include atmospheric turbulence, weather conditions, and pointing misalignment. This article offers a comprehensive cross-layer design framework of error-control protocols with rate adaptation for FSO burst transmissions in HAP-aided SAGIVN. Remarkably, we propose a design of link-layer cooperative incremental redundancy (IR) hybrid automatic repeat request (HARQ)-based sliding window mechanism. An analytical channel model for HAP-aided LEO satellite to emerging unmanned aerial vehicles FSO links is provided. At the same time, the analysis can also be applied to other kinds of vehicles. The queuing behavior induced by both the cooperative IR-HARQ protocol and the rate adaptation scheme is analyzed with a Markov model. Several performance metrics are analytically obtained, including the average round-trip frame delay, throughput, and energy efficiency. The results quantitatively demonstrate the impact of atmospheric turbulence and weather conditions on the system performance and support the optimal selection of system parameters. Additionally, the effectiveness of the proposed system is numerically confirmed. Monte Carlo simulations are also performed to validate the accuracy of theoretical derivations. PubDate:
FRI, 13 JAN 2023 10:02:43 -04 Issue No:Vol. 59, No. 4 (2023)
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Authors:
Jaehyun Park;Ismail Guvenc;
Pages: 4092 - 4104 Abstract: Due to the increasing number of aerial radars and joint communication/sensing technologies, interference from uncoordinated radars will limit the target detection and ranging performance in the future. In this article, we investigate the interference behavior in an aerial radar network for sensing ground targets. We consider that the radars mounted on unmanned aerial vehicles (UAVs) that fly at a certain altitude are randomly distributed according to a two-dimensional homogeneous Poisson point process (HPPP), and that the propagation is modeled using a probabilistic line-of-sight channel model. For such a sensing network, we derive the distribution of the radar interference using a stochastic geometry based analysis. In particular, when Swerling I model is considered for radar cross-section area for the target, we derive the Laplace transform of the radar interference. To avoid a strong interference between neighboring radars, a guard zone is introduced within which the UAV radar transmission around the permitted active radar is inhibited. As the radar performance metric, we derive the successful ranging probability (SRP) of a given radar by exploiting the Laplace transform of radar interference. Using the analytic SRP, we show that we can optimize the radar network parameters such as the radius of the guard zone and the density of the active radars. In addition, we also discuss how the analytic SRP gives an insight into the spectrum utilization strategy for the UAV radar networks with the guard zones. PubDate:
WED, 11 JAN 2023 10:03:01 -04 Issue No:Vol. 59, No. 4 (2023)
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Authors:
Zhetao Zhang;Haijun Yuan;Xiufeng He;Bofeng Li;Jianghui Geng;
Pages: 4105 - 4117 Abstract: Global navigation satellite system has been widely used for navigation and positioning in many areas, from professional applications to the mass market. However, in the real-time kinematic positioning, the ambiguities usually cannot be fixed in natural and urban canyon environments due to the high occlusion, strong reflection, and frequent maneuvering. In this article, the best integer equivariant (BIE) estimation with quality control (QC) is proposed. Specifically, the QC issues based on the observation and state domains are added to the BIE estimator. First, an improved multipath processing approach is used to mitigate the effects of multipath and diffraction, and a modified detection, identification, and adaptation procedure is adopted for processing the outliers and non-line-of-sight reception. For state-domain QC, a two-step selection and segment estimation are used to refine the ambiguity candidates. Finally, the BIE estimator is obtained. To validate the effectiveness of the proposed method, two experiments, including natural and urban canyon environments, are conducted. Compared with the float, fixed, and traditional BIE solutions, the BIE solution with QC has the best positioning performance, including precision and reliability. Moreover, the problem of ambiguity resolution is also alleviated to a great extent. Specifically, in real-time monitoring, the real-time single-epoch positioning accuracy in east, north, and up directions are approximately 0.023, 0.014, and 0.044 m, respectively. For the low-cost urban vehicle data, the proposed method performs best regarding availability, precision, and reliability. PubDate:
MON, 16 JAN 2023 10:05:07 -04 Issue No:Vol. 59, No. 4 (2023)
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Authors:
Batu K. Chalise;Daniel M. Wong;Kevin T. Wagner;Moeness G. Amin;
Pages: 4118 - 4133 Abstract: Despite their potential to significantly enhance target detection capability, distributed radar networks, with or without a central coordinator, have not been sufficiently examined. In this article, we propose a generalized likelihood ratio test (GLRT)-based constant false alarm rate (CFAR) detector for distributed detection in a radar network, wherein only neighboring nodes require sharing their GLRT values. We obtain the analytical expression for the local GLRT and employ distributed average consensus-based estimation to reach the global metric in the case of noise-free communications links. The exact analytical expressions for the local probability of false alarm (PFA) and probability of detection (PD) are derived and used to obtain the exact analytical expression for the global PFA as well as an approximate expression for the global PD. In the case of noisy communications links, we demonstrate the effects of quantization and different modulation techniques, such as chirp and phase shift keying, on the global detection probability. Our results show that the proposed detector performs significantly better than the non-CFAR energy detector and provides performance comparable to that of the non-CFAR matched filter detector. It is shown that the performance of the chirp and binary phase shift keying modulations is similar but better than that of quadrature phase shift keying. Our results also show that the uniform quantization of GLRT values with only 4 bits is sufficient to enable each node to achieve performance similar to the global performance achieved in the case of error-free communications links. PubDate:
TUE, 31 JAN 2023 10:06:33 -04 Issue No:Vol. 59, No. 4 (2023)
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Authors:
Siyuan Li;Dong Ye;Zhaowei Sun;Jianqiao Zhang;Weichao Zhong;
Pages: 4134 - 4146 Abstract: In this article, a flocking control strategy combining with artificial potential field is developed for collision-free trajectory tracking of satellite cluster with multiple disturbances and communication delay. Considering the link constraints of each satellite, a degree-constrained spanning tree is adopted as the communication topology. Furthermore, a topology optimization method based on the Prim and greedy algorithms is investigated to compute the degree radius constrained minimum spanning tree. By using the optimized communication topology, the satellites in cluster can reduce the communication delay and converge to the desired distances more quickly. Finally, the effectiveness and advantages of the proposed method are verified by numerical simulations. PubDate:
TUE, 17 JAN 2023 10:02:06 -04 Issue No:Vol. 59, No. 4 (2023)
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Authors:
Isaac E. Weintraub;Alexander Von Moll;Eloy Garcia;David W. Casbeer;Meir Pachter;
Pages: 4147 - 4158 Abstract: The maximum surveillance of a target which is holding course is considered, wherein an observer vehicle aims to maximize the time that a faster target remains within a fixed-range of the observer. This entails two coupled phases: 1) approach phase and 2) observation phase. In the approach phase, the observer strives to make contact with the faster target, such that in the observation phase, the observer is able to maximize the time where the target remains within range. Using Pontryagin's Minimum Principle, the optimal control laws for the observer are found in closed-form. Example scenarios highlight various aspects of the engagement. PubDate:
MON, 16 JAN 2023 10:05:07 -04 Issue No:Vol. 59, No. 4 (2023)
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Authors:
Zhaocheng Wang;Ruonan Wang;Jiaqiu Ai;Huanxin Zou;Jun Li;
