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  Subjects -> ELECTRONICS (Total: 179 journals)
Showing 1 - 200 of 277 Journals sorted alphabetically
Acta Electronica Malaysia     Open Access  
Advances in Biosensors and Bioelectronics     Open Access   (Followers: 7)
Advances in Electrical and Electronic Engineering     Open Access   (Followers: 5)
Advances in Electronics     Open Access   (Followers: 78)
Advances in Magnetic and Optical Resonance     Full-text available via subscription   (Followers: 8)
Advances in Microelectronic Engineering     Open Access   (Followers: 13)
Advances in Power Electronics     Open Access   (Followers: 33)
Advancing Microelectronics     Hybrid Journal  
Aerospace and Electronic Systems, IEEE Transactions on     Hybrid Journal   (Followers: 313)
American Journal of Electrical and Electronic Engineering     Open Access   (Followers: 24)
Annals of Telecommunications     Hybrid Journal   (Followers: 9)
APSIPA Transactions on Signal and Information Processing     Open Access   (Followers: 9)
Archives of Electrical Engineering     Open Access   (Followers: 13)
Autonomous Mental Development, IEEE Transactions on     Hybrid Journal   (Followers: 8)
Bell Labs Technical Journal     Hybrid Journal   (Followers: 28)
Bioelectronics in Medicine     Hybrid Journal  
Biomedical Engineering, IEEE Reviews in     Full-text available via subscription   (Followers: 19)
Biomedical Engineering, IEEE Transactions on     Hybrid Journal   (Followers: 36)
Biomedical Instrumentation & Technology     Hybrid Journal   (Followers: 6)
Broadcasting, IEEE Transactions on     Hybrid Journal   (Followers: 12)
BULLETIN of National Technical University of Ukraine. Series RADIOTECHNIQUE. RADIOAPPARATUS BUILDING     Open Access   (Followers: 1)
Bulletin of the Polish Academy of Sciences : Technical Sciences     Open Access   (Followers: 1)
Canadian Journal of Remote Sensing     Full-text available via subscription   (Followers: 47)
China Communications     Full-text available via subscription   (Followers: 8)
Chinese Journal of Electronics     Hybrid Journal  
Circuits and Systems     Open Access   (Followers: 15)
Consumer Electronics Times     Open Access   (Followers: 5)
Control Systems     Hybrid Journal   (Followers: 266)
Edu Elektrika Journal     Open Access   (Followers: 1)
Electrica     Open Access  
Electronic Design     Partially Free   (Followers: 105)
Electronic Markets     Hybrid Journal   (Followers: 7)
Electronic Materials Letters     Hybrid Journal   (Followers: 4)
Electronics     Open Access   (Followers: 86)
Electronics and Communications in Japan     Hybrid Journal   (Followers: 10)
Electronics For You     Partially Free   (Followers: 92)
Electronics Letters     Hybrid Journal   (Followers: 26)
Elkha : Jurnal Teknik Elektro     Open Access  
Embedded Systems Letters, IEEE     Hybrid Journal   (Followers: 51)
Energy Harvesting and Systems     Hybrid Journal   (Followers: 4)
Energy Storage Materials     Full-text available via subscription   (Followers: 3)
EPJ Quantum Technology     Open Access  
EURASIP Journal on Embedded Systems     Open Access   (Followers: 11)
Facta Universitatis, Series : Electronics and Energetics     Open Access  
Foundations and Trends® in Communications and Information Theory     Full-text available via subscription   (Followers: 6)
Foundations and Trends® in Signal Processing     Full-text available via subscription   (Followers: 10)
Frequenz     Hybrid Journal   (Followers: 1)
Frontiers of Optoelectronics     Hybrid Journal   (Followers: 1)
Geoscience and Remote Sensing, IEEE Transactions on     Hybrid Journal   (Followers: 189)
Haptics, IEEE Transactions on     Hybrid Journal   (Followers: 4)
IACR Transactions on Symmetric Cryptology     Open Access  
IEEE Antennas and Propagation Magazine     Hybrid Journal   (Followers: 97)
IEEE Antennas and Wireless Propagation Letters     Hybrid Journal   (Followers: 77)
IEEE Journal of Emerging and Selected Topics in Power Electronics     Hybrid Journal   (Followers: 46)
IEEE Journal of the Electron Devices Society     Open Access   (Followers: 9)
IEEE Journal on Exploratory Solid-State Computational Devices and Circuits     Hybrid Journal   (Followers: 1)
IEEE Power Electronics Magazine     Full-text available via subscription   (Followers: 66)
IEEE Transactions on Antennas and Propagation     Full-text available via subscription   (Followers: 70)
IEEE Transactions on Automatic Control     Hybrid Journal   (Followers: 56)
IEEE Transactions on Circuits and Systems for Video Technology     Hybrid Journal   (Followers: 19)
IEEE Transactions on Consumer Electronics     Hybrid Journal   (Followers: 40)
IEEE Transactions on Electron Devices     Hybrid Journal   (Followers: 19)
IEEE Transactions on Information Theory     Hybrid Journal   (Followers: 26)