Pages: 4159 - 4167 Abstract: Due to the large sizes of synthetic aperture radar (SAR) images, traditional deep learning-based ship detection methods usually utilize the sliding window preprocessing strategy to obtain the small-sized subimages. However, there are amounts of background clutter areas without ships in SAR images. Thus, traditional sliding window-based methods may generate numerous subimages without ships, which can bring high computation redundancy and numerous false alarms. To deal with the above problems, in this article, a novel detection method called global and local context-aware ship detector for high-resolution SAR images is proposed. The proposed method mainly contains three parts: the global context-aware-based subimages selection (GCSS) module, the deep learning module, and the local context-aware-based false alarms suppression (LCFS) module. The GCSS module employs the global context information to eliminate the subimages without ships, which can enhance detection efficiency and avoid generating numerous false alarms. The deep learning module is used to further obtain the preliminary detection boxes. The LCFS module is a postprocessing step, which employs the local context information around the detection boxes to further eliminate the false alarms. The experimental results on the measured data of AIR-SARShip-1.0 and 2.0 high-resolution SAR images demonstrate that the proposed method has higher precision and efficiency than the original deep learning methods. PubDate:
MON, 16 JAN 2023 10:05:07 -04 Issue No:Vol. 59, No. 4 (2023)
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Authors:
Kai Ning;Baolin Wu;Danwei Wang;
Pages: 4168 - 4179 Abstract: In this article, the spacecraft attitude takeover control (ATC) problem with limited communication and the unavailable angular velocity using cellular satellites is addressed. First, a dynamic uniform quantizer (DUQ) is proposed to quantize unit quaternion between sensor cellular satellites and controller cellular satellite. Second, an adaptive fuzzy observer is proposed to estimate the unavailable angular velocity. Further, between controller cellular satellite and actuator cellular satellites, an event-triggered mechanism (ETM) is provided to lighten the communication burden. By combing DUQ, adaptive fuzzy observer, the adaptive fuzzy control law and the ETM is established. The stability of the ATC systems with the proposed control method is ensured. Finally, the simulation results illustrate the effectiveness of the developed control laws. PubDate:
MON, 16 JAN 2023 10:05:07 -04 Issue No:Vol. 59, No. 4 (2023)
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Authors:
William Dale Blair;Yaakov Bar-Shalom;
Pages: 4180 - 4191 Abstract: When tracking maneuvering targets with a nearly constant velocity (NCV) Kalman filter with white noise acceleration, the selection of the process noise variance is complicated by the fact that the process noise errors are modeled as white Gaussian in the Kalman filter, while target maneuvers are deterministic or highly correlated in time. In recent years, the deterministic maneuver index was introduced for NCV Kalman filters and used to develop a relationship between the anticipated maximum acceleration of the target and the process noise variance that minimizes the maximum mean squared error (MSE) in position. Lower bounds on the process noise variance that prevent the position MSE from exceeding the measurement noise variance were also expressed in terms of the maximum acceleration and deterministic maneuver index. In this article, those results are summarized and codified for practical application by the target tracking community. The design methods for NCV Kalman filters with discrete white noise acceleration and continuous white noise acceleration are presented for sustained and brief maneuvers. The application of the design methods to radar tracking of maneuvering targets is also addressed. The effectiveness of the design methods is illustrated via Monte Carlo simulations. PubDate:
TUE, 31 JAN 2023 10:06:33 -04 Issue No:Vol. 59, No. 4 (2023)
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Authors:
Guozeng Cui;Hui Xu;Xinkai Chen;Jinpeng Yu;
Pages: 4192 - 4206 Abstract: This article devises a fixed-time distributed adaptive formation control algorithm under the event-triggered framework to guarantee the expected formation pattern for multiple quadrotor unmanned aerial vehicles (QUAVs) with full-state constraints. The multiple QUAVs subject to full-state constraints are transformed into the ones that are free from any constraints via a time-varying nonlinear transformation function, which is effective to handle the case regardless of whether there exist state constraints. The issue of “explosion of complexity” as well as the singularity problem is fully coped via the fixed-time command filter and the smooth switch function, respectively. To further improve the control performance of multiple QUAVs, the nonsmooth error compensation mechanism is constructed to compensate the filtered error resulting from a command filter. The rigorous stability analysis of the developed event-trigger-based distributed formation control scheme proves that all signals of the closed-loop system are fixed-time bounded, and the states of multiple QUAVs will not violate the prescribed constraints and the formation tracking errors converge to a small region around the origin in a fixed time. Finally, simulation examples are performed to delineate the validity of the proposed distributed formation control algorithm. PubDate:
WED, 18 JAN 2023 10:57:51 -04 Issue No:Vol. 59, No. 4 (2023)
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Authors:
Biao Yang;Shengqi Zhu;Xiongpeng He;Lan Lan;Ximin Li;
Pages: 4207 - 4222 Abstract: This article proposes a cognitive frequency diversity array (FDA) multiple-input multiple-output (MIMO) (FDA-MIMO) radar network (CFDA-MIMON) target discrimination and tracking algorithm under main-lobe deceptive trajectory interference. This algorithm can be divided into two stages: search-discrimination-initialization and cognitive target tracking. The first stage mainly uses the distribution characteristics of target and main-lobe deceptive trajectory interference on different radars to discriminate the target and interference in the radar network. A target state initialization strategy driven by G-pair measurements with large time interval is proposed for target tracking. In the second stage, a cognitive target tracking algorithm of single FDA-MIMO radar system is designed based on the criteria of maximum Capon power spectrum. In addition, in order to avoid the divergence problem of the extended Kalman filter, a target state correction method based on auxiliary particles is proposed. Finally, the fusion strategy of multiple radar trajectories is used to alleviate the estimation error of the single radar. Numerical experiments verify that the proposed CFDA-MIMON target discrimination and tracking algorithm can distinguish the target from main-lobe deceptive trajectory interference without prior information of the target, and output the target's trajectory. PubDate:
TUE, 17 JAN 2023 10:02:06 -04 Issue No:Vol. 59, No. 4 (2023)
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Authors:
Shengzhou Bai;Yujin Zhang;Yiping Jiang;Yuhan Chen;
Pages: 4223 - 4239 Abstract: This article proposes a geometric-based method of the ground-point visibility from a satellite or satellite constellation in elliptical orbit considering the J2 perturbation. First, the field-element equations describing the relationship between the elliptical satellite orbit, field parameters, and ground point are introduced and can be solved semi-analytically. Also, using a 2-D map composed of the mean argument of latitude and geographic longitude of the ascending node, the problem of calculating visible intervals is transformed into a simple intersection problem of a group of parallel lines and a time-invariant region generated by the field-element equations. Furthermore, based on the geometric relationship between any two satellites, the relative field mapping and constellation field mapping are described, which can simplify the multisatellite coverage problem to a single-satellite coverage problem and can be used to obtain the coverage performance of the constellation analytically and rapidly for the target. The simulation results demonstrate that the proposed method is rapid, efficient, intuitive, and accurate, suggesting its wide applications in constellation studies. PubDate:
WED, 08 FEB 2023 10:02:49 -04 Issue No:Vol. 59, No. 4 (2023)
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Authors:
Ziyao Wang;Jianxin Yi;Ziping Gong;Xianrong Wan;
Pages: 4240 - 4249 Abstract: Harmonic radar is a special radar system that has been widely used in insect tracking, search and rescue, and electronic equipment detection in recent years due to its excellent anti-clutter capability. However, in complex close-range scenarios, harmonic radar still suffers from nonlinear clutter interferences, which will cause a large number of clutter false alarms and seriously affect the performance of target detection. This article analyzes the mechanism and the characteristic of nonlinear clutter through experimental results in complex close-range scenarios. It is found that the nonlinear clutter is generated by the harmonics and intermodulation components of the multipath signals. More importantly, it is the first time for the multipath intermodulation phenomenon to be revealed in harmonic radar with frequency-modulated waveform. A nonlinear clutter signal model is developed to explain this special phenomenon in this article. The proposed theory is verified by the simulation and measurement results. The work in this article lays a theoretical foundation for the subsequent work on nonlinear clutter suppression. PubDate:
TUE, 17 JAN 2023 10:02:06 -04 Issue No:Vol. 59, No. 4 (2023)
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Authors:
Tianfang Zhang;Lei Li;Siying Cao;Tian Pu;Zhenming Peng;
Pages: 4250 - 4261 Abstract: Infrared small target detection techniques remain a challenging task due to the complex background. To overcome this problem, by exploring context information, this research presents a data-driven approach called attention-guided pyramid context network (AGPCNet). Specifically, we design attention-guided context block and perceive pixel correlations within and between patches at specific scales via local semantic association and global context attention, respectively. Then, the contextual information from multiple scales is fused by context pyramid module to achieve better feature representation. In the upsampling stage, we fuse the low and deep semantics through asymmetric fusion module to retain more information about small targets. The experimental results illustrate that AGPCNet has achieved state-of-the-art performance on three available infrared small target datasets. PubDate:
MON, 23 JAN 2023 10:08:37 -04 Issue No:Vol. 59, No. 4 (2023)
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Authors:
Yuanhang Wang;Tianxian Zhang;Lingjiang Kong;Zhijie Ma;
Pages: 4262 - 4273 Abstract: In this article, we study the strategy optimization problem of black-box range gate pull-off (RGPO) jamming. In the black-box RGPO jamming, the jammer does not have extensive knowledge about the tracking model of the threat radar, which makes it difficult to accurately estimate the performance of candidate jamming strategies. To address the issue, this article proposes a multimode black-box RGPO jamming method, which uses a set of local elemental simulation models to cover the possible tracking model of the threat radar, and the overall performance estimate of the candidate jamming strategies are obtained by a certain combination of the sampling results from the local elemental simulation models. To obtain the desired RGPO jamming strategy, a particle swarm optimization with optimal computing budget allocation scheme-based multimode black-box RGPO jamming strategy optimization algorithm is proposed. In addition, we construct several most widely used tracking problems as the benchmark problems to test the performance of the proposed method. Experimental results demonstrate that the proposed method is highly competitive to deal with the strategy optimization problem of the black-box RGPO jamming. PubDate:
TUE, 31 JAN 2023 10:06:33 -04 Issue No:Vol. 59, No. 4 (2023)
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Authors:
Mingying Huo;Ruhao Jin;Lie Yang;Naiming Qi;
Pages: 4274 - 4288 Abstract: Electric sail-based propulsion is an innovative propellant-less propulsion technology that generates continuous thrust through the interaction between an artificial electric field and the solar wind. In an electric sail, the propulsive acceleration is adjusted by controlling the attitude of its normal plane and the coefficient determining the maximum thrust. However, the attitude adjustment speed of the electric sail is relatively small and the direction of the normal vector is constrained. Consequently, the electric sail is required to maintain a continuous propulsive acceleration vector when flying by the intermediate targets in multitarget interplanetary exploration. Therefore, an indirect optimization of three-dimensional optimal continuous interplanetary trajectory for electric sails with refined thrust model is investigated in this article. First, the optimal propulsive angles and thrust adjustment coefficient of electric sails with a refined thrust model are derived using Pontryagin's minimum principle. Second, a homotopy function is introduced in the process of trajectory optimization with an indirect method to approximate the step of the thrust adjustment coefficient to improve the accuracy of numerical integration. Additionally, the initial costates of the electric sail are transformed from the numerical simulation results of the Bezier shaping approach (BSA) and integrative BSA (IBSA) using the Karush–Kuhn–Tucker condition. The numerical simulation results for the Earth–Mars rendezvous mission and the multitarget flyby mission reveal that the initial values of the costates are effective to implement an indirect optimization process of the optimal continuous trajectory for the rapid convergence of the electric sail. According to the numerical simulation results for multitarget mission, the indirect method is on average 2.5% better than the Gauss pseudospectral method (GPM) in overall index, and the calculation time is only 1.06% of GPM. PubDate:
MON, 13 FEB 2023 10:07:32 -04 Issue No:Vol. 59, No. 4 (2023)
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Authors:
Zhigang Zhu;Hongbing Ji;Lin Li;
Pages: 4289 - 4300 Abstract: This article investigates the problem of specific emitter identification (SEI), i.e., radar emitter fingerprint or individual emitter identification, which first measures the emitter-specific differences caused by radar's nonlinearities, e.g., mixer, power amplifiers, transmitter, and then makes a decision. In this article, the SEI problem is considered in the single-modal, dual-modal, and multimodal scenarios, respectively. First, a multimodal subspace interactive mutual unit is proposed to perform information interaction between radar signal and its multiple transformations. Based on this, a data-driven multimodal subspace interactive mutual network is then built to solve the SEI problem. Extensive experiment results demonstrate that the proposed algorithm achieves superior identification performance on the airplane measured data. PubDate:
THU, 26 JAN 2023 10:02:43 -04 Issue No:Vol. 59, No. 4 (2023)
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Authors:
Xiandong Pu;Chunyan Zhang;Jianlei Zhang;
Pages: 4301 - 4312 Abstract: MTRT is an extension of path planning that aims to traverse multiple targets in an unknown environment at the lowest cost. The MTRT is governed by the “multitarget” demand leading to a rather extensive search space and the “real-time” requirement that imposes fast planning. However, the traditional path planning algorithm A* is notoriously inefficient in large spaces. Therefore, spurred by the low efficiency of A* for MTRT, this article proposes the DAA, which implements an adaptive multitarget heuristic function and an adaptive node expansion method to accelerate planning. The suggested method is evaluated utilizing the following two approaches to establishing the search space: 1) decompose MTRT into traditional path planning problems and involve one target at a time; 2) consider all unsearched targets while planning. Simulations in discrete grid maps demonstrate that DAA provides at least equivalent searching paths to A* and other algorithms, but at much less running time. PubDate:
TUE, 31 JAN 2023 10:06:33 -04 Issue No:Vol. 59, No. 4 (2023)
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Authors:
Jaymin Patel;Boris Pervan;
Pages: 4313 - 4332 Abstract: In this article, we generate accurate global positioning system (GPS) legacy navigation (LNAV) orbital parameters to provide truth satellite positions and satellite clock biases for advanced receiver autonomous integrity monitoring offline monitoring. In our prior work, we proposed an estimator to determine satellite positions and clock biases, and here, we demonstrate the estimator performance using experimental data. We utilize the International global navigation satellite systems Service (IGS) ground network to collect dual-frequency raw GPS code and carrier phase measurements. The estimator is modified to handle practical challenges of experimental data, and detailed insight of estimated LNAV parameters and clock biases are discussed. The resulting signal-in-space ranging errors (SISREs) from the estimated LNAV parameters and clocks are predicted by covariance analysis to have a standard deviation $\sigma$ = 0.5 m. The performance of estimated LNAV parameters and clock biases is evaluated over ten days, and when compared with precise IGS orbit and clock products, the resulting SISREs are within $2\sigma$ at all times. PubDate:
FRI, 03 FEB 2023 10:02:54 -04 Issue No:Vol. 59, No. 4 (2023)
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Authors:
Ruoming Li;Wangzhe Li;Yongwei Dong;Zhilei Wen;Hanqing Zhang;Wei Sun;Jiyao Yang;Henan Zeng;Yuhui Deng;Yuchen Luan;Weidi Xu;Siwen Yang;Zhenwei Mo;
Pages: 4333 - 4346 Abstract: The next generation of synthetic aperture radar (SAR) systems will need transmit and receive analog signals over a wide frequency range with large bandwidth to fulfil the increasing demands. Since the performance of the digital microwave component is deteriorated at increasing frequency, radio frequency (RF) front-end with the capability of frequency conversion is needed for frequency beyond a few gigahertz. However, for the widely employed RF mixers, the inherent imperfect of I-V characteristics of nonlinear devices, generates many undesired mixing spurs, which restricts on the instantaneous bandwidth and the spurious-free dynamic range. At Aerospace Information Research Institute Chinese Academy of Sciences, a photonic-assisted front-end with functions of signal generation and deramp processing has been conceived and implemented in an experimental deramp-on-receive CW SAR system. The system is called Photonic-Assisted Front-End Deramp-on-Receive Imaging Radar and is envisaged to obtain SAR imaging at high resolution. In current stage, the Ku-band system with a bandwidth of 5.72 GHz, corresponding to a relative bandwidth of 37.8%, operates well with a fixed two-horn antenna. The configuration of the photonic front-end and the system design are described. Ground-based tests and airborne imaging results with geometrical resolution down to 5 cm are presented. PubDate:
THU, 26 JAN 2023 10:02:43 -04 Issue No:Vol. 59, No. 4 (2023)
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Authors:
Omar García Crespillo;Steve Langel;Mathieu Joerger;
Pages: 4347 - 4362 Abstract: Safety-critical navigation applications require that estimation errors be reliably quantified and bounded. This can be challenging for linear dynamic systems if the process noise or measurement errors have uncertain time correlation. In many systems (e.g., in satellite-based or inertial navigation systems), there are sources of time-correlated sensor errors that can be well modeled using Gauss–Markov processes (GMP). However, uncertainty in the GMP parameters, particularly in the correlation time constant, can cause misleading error bounds. In this article, we develop time-correlated models that ensure tight upper bounds on the estimation error variance, assuming that the actual error is a stationary first-order GMP with a variance and time constant that are only known to reside within an interval. We first use frequency-domain analysis to derive stationary GMP models in both the continuous and discrete-time domains, which outperform models previously described in the literature. Then, we derive an even tighter estimation error bound using a nonstationary GMP model, for which we determine the minimum initial variance that guarantees bounding conditions. Both models can easily be implemented in a linear estimator like the Kalman filter. PubDate:
TUE, 07 FEB 2023 10:05:21 -04 Issue No:Vol. 59, No. 4 (2023)
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Authors:
Wentao Wang;Yongqing Wang;Yuyao Shen;Siliang Wu;
Pages: 4363 - 4379 Abstract: Existing cross-correlation mitigation algorithms based on the minimum mean square error (MMSE) criterion can effectively suppress multiple access interference (MAI) but suffer from high complexity and modeling grid mismatch. In this work, we propose a cell-straddling robust-fast cross-correlation mitigation (CSR-FCCM) algorithm with two improvements. First, CSR-FCCM combines the 2-D joint iterative adaptive filtering with interference cancellation, which significantly reduces the number and computational cost of complex amplitude MMSE filters. Second, two discriminators are designed to estimate the straddling offset of delay and frequency for the direct sequence spread spectrum signal. The mismatch problem can be ameliorated by substituting estimated straddling offsets into the signal model, which further improves the MAI mitigation effect. The effectiveness of the CSR-FCCM is verified by simulations using 1023- and 63-length gold codes. Simulation results show that CSR-FCCM has a better MAI mitigation performance and a lower complexity than the open-loop MAI mitigation algorithms, including 2-D jointly iterative adaptive filter and RSR-APC. PubDate:
THU, 02 FEB 2023 10:05:38 -04 Issue No:Vol. 59, No. 4 (2023)
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Authors:
Zhijun Wu;Cheng Liang;Yuan Zhang;
Pages: 4380 - 4392 Abstract: The civil navigation message (CNAV) of the global navigation satellite system (GNSS) is transmitted in an open channel without authentication and integrity protection mechanism. Therefore, the CNAV is facing the threat of interception and tampering, and it is vulnerable to spoofing attacks. To guarantee the authenticity and integrity of CNAV, we propose a cryptographic antispoofing scheme of CNAV in GNSS based on consortium blockchain using domestic cryptographic algorithms. In this scheme, we design a CNAV authentication model based on satellites, ground stations, and key management center, and implement the authentication protocol to achieve the purpose of preventing CNAV in GNSS from being tampered with. On the basis of the authentication of the entities, the scheme further realizes the functions of information source authentication and integrity protection of the legitimate senders. On the basis of satisfying security, the protocol has lower computing and communication cost, simplifies the process of reauthentication of information source, and has great practicability for receivers that use civil navigation message to achieve navigation and positioning functions. PubDate:
TUE, 31 JAN 2023 10:06:33 -04 Issue No:Vol. 59, No. 4 (2023)
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Authors:
Ignacio Fernandez-Hernandez;Jón Winkel;Cillian O'Driscoll;Simón Cancela;Rafael Terris-Gallego;Jose A. López-Salcedo;Gonzalo Seco-Granados;Andrea Dalla Chiara;Carlo Sarto;Daniel Blonski;Javier de Blas;
Pages: 4393 - 4404 Abstract: A semiassisted global navigation satellite systems (GNSS) authentication concept is proposed, with two main advantages. First, it can be implemented in a GNSS without modifications to the signal plan, provided that the GNSS can transmit an encrypted signal and an open signal with unpredictable and verifiable bits regularly. Second, it can work in a receiver for up to several days without any assistance or the possession of a private key, at the expense of some authentication latency. In this concept, parts of the encrypted signal to be transmitted in the future are re-encrypted, published, and downloaded in the receiver. Some seconds after transmission, the satellite openly broadcasts the decryption key, and the receiver performs the a-posteriori correlation with the encrypted signal. The concept is particularized for the Galileo system as Galileo assisted commercial authentication service, based on OSNMA in E1B for the decryption keys and E6C for the encrypted signal. An end-to-end procedure for measurement authentication is proposed and tested, showing its viability. PubDate:
THU, 09 FEB 2023 10:01:54 -04 Issue No:Vol. 59, No. 4 (2023)
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Authors:
Francesco A. Palmieri;Christopher Franzini;Peter Willett;Yaakov Bar-Shalom;
Pages: 4405 - 4413 Abstract: We analyze the likelihood distribution for a multipath model in which no target is present, focusing on the peculiarities of the maximum-likelihood probabilistic multi-hypothesis tracker (ML-PMHT) when multiple peaks emerge. We study analytically the case in which peaks are separated and for the general case we propose a numerical algorithm based on sampling. The final distribution is used to compute a parameter-dependent false alarm probability threshold. PubDate:
TUE, 07 FEB 2023 10:05:21 -04 Issue No:Vol. 59, No. 4 (2023)
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Authors:
Gongjian Zhou;Bin Zhu;Xiaoping Ye;