IEEE Transactions on Power Electronics     Hybrid Journal   (Followers: 71)
IEEE Transactions on Signal and Information Processing over Networks     Full-text available via subscription   (Followers: 12)
IEICE - Transactions on Electronics     Full-text available via subscription   (Followers: 12)
IEICE - Transactions on Information and Systems     Full-text available via subscription   (Followers: 5)
IET Cyber-Physical Systems : Theory & Applications     Open Access   (Followers: 1)
IET Microwaves, Antennas & Propagation     Hybrid Journal   (Followers: 35)
IET Nanodielectrics     Open Access  
IET Power Electronics     Hybrid Journal   (Followers: 46)
IET Smart Grid     Open Access  
IET Wireless Sensor Systems     Hybrid Journal   (Followers: 18)
IETE Journal of Education     Open Access   (Followers: 4)
IETE Journal of Research     Open Access   (Followers: 11)
IETE Technical Review     Open Access   (Followers: 13)
IJEIS (Indonesian Journal of Electronics and Instrumentation Systems)     Open Access   (Followers: 3)
Industrial Electronics, IEEE Transactions on     Hybrid Journal   (Followers: 58)
Industry Applications, IEEE Transactions on     Hybrid Journal   (Followers: 24)
Informatik-Spektrum     Hybrid Journal   (Followers: 2)
Instabilities in Silicon Devices     Full-text available via subscription   (Followers: 1)
Intelligent Transportation Systems Magazine, IEEE     Full-text available via subscription   (Followers: 13)
International Journal of Advanced Research in Computer Science and Electronics Engineering     Open Access   (Followers: 18)
International Journal of Advances in Telecommunications, Electrotechnics, Signals and Systems     Open Access   (Followers: 10)
International Journal of Antennas and Propagation     Open Access   (Followers: 11)
International Journal of Applied Electronics in Physics & Robotics     Open Access   (Followers: 5)
International Journal of Computational Vision and Robotics     Hybrid Journal   (Followers: 6)
International Journal of Control     Hybrid Journal   (Followers: 12)
International Journal of Electronics     Hybrid Journal   (Followers: 7)
International Journal of Electronics and Telecommunications     Open Access   (Followers: 13)
International Journal of Granular Computing, Rough Sets and Intelligent Systems     Hybrid Journal   (Followers: 2)
International Journal of High Speed Electronics and Systems     Hybrid Journal  
International Journal of Image, Graphics and Signal Processing     Open Access   (Followers: 14)
International Journal of Microwave and Wireless Technologies     Hybrid Journal   (Followers: 8)
International Journal of Nano Devices, Sensors and Systems     Open Access   (Followers: 12)
International Journal of Nanoscience     Hybrid Journal   (Followers: 1)
International Journal of Numerical Modelling: Electronic Networks, Devices and Fields     Hybrid Journal   (Followers: 4)
International Journal of Power Electronics     Hybrid Journal   (Followers: 24)
International Journal of Review in Electronics & Communication Engineering     Open Access   (Followers: 4)
International Journal of Sensors, Wireless Communications and Control     Hybrid Journal   (Followers: 10)
International Journal of Systems, Control and Communications     Hybrid Journal   (Followers: 4)
International Journal of Wireless and Microwave Technologies     Open Access   (Followers: 6)
International Transaction of Electrical and Computer Engineers System     Open Access   (Followers: 2)
JAREE (Journal on Advanced Research in Electrical Engineering)     Open Access  
Journal of Biosensors & Bioelectronics     Open Access   (Followers: 3)
Journal of Advanced Dielectrics     Open Access   (Followers: 1)
Journal of Artificial Intelligence     Open Access   (Followers: 10)
Journal of Circuits, Systems, and Computers     Hybrid Journal   (Followers: 4)
Journal of Computational Intelligence and Electronic Systems     Full-text available via subscription   (Followers: 1)
Journal of Electrical and Electronics Engineering Research     Open Access   (Followers: 24)
Journal of Electrical Bioimpedance     Open Access   (Followers: 2)
Journal of Electrical Engineering & Electronic Technology     Hybrid Journal   (Followers: 7)
Journal of Electrical, Electronics and Informatics     Open Access  
Journal of Electromagnetic Analysis and Applications     Open Access   (Followers: 7)
Journal of Electromagnetic Waves and Applications     Hybrid Journal   (Followers: 8)
Journal of Electronic Design Technology     Full-text available via subscription   (Followers: 6)
Journal of Electronics (China)     Hybrid Journal   (Followers: 4)
Journal of Energy Storage     Full-text available via subscription   (Followers: 4)
Journal of Engineered Fibers and Fabrics     Open Access  
Journal of Field Robotics     Hybrid Journal   (Followers: 2)