Pages: 4414 - 4433 Abstract: In most of the existing state estimation algorithms for maneuvering target tracking, the formulation of the mode switching process fails to accurately capture the deterministic law that the target mode will persist for a period of time once it turns to be in effect. In this article, two strategies are presented to describe this characteristic. First, a constraint that model switching occurs no more than once over three consecutive time steps is proposed to provide a deterministic description that mode does not switch continuously. Second, considering target mode always lasts for some time while mode switching is completed instantly, the transition probabilities from one model to itself are fixed at extremely large values to enhance the certainty in mode sojourn segments. Based on these strategies, two recursive multiple model (MM) filters are derived in the framework of generalized pseudo-Bayesian (GPB) estimation and interacting multiple model (IMM) estimation, respectively. In both algorithms, although the large probability of model staying unchanged causes high peak errors at mode switching instants, the introduction of the switching constraint prevents the input to the mode-matched filter from being affected by the model transition probability, thereby obtaining a near-optimal performance in mode sojourn segments. Additionally, in order to reduce the peak estimation errors, a mode switching detector based on likelihood function is presented to work in parallel with the recursive MM filters. Once the detector declares that a mode switch occurs, the final estimate is adjusted from the output of the recursive MM filters to the estimate of the corresponding elemental filter, performance of which is guaranteed by the switching constraint. Simulation results demonstrate the capability of the proposed recursive MM filters to obtain performance close to that of a filter without model uncertainty in mode sojourn segments and the effectiveness of the mode switching detector to reduce peak errors at the same time. PubDate:
MON, 13 FEB 2023 10:07:32 -04 Issue No:Vol. 59, No. 4 (2023)
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Authors:
Yachao Li;Jiadong Wang;Yu Wang;Pan Zhang;Lei Zuo;
Pages: 4434 - 4449 Abstract: Among the various types of jamming, active deception jamming has similar characteristics to the transmitted signal. The jamming seriously affects the detection and tracking of real targets by radar. In recent years, waveform design has become an effective antijamming method with the maturity of waveform generator technology. However, most antijamming waveforms are only designed to combat a single kind of jamming. To compensate for the shortage of existing waveforms that cannot simultaneously combat compound deception jamming, we construct an interpulse–intrapulse joint frequency-coded (I-IJFC) antijamming waveform and analyze the antijamming process flow. Moreover, to reduce the influence of residual jamming, we propose an intrapulse-frequency-coded method based on jamming parameters estimation. The waveform can be used against crosspulse repeater deception jamming and interrupted sampling jamming. Then, to solve the problem that the existing algorithm cannot realize the coherent accumulation of the proposed waveform, we propose a coherent accumulation algorithm of subpulse rearrangement compensation and nonuniform discrete Fourier transform. The simulation examples show that the waveform proposed in this article performs better against compound deception jamming than existing waveforms, and the proposed algorithm can realize the coherent accumulation of I-IJFC echo signals. PubDate:
FRI, 10 FEB 2023 10:02:19 -04 Issue No:Vol. 59, No. 4 (2023)
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Authors:
Min-Seok Kang;Jae-Min Baek;
Pages: 4450 - 4463 Abstract: For synthetic aperture radar (SAR) imaging, the irregular loss of received data and the nonuniformly under sampling yield the SAR azimuth ambiguity (SAA) resulting in the degradation in image quality. To address this issue, the incremental SAR imaging approach based on the estimation of sensing dictionary matrix in the pursuit of sparsity is presented in this article. Several beneficial contributions are included in the proposed method. First, the SAA reduction achievable in the proposed method is considerably improved more than that of the conventional compressive sensing (CS)-based approach in terms of the image quality and computational efficiency. Second, we established the signal parameterization scheme, which is divided into coarse and fine search steps to estimate the sensing matrix for SAR image restoration via signal model reconstruction. Third, an incremental imaging approach is devised to overcome the drawback of the conventional CS-based approach, which is not sufficiently good leading to limited SAA reduction performance under the nonsparse SAR image. These contributions are verified using numerical simulations and experimental results. PubDate:
FRI, 03 FEB 2023 10:02:54 -04 Issue No:Vol. 59, No. 4 (2023)
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Authors:
Jian Lan;
Pages: 4464 - 4477 Abstract: For extended object tracking (EOT), a fluctuating number of measurements are generated by a sensor at a time instant. In practice, the measurement number depends on the object extension, sensor resolution, and sensor-to-object geometry. Given the sensor resolution, the number, thus, contains information on the object state and extension. This article proposes a random-matrix approach to EOT utilizing this information to improve the performance of state and extension estimation. First, a Gamma-alike distribution of the measurement number is proposed to model the dependence of the number on sensor resolution and the object state and extension. This model also fits the random-matrix framework. Second, a Bayesian approach to jointly estimating the state and extension based on an extension-dependent number of measurements is derived. Facilitated by the form of the distribution, the derived approach has an analytical form and it can naturally reduce to an EOT approach without directly using measurement numbers. The proposed number model can also be incorporated with different random-matrix approaches. The effectiveness of the proposed approach is demonstrated by evaluation results using one simulation and two real-data experimental scenarios compared with existing random-matrix algorithms. PubDate:
FRI, 03 FEB 2023 10:02:54 -04 Issue No:Vol. 59, No. 4 (2023)
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Authors:
Qinglong Hua;Yun Zhang;Yicheng Jiang;Dan Xu;
Pages: 4478 - 4492 Abstract: In a synthetic aperture radar (SAR) system, target rotation during the coherent integration time results in a time-varying Doppler frequency shift and a blurred image. Blurred images are not conducive to subsequent information interpretation. This article proposes a complex-valued channel fusion U-shape network (CV-CFUNet) for the 3-D rotation refocusing task of ship targets. The proposed method integrates the refocusing task into a blind inverse problem. To take advantage of the amplitude and phase information of complex SAR images, all elements of CV-CFUNet, including convolutional layer, activation function, feature maps, and network parameters, are extended to the complex domain. The proposed CV-CFUNet is designed by adopting a complex-valued encoder (CV-Encoder), channel fusion module (CFM), and complex-valued decoder (CV-Decoder) to adaptively learn complex features. Experiments on simulated data, GF-3 data, and Sentinel-1 data show that the proposed method achieves significant improvements over existing methods in both efficiency and refocusing accuracy. PubDate:
TUE, 06 JUN 2023 10:02:23 -04 Issue No:Vol. 59, No. 4 (2023)
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Authors:
Lingxiao Zhu;Gongjian Wen;Yuanyuan Liang;Dengsanlang Luo;Haojun Jian;
Pages: 4493 - 4510 Abstract: Target localization is one of the most important research topics in the field of radar signal processing. In this article, the problem of multitarget enumeration and localization in the distributed multiple-input multiple-output radar with noncoherent processing mode is investigated. We first analyze the theoretical bound of the multitarget localization accuracy under the discrete time signal model and the Swerling 1 target model. It is determined by the Cram$\acute{\text{e}}$r–Rao lower bound at a low signal-to-noise ratio (SNR) and the sampling lower bound when the SNR is high. Furthermore, an innovative multitarget enumeration and localization scheme is developed, which is based on the energy modeling of the multiple transmitter–receiver paths and the compressive sensing theory. To solve the sparse vector recovery issue, we design a lightweight iterative greedy pursuit algorithm including the similarity evaluation strategy. In addition, an iterative-based target position refinement process is designed to alleviate the off-grid problem caused by the spatial discretization. The proposal utilizes the samples of the raw signals and belongs to the category of the direct localization. Nevertheless, it has significantly higher computational efficiency and lower data communication burden than the conventional direct localization methods, while avoiding the complex data association encountered by the indirect localization methods. Finally, the simulation results validate the effectiveness and robustness of the proposed method. PubDate:
TUE, 07 FEB 2023 10:05:21 -04 Issue No:Vol. 59, No. 4 (2023)
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Authors:
Guofei Li;Zongyu Zuo;
Pages: 4511 - 4524 Abstract: This article investigates the problem of leader–follower cooperative guidance in consideration of false-data injection attacks (FDIAs). Both the leader and the followers are required to reach the target at a desired impact time, while only the leader can receive the impact time command. A fixed-time convergent guidance law is presented for the leader to hit the target with impact time control. A distributed observer is introduced for each follower to estimate the leader's time to go. The confidence factors and the trust factors are exploited in the distributed observer to cope with FDIAs. Governed by the proposed distributed observer-based cooperative guidance law, the leader and the followers can achieve the simultaneous arrival in the presence of FDIAs. To facilitate the seekers detecting the target, the field-of-view angles of all the flight vehicles can be limited in a permissible range. Numerical simulation is carried out to verify the effectiveness. PubDate:
MON, 06 FEB 2023 10:04:28 -04 Issue No:Vol. 59, No. 4 (2023)
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Authors:
Yuebin Wang;Wenbin Yang;Dan Li;Jian Qiu Zhang;
Pages: 4525 - 4539 Abstract: In this article, the decomposition and retrieval of the chirp modes with dynamic cross, appearance, and/or disappearance in a signal are formulated as a process of tracking time-frequency (TF) trajectories. Analyses show that the amplitude and frequency evolutions of each chirp mode in the signal can be described by polynomial prediction models. When all these evolutions are viewed as state equations, it is illustrated that the random appearance and/or disappearance of these modes will make the state equations into a state random finite set (RFS). If the amplitudes and frequencies obtained by the short-time spectrum of the signal are taken as the measurements of the state equations, a measurement RFS model in the presence of data association and detection uncertainties is coined when the statistical properties of the existing and newborn chirp modes as well as the noise/clutter are taken into consideration. So, an RFS TF model for tracking the TF trajectories in a signal is established. It is then demonstrated that a modified probability hypothesis density filter can be used to infer the amplitude and frequency posterior distributions of the chirp modes in the signal when the intensity of the RFS states is modeled as a Gaussian mixture. Numerical simulation experiments verify the effectiveness of our model and analytical results. Meanwhile, a superior performance is achieved especially for the high readability, extractability, and decomposability of instantaneous frequency trajectories with dynamic cross, appearance, and disappearance in a signal. PubDate:
MON, 13 FEB 2023 10:07:32 -04 Issue No:Vol. 59, No. 4 (2023)
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Authors:
Ling Hong;Fengzhou Dai;
Pages: 4540 - 4558 Abstract: In this article, the problem of wideband radar target detection in a heterogeneous environment is addressed. The wideband radar return of the target with range migration is characterized as a subband model, and the heterogeneous clutter is described with a hierarchical Bayesian model. Both the prior knowledge of the clutter power and the covariance matrix and the dependence of the primary data and the secondary data are characterized by the inverse gamma and the inverse complex Wishart distribution, respectively. Based on the target and the clutter models, knowledge-aided maximum posterior ratio test, knowledge-aided Rao test, and knowledge-aided Wald test for wideband radar target detection in heterogeneous clutter are proposed. Finally, the performance of the proposed detectors is evaluated by simulations with both the simulated clutter generated by the probability model and the synthesized clutter from a real synthetic aperture radar complex image. The results show that the proposed knowledge-aided detectors are effective for wideband radar target detection in heterogeneous clutter. PubDate:
TUE, 07 FEB 2023 10:05:21 -04 Issue No:Vol. 59, No. 4 (2023)
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Authors:
Ban Wang;Dehai Zhu;Linying Han;Honggang Gao;Zhenghong Gao;Youmin Zhang;
Pages: 4559 - 4574 Abstract: This article proposes an adaptive fault-tolerant control scheme for an overactuated hybrid vertical take-off and landing canard rotor/wing unmanned aerial vehicle (UAV) to simultaneously compensate actuator faults and model uncertainties without the requirement of fault information and uncertain bounds. The proposed control scheme is constructed with two separate control modules. The high-level control module is developed with a novel adaptive sliding-mode controller, which is employed to maintain the overall system tracking performance in both faulty and fault-free conditions. The low-level control allocation module is used to distribute the virtual control signals that are generated by the high-level control module among the available redundant actuators. In the case of actuator faults, the proposed adaptive scheme can seamlessly adjust the control parameters to compensate the virtual control error and reconfigure the distribution of control signals among the available redundant actuators. A significant feature of this study is that the stability of the closed-loop system is guaranteed theoretically in the presence of both actuator faults and model uncertainties and overestimation of the adaptive control parameters can be avoided. The effectiveness of the proposed control strategy is validated through comparative simulation tests under different faulty and uncertain scenarios. PubDate:
THU, 09 FEB 2023 10:01:54 -04 Issue No:Vol. 59, No. 4 (2023)
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Authors:
Bowen Su;Fan Zhang;Panfeng Huang;
Pages: 4575 - 4589 Abstract: This article studies the open-loop stability analysis and radial-basis-function-based neural network (RBFNN) control of triangular tethered satellite formation (TTSF) systems, comprised of the in-plane and out-plane dynamics. The dynamical equations of TTSF are nonlinear coupled second-order differential equations (DEs), whose explicit solutions are hard to work out. Therefore, the dynamics of systems are analyzed by imposing some constraints on initial states, and the norms of proper initialization for such TTSF systems are obtained by solving the DE. As a result, the nonlinear controllers achieving stable tracking to reference states of TTSF systems are designed based on open-loop analysis. Furthermore, when the structure information of the system is uncertain, delay-sampled neural network and offline training neural network control algorithms are proposed to train the RBFNN, and the optimal weights of the neural network are computed by the least squares method. Then, RBFNN control is imposed to the uncertain TTSF system to ensure stable tracking, and the stability proof of the control is given. Finally, simulations are taken on the specific motions of the TTSF system to test the theoretical results. PubDate:
THU, 09 FEB 2023 10:01:54 -04 Issue No:Vol. 59, No. 4 (2023)
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Authors:
Jianglong Yu;Zhexin Shi;Xiwang Dong;Qingdong Li;Jinhu Lv;Zhang Ren;
Pages: 4590 - 4603 Abstract: Cooperative guidance issues with impact time consensus against a maneuvering target are considered in this article. Different from the existing achievements, the expected impact time does not need to be predesigned, which is coordinated by multiple missiles using the neighboring information. First, the impact time consensus command is generated by using the maximum consensus algorithm of time-to-go for each missile. Second, an analytical cooperative guidance law with bias proportional guidance form is proposed for achieving impact time consensus. In addition, the convergence and the stability of the proposed algorithm and guidance law are analyzed. Third, an equivalent guidance experimental platform is constructed for testing the performance of the proposed cooperative guidance strategy. Finally, the numerical simulation and experimental results are presented to verify the effectiveness of the proposed theoretical cooperative guidance methods. PubDate:
WED, 08 FEB 2023 10:02:49 -04 Issue No:Vol. 59, No. 4 (2023)
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Authors:
Kaitlin Dennison;Nathan Stacey;Simone D'Amico;
Pages: 4604 - 4624 Abstract: This article first defines a class of estimation problem called simultaneous navigation and characterization (SNAC), which is a superset of simultaneous localization and mapping (SLAM). A SNAC framework is then developed for the Autonomous Nanosatellite Swarming (ANS) mission concept to autonomously navigate about and characterize an asteroid including the asteroid gravity field, rotational motion, and 3-D shape. The ANS SNAC framework consists of three modules: 1) multiagent optical landmark tracking and 3-D point reconstruction using stereovision, 2) state estimation through a computationally efficient and robust unscented Kalman filter, and 3) reconstruction of an asteroid spherical harmonic shape model by leveraging a priori knowledge of the shape properties of celestial bodies. Despite significant interest in asteroids, there are several limitations to current asteroid rendezvous mission concepts. First, completed missions heavily rely on human oversight and Earth-based resources. Second, proposed solutions to increase autonomy make oversimplifying assumptions about state knowledge and information processing. Third, asteroid mission concepts often opt for high size, weight, power, and cost (SWaP-C) avionics for environmental measurements. Finally, such missions often utilize a single spacecraft, neglecting the benefits of distributed space systems. In contrast, ANS is composed of multiple autonomous nanosatellites equipped with low SWaP-C avionics. The ANS SNAC framework is validated through a numerical simulation of three spacecraft orbiting asteroid 433 Eros. The simulation results demonstrate that the proposed architecture provides autonomous and accurate SNAC in a safe manner without an a priori shape model and using only low SWaP-C avionics. PubDate:
WED, 22 FEB 2023 07:51:31 -04 Issue No:Vol. 59, No. 4 (2023)
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Authors:
Yi Liao;Zhibang Luo;Jian Wang;Zhi Zheng;Shunsheng Zhang;
Pages: 4625 - 4639 Abstract: Mosaic synthetic aperture radar (SAR) can achieve high resolution and wide swath (HRWS) imaging by steering its antenna beam elaborately. However, its unique time-frequency diagram and radiometric variation challenge the imaging. The conventional methods cannot be applied to mosaic SAR imaging directly. To address these problems, this article takes the imaging geometry into consideration, utilizing time frequency transform to suppress the spectrum ambiguity. Then, the azimuth nonlinear chirp scaling (NCS) algorithm is performed to compensate the variant modulation and the pattern weighting approach is used to correct the radiometric variance. Simulation results verify the effectiveness of the spectrum analysis and the proposed imaging algorithm. PubDate:
TUE, 21 FEB 2023 04:43:39 -04 Issue No:Vol. 59, No. 4 (2023)
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Authors:
Guangdeng Chen;Yang Liu;Deyin Yao;Hongyi Li;Choon Ki Ahn;
Pages: 4640 - 4650 Abstract: This study is aimed at addressing the event-based state estimation and tracking control problems for a class of nonlinear systems, the output of which is measured by multiple sensors, but the adversary can manipulate nearly half of the measurements simultaneously. First, a sampled-data-based event-triggered strategy is developed to reduce unnecessary data transmissions under sparse sensor attacks, and the transmitted data are filtered by a data selector to obtain reliable data. Subsequently, an output-prediction-based continuous-discrete observer is improved so that it can estimate continuous-time system states from the event-triggered output, rather than being limited to time-triggered sampled output. Further, to design a tracking controller with the segmentally differentiable estimated states, a backstepping method incorporating tracking differentiators is proposed. Finally, the effectiveness of the proposed method is demonstrated by applying it in the simulation of a rigid aircraft. PubDate:
MON, 20 FEB 2023 10:48:02 -04 Issue No:Vol. 59, No. 4 (2023)
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Authors:
Zesi Pan;Yunjie Li;Shafei Wang;Yan Li;
Pages: 4651 - 4665 Abstract: Developing intelligent jamming methods to combat the multifunction radar (MFR) has become a vital task in electronic warfare, because the MFR can tune into different working modes according to surrounding environment information. In this article, we present a solution to the limitations of conventional jamming methods, including strong prior knowledge dependence and inaccurate selection strategies. Specifically, we study a joint optimization of jamming type selection and power control task (JO-JTSPC) for a general radar countermeasure scenario. In particular, we first model the sequential decision-making task JO-JTSPC as a Markov decision process (MDP). Subsequently, considering the differences in the designed action space, we accordingly develop two algorithms, i.e., dueling double deep Q-learning and hybrid proximal policy optimization, to solve the optimization problem. Taking into consideration the threat level of various MFR working modes and the corresponding required jamming effect, we elaborately design the reward function of MDP as a weighted summation of the mode switching factor, jamming performance factor, and jamming power factor. Further, the learned polices of these algorithms are derived based on the designed reinforcement learning elements. Extensive simulation results demonstrate that the proposed algorithms can learn highly adaptive polices in the radar countermeasure scenarios and achieve good jamming performance. PubDate:
TUE, 02 MAY 2023 10:14:46 -04 Issue No:Vol. 59, No. 4 (2023)
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Authors:
Tyler D. Ridder;Anthony F. Martone;Benjamin H. Kirk;Ram M. Narayanan;
Pages: 4689 - 4699 Abstract: The concept of metacognition has been proposed and applied to radar system analysis to enhance the classical cognitive radar paradigm. Metacognition allows a cognitive radar to have self-awareness about its cognitive processes. To accurately compare various cognitive processes and select the best under the operational scenario, a performability metric capable of comparing system performance over various scales and units is proposed and analyzed. This correspondence expands previous work on radar operational reliability to provide a metareliability metric for a metacognitive tracking radar. The approach is tested and validated on a radar that tracks a target performing a composite maneuver involving constant velocity, constant turn, and constant acceleration. PubDate:
FRI, 06 JAN 2023 10:02:32 -04 Issue No:Vol. 59, No. 4 (2023)
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Authors:
Olivier Besson;
Pages: 4700 - 4708 Abstract: We address the problem of detecting a signal of interest in Gaussian noise with an unknown covariance matrix, when the amplitude of the signal fluctuates along the observations and follows a Rice distribution. This is typical of a target that consists of one large dominant scatterer and a collection of small independent scatterers. We formulate it as a composite hypothesis testing problem, for which we derive the generalized likelihood ratio test, and show that it ensures a constant false alarm rate. Numerical simulations enable to assess its performance for Rician as well as Swerling I and III targets. It is shown that the new detector incurs no loss for Swerling targets but can offer a significant improvement for Rician targets, especially when the number of training samples is small. PubDate:
THU, 05 JAN 2023 10:02:33 -04 Issue No:Vol. 59, No. 4 (2023)
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Authors:
Yigen He;Xuesen Shi;Yongqing Wang;Yuyao Shen;