Journal of Guidance, Control, and Dynamics     Hybrid Journal   (Followers: 167)
Journal of Information and Telecommunication     Open Access   (Followers: 1)
Journal of Intelligent Procedures in Electrical Technology     Open Access   (Followers: 3)
Journal of Low Power Electronics     Full-text available via subscription   (Followers: 7)
Journal of Low Power Electronics and Applications     Open Access   (Followers: 9)
Journal of Microelectronics and Electronic Packaging     Hybrid Journal  
Journal of Microwave Power and Electromagnetic Energy     Hybrid Journal  
Journal of Microwaves, Optoelectronics and Electromagnetic Applications     Open Access   (Followers: 10)
Journal of Nuclear Cardiology     Hybrid Journal  
Journal of Optoelectronics Engineering     Open Access   (Followers: 4)
Journal of Physics B: Atomic, Molecular and Optical Physics     Hybrid Journal   (Followers: 28)
Journal of Power Electronics & Power Systems     Full-text available via subscription   (Followers: 11)
Journal of Semiconductors     Full-text available via subscription   (Followers: 5)
Journal of Sensors     Open Access   (Followers: 26)
Journal of Signal and Information Processing     Open Access   (Followers: 9)
Jurnal Rekayasa Elektrika     Open Access  
Jurnal Teknik Elektro     Open Access  
Jurnal Teknologi Elektro     Open Access  
Kinetik : Game Technology, Information System, Computer Network, Computing, Electronics, and Control     Open Access  
Learning Technologies, IEEE Transactions on     Hybrid Journal   (Followers: 12)
Magnetics Letters, IEEE     Hybrid Journal   (Followers: 7)
Majalah Ilmiah Teknologi Elektro : Journal of Electrical Technology     Open Access   (Followers: 2)
Metrology and Measurement Systems     Open Access   (Followers: 5)
Microelectronics and Solid State Electronics     Open Access   (Followers: 18)
Nanotechnology Magazine, IEEE     Full-text available via subscription   (Followers: 33)
Nanotechnology, Science and Applications     Open Access   (Followers: 6)
Nature Electronics     Hybrid Journal  
Networks: an International Journal     Hybrid Journal   (Followers: 5)
Open Electrical & Electronic Engineering Journal     Open Access  
Open Journal of Antennas and Propagation     Open Access   (Followers: 8)
Optical Communications and Networking, IEEE/OSA Journal of     Full-text available via subscription   (Followers: 15)
Paladyn. Journal of Behavioral Robotics     Open Access   (Followers: 1)
Power Electronics and Drives     Open Access   (Followers: 1)
Problemy Peredachi Informatsii     Full-text available via subscription  
Progress in Quantum Electronics     Full-text available via subscription   (Followers: 7)
Pulse     Full-text available via subscription   (Followers: 5)
Radiophysics and Quantum Electronics     Hybrid Journal   (Followers: 2)
Recent Advances in Communications and Networking Technology     Hybrid Journal   (Followers: 3)
Recent Advances in Electrical & Electronic Engineering     Hybrid Journal   (Followers: 9)
Research & Reviews : Journal of Embedded System & Applications     Full-text available via subscription   (Followers: 5)
Security and Communication Networks     Hybrid Journal   (Followers: 2)
Selected Topics in Applied Earth Observations and Remote Sensing, IEEE Journal of     Hybrid Journal   (Followers: 53)
Semiconductors and Semimetals     Full-text available via subscription   (Followers: 1)
Sensing and Imaging : An International Journal     Hybrid Journal   (Followers: 2)
Services Computing, IEEE Transactions on     Hybrid Journal   (Followers: 4)
Software Engineering, IEEE Transactions on     Hybrid Journal   (Followers: 75)
Solid-State Circuits Magazine, IEEE     Hybrid Journal   (Followers: 13)
Solid-State Electronics     Hybrid Journal   (Followers: 9)
Superconductor Science and Technology     Hybrid Journal   (Followers: 2)
Synthesis Lectures on Power Electronics     Full-text available via subscription   (Followers: 3)
Technical Report Electronics and Computer Engineering     Open Access  
TELE     Open Access  
Telematique     Open Access  
TELKOMNIKA (Telecommunication, Computing, Electronics and Control)     Open Access   (Followers: 9)
Universal Journal of Electrical and Electronic Engineering     Open Access   (Followers: 6)
Visión Electrónica : algo más que un estado sólido     Open Access   (Followers: 1)
Wireless and Mobile Technologies     Open Access   (Followers: 6)
Wireless Power Transfer     Full-text available via subscription   (Followers: 4)
Women in Engineering Magazine, IEEE     Full-text available via subscription   (Followers: 11)
Електротехніка і Електромеханіка     Open Access  

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Journal Cover
Journal of Sensors
Journal Prestige (SJR): 0.288
Citation Impact (citeScore): 1