Pages: 4709 - 4720 Abstract: This study focuses on a Doppler frequency search strategy for signal acquisition in direct-sequence spread spectrum (DSSS) systems. According to DSSS signal accumulation energy vibration characteristics, the whole 2-D search region can be divided into the non-vicinity region, the transition region, and the vicinity region. If only one search strategy is used for the whole region, it is difficult to balance the frequency search times and the frequency estimation accuracy. To solve the above problem, this study proposes an intelligent Doppler frequency search (IDFS) strategy. A fuzzy logic (FL) controller with two sets of fuzzy parameters is utilized to adjust the frequency search step size in the non-vicinity region and the vicinity region, respectively. In the non-vicinity region, by jointly considering signal amplitude and code phase to design the fuzzy parameters of the FL controller, the IDFS strategy can reduce the frequency search times while reducing frequency false detection caused by an abnormal change of signal energy. In the vicinity region, the fuzzy parameters are designed based on our previous work, which aims to achieve higher frequency estimation accuracy. The effectiveness of the IDFS strategy is evaluated through Monte Carlo simulations. Simulation results show that the proposed intelligent search strategy can reduce the frequency search times while ensuring frequency estimation accuracy compared to other existing search strategies. Moreover, the proposed search strategy can reduce false detection in the non-vicinity region PubDate:
MON, 09 JAN 2023 10:04:05 -04 Issue No:Vol. 59, No. 4 (2023)
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Authors:
Azer P. Shikhaliev;Braham Himed;
Pages: 4721 - 4728 Abstract: We derive several parametric detectors for the case of a ground-based distributed multiple-input multiple-output radar system with colocated transmitters and receivers. The proposed detectors are based on exact and approximate generalized likelihood ratio tests. For the transmit–receive paths, which start and end at the same node, we incorporate the constraint of spectral symmetry, meaning that the clutter returns are assumed to have a power spectral density that is symmetric around the zero Doppler, which is motivated by statistical analyses performed on measured clutter radar data. Our numerical simulations suggest that the proposed parametric detectors, which incorporate the physics-based spectral symmetry constraint on clutter returns, achieve better performance than previously investigated parametric detection approaches which do not incorporate this constraint. PubDate:
MON, 23 JAN 2023 10:08:37 -04 Issue No:Vol. 59, No. 4 (2023)
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Authors:
Sung Joon Maeng;Md Moin Uddin Chowdhury;İsmail Güvenç;Arupjyoti Bhuyan;Huaiyu Dai;
Pages: 4729 - 4737 Abstract: Reliable wireless coverage in drone corridors is critical to enable a connected, safe, and secure airspace. To support beyond-visual-line-of-sight operations of aerial vehicles in a drone corridor, cellular base stations (BSs) can serve as a convenient infrastructure as they are widely deployed to provide seamless wireless coverage. However, antennas in the existing cellular networks are downtilted to optimally serve their ground users, which results in coverage holes at higher altitudes when they are used to serve drones. In this article, we consider the use of additional uptilted antennas at each cellular BS and optimize the uptilt angle to maximize the wireless coverage probability across a given drone corridor. Through numerical results, we characterize the optimal value of the antenna uptilt angle for a given antenna pattern as well as the minimum/maximum altitudes of the drone corridor. PubDate:
THU, 19 JAN 2023 10:01:49 -04 Issue No:Vol. 59, No. 4 (2023)
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Authors:
Pirmin Schoeder;Vinzenz Janoudi;Timo Grebner;Christian Waldschmidt;
Pages: 4738 - 4743 Abstract: In order to simulate highly realistic scenarios for modern radar sensors, like traffic scenarios, radar target simulators require the capability to generate targets in all four radar dimensions, which are range, radial velocity, azimuth, and elevation angle. To generate targets with angular information, coherent direction-of-arrival (DoA) simulation allows a highly accurate and flexible angular simulation, at a minimum of the required hardware. In this article, a unifying general model for coherent DoA simulation with channel knowledge for radar target simulators is derived. It comprises previous models. We present methods that allow the simulation of arbitrary and adjustable DoAs, without any constraints on the radar array geometry or the implemented beamformer. The proposed models and methods are analytically derived, analyzed by simulations, and finally verified by measurements. Lastly, a measurement of a 2D-DoA simulation for a radar with 12 channels is conducted, in order to show the general applicability of the concept. PubDate:
MON, 30 JAN 2023 10:11:53 -04 Issue No:Vol. 59, No. 4 (2023)
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Authors:
Berkan Dulek;Suleyman Taylan Topaloglu;Sinan Gezici;
Pages: 4744 - 4752 Abstract: A restricted Bayes approach is proposed for linear estimation of a scalar random parameter based on a scalar observation under uncertainty regarding the correlation between the parameter and the observation. In particular, the optimal linear estimator that minimizes the average mean-squared error (MSE) is derived under a constraint on the worst-case MSE by considering possible values of the correlation coefficient and its probability distribution. A closed-form expression is derived for the optimal linear estimator in the proposed restricted Bayesian framework by considering a generic statistical characterization of the correlation coefficient. Performance of the proposed estimator is evaluated via numerical examples and its benefits are illustrated in various scenarios. The proposed framework is also extended to the case of vector-valued observation and the properties of the optimal linear estimator are characterized. PubDate:
TUE, 31 JAN 2023 10:06:33 -04 Issue No:Vol. 59, No. 4 (2023)
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Authors:
Ying Zhang;Lei Ma;Chunyu Yang;Linna Zhou;Guoqing Wang;Wei Dai;
Pages: 4753 - 4762 Abstract: This article looks into the topic of distributed formation control for a group of quadrotors that are vulnerable to denial-of-service (DoS) attacks. By preventing information interaction between adjacent quadrotors, the DoS attacks, which happen independently on individual communication channels, disrupt the formation mission. A decomposition-combination control framework is devised for the formation task. The corresponding high-order dynamic system is partitioned into slow and fast subsystems using the singular perturbation technique, which lessens the computing load and resolves the under-driven issue. A composition formation control scheme is then put forward, which includes a resilient slow-scale controller to tackle DoS attacks along with an optimal fast-scale controller to assure flying performance and stability. It should be noted that position and velocity information, which can be acquired and processed entirely by subcontroller in the proposed method, is the main content of communication between quadrotors, permitting more effective system execution. Finally, a slow-fast composition mechanism is provided, and simulation results of a system containing four quadrotors serve as validation for the suggested methods. PubDate:
TUE, 31 JAN 2023 10:06:33 -04 Issue No:Vol. 59, No. 4 (2023)
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Authors:
Huiping Huang;Qi Liu;Hing Cheung So;Abdelhak M. Zoubir;
Pages: 4763 - 4773 Abstract: Distorted sensors could occur randomly and may lead to the breakdown of a sensor array system. In this article, we consider an array model within which a small number of sensors are distorted by unknown sensor gain and phase errors. With such an array model, the problem of joint direction-of-arrival (DOA) estimation and distorted sensor detection is formulated under the framework of low-rank and row-sparse decomposition. We derive an iteratively reweighted least squares (IRLS) algorithm to solve the resulting problem. The convergence property of the IRLS algorithm is analyzed by means of the monotonicity and boundedness of the objective function. Extensive simulations are conducted regarding parameter selection, convergence speed, computational complexity, and performances of DOA estimation as well as distorted sensor detection. Even though the IRLS algorithm is slightly worse than the alternating direction method of multipliers in detecting the distorted sensors, the results show that our approach outperforms several state-of-the-art techniques in terms of convergence speed, computational cost, and DOA estimation performance. PubDate:
FRI, 03 FEB 2023 10:02:54 -04 Issue No:Vol. 59, No. 4 (2023)
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