Number of Followers: 26  

  This is an Open Access Journal Open Access journal
ISSN (Print) 1687-725X - ISSN (Online) 1687-7268
Published by Hindawi Homepage  [338 journals]
  • Segmentation of LiDAR Data Using Multilevel Cube Code

    • Abstract: Light detection and ranging (LiDAR) data collected from airborne laser scanning systems are one of the major sources of spatial data. Airborne laser scanning systems have the capacity for rapid and direct acquisition of accurate 3D coordinates. Use of LiDAR data is increasing in various applications, such as topographic mapping, building and city modeling, biomass measurement, and disaster management. Segmentation is a crucial process in the extraction of meaningful information for applications such as 3D object modeling and surface reconstruction. Most LiDAR processing schemes are based on digital image processing and computer vision algorithms. This paper introduces a shape descriptor method for segmenting LiDAR point clouds using a “multilevel cube code” that is an extension of the 2D chain code to 3D space. The cube operator segments point clouds into roof surface patches, including superstructures, removes unnecessary objects, detects the boundaries of buildings, and determines model key points for building modeling. Both real and simulated LiDAR data were used to verify the proposed approach. The experiments demonstrated the feasibility of the method for segmenting LiDAR data from buildings with a wide range of roof types. The method was found to segment point cloud data effectively.
      PubDate: Wed, 17 Apr 2019 13:05:29 +000
  • An Analytical Model for Bandwidth Enhancement of Air-Coupled Unsealed
           Helmholtz Structural CMUTs

    • Abstract: Capacitive micromachined ultrasonic transducers (CMUTs) were reported to own high potential in air-coupled ultrasonic applications such as noncontact nondestructive examination and gas flow measurement. The unsealed CMUTs which utilized the squeeze film effect were reported to overcome the narrow output pressure bandwidth of the conventional sealed CMUTs in air operation. This kind of unsealed CMUTs can also be regarded as Helmholtz resonators. In this work, we present the air-coupled unsealed Helmholtz structural CMUTs which utilize both the squeeze film effect and the Helmholtz resonant effect to enhance the output pressure bandwidth. Based on the mechanism of vibration coupling between membrane and air pistons in membrane holes, we propose an analytical model to aid the design process of this kind of CMUTs. We also use finite element method (FEM) to investigate this kind of CMUTs for our analytical model validation. The FEM results show that the significant bandwidth enhancement can be achieved when the Helmholtz resonant frequency is designed close to the fundamental resonant frequency of the CMUT membrane. Compared with the conventional sealed CMUT cell, the 4-hole unsealed Helmholtz structural CMUT cell improves both the 3-dB fractional bandwidth and SPL-bandwidth product around 35 times. Furthermore, it is found that, with more holes under the same hole area ratio or with a smaller ratio of the cavity height to the viscous boundary layer thickness, the Helmholtz resonant effect becomes weaker and thus the output pressure bandwidth decreases.
      PubDate: Wed, 17 Apr 2019 11:05:17 +000
  • Real-Time Vehicle Detection Algorithm Based on Vision and Lidar Point
           Cloud Fusion

    • Abstract: Vehicle detection is one of the most important environment perception tasks for autonomous vehicles. The traditional vision-based vehicle detection methods are not accurate enough especially for small and occluded targets, while the light detection and ranging- (lidar-) based methods are good in detecting obstacles but they are time-consuming and have a low classification rate for different target types. Focusing on these shortcomings to make the full use of the advantages of the depth information of lidar and the obstacle classification ability of vision, this work proposes a real-time vehicle detection algorithm which fuses vision and lidar point cloud information. Firstly, the obstacles are detected by the grid projection method using the lidar point cloud information. Then, the obstacles are mapped to the image to get several separated regions of interest (ROIs). After that, the ROIs are expanded based on the dynamic threshold and merged to generate the final ROI. Finally, a deep learning method named You Only Look Once (YOLO) is applied on the ROI to detect vehicles. The experimental results on the KITTI dataset demonstrate that the proposed algorithm has high detection accuracy and good real-time performance. Compared with the detection method based only on the YOLO deep learning, the mean average precision (mAP) is increased by 17%.
      PubDate: Wed, 17 Apr 2019 10:05:22 +000
  • NLRP3, IL-1β, and Caspase-1 Gene Transcript Identification and Expression
           by QCM-D in Obese Children

    • Abstract: Background. Obesity in children is highly prevalent in Mexican population. Adipose tissue has been related to specific pro- and anti-inflammatory cytokine and inflammasome gene and protein expression patterns. Actually, there is no existing biosensor for detecting gene expression patterns in children with obesity. The quartz crystal microbalance with dissipation monitoring (QCM-D) has been used as a transducer for DNA biosensor design. Results. In this study, the gene expression pattern of IL-1β, NLRP3, and CASPASE-1 in children with obesity was successfully determined by means of QCM-D. Gene expression patterns were validated with those obtained by quantitative polymerase chain reaction (qPCR), a validated molecular biology technique for gene expression quantification. QCM-D analysis of the detected mass corresponding results for each of the genes showed a major detected mass for IL-1β, followed by similar NLRP3 and constitutive gene 18S deposited mass and a smaller deposited mass for CASPASE-1. Surprisingly, when comparing mRNA gene expression results for NLRP3, IL-1β, and CASPASE-1 obtained with qPCR and QCM-D, similar patterns were found, revealing greatest expression of IL-1β, followed by NLRP3, with CASPASE-1 being the molecule of least expression in the group of children with obesity. AFM images illustrate the step-by-step changes that took place on the quartz surface. Conclusions. QCM-D proved successfully for determining the gene transcripts and expression of NLRP3, IL-1β, and CASPASE-1 in children with obesity, with similar results validated by qPCR. “QCM-D decreases detection costs compared with a validated molecular biology technique.” The QCM-D biosensor developed by our group was successful for gene expression determination; in the future, it can be used for molecular diagnosis.
      PubDate: Wed, 17 Apr 2019 09:05:23 +000
  • Characteristics of Laser Backscattering Intensity to Detect Frozen and Wet
           Surfaces on Roads

    • Abstract: A frozen or wet road surface is a cause of skidding and accidents, so road surface condition is important information for driving safety. Some instruments and methods have been developed to investigate road surface conditions based on optical imagery, although an active sensor is needed, regardless of the time of day. Recently, the laser scanner, which acquires backscattering intensity data related to reflectivity, has become popular in various fields. There is a need to investigate road surface conditions (frozen, wet, or dry) using laser backscattering intensity. This study tries to analyze signal characteristics of laser backscattering intensity to detect frozen and wet surfaces on roads. An ice target with a 7 cm thickness was placed on a road surface, and a wet surface was made due to the melting ice. The ice target, wet surface, dry surface, and roadside vegetation were scanned using a laser scanner. As a result, backscattering signals from the top surface of the ice target were missing due to its smoothness. Dry and wet asphalt surfaces showed distinguishable intensity ranges in their signals. The thick sidewall of the ice target and vegetation at the roadside showed overlapping intensity ranges. An ice sheet is only a few millimeters thick on a real road surface, and the roadside vegetation might be easily distinguished by using texture or auxiliary data. Therefore, laser backscattering intensity can be used to detect frozen, wet, and dry road surfaces, regardless of the time of day. The laser scanner can be installed to acquire information about road surface conditions from observation stations and vehicles in an application for transportation.
      PubDate: Wed, 17 Apr 2019 08:05:32 +000
  • Analysis of Parameter Correlations of the ECOM Solar Radiation Pressure
           Model for GPS Orbit

    • Abstract: The modeling of solar radiation pressure is the most important issue in precision GNSS orbit determination and is usually represented by constant and periodic terms in three orthogonal axes. Unfortunately, these parameters are generally correlated with each other due to overparameterization, and furthermore, the correlation does not remain constant throughout a long-term period. A total of 500 weeks of GPS daily solutions were estimated with the empirical CODE orbit model (ECOM) to cover various block types of satellites. The statistics of the postfit residuals were analyzed in this study, which shows the dominant annual variation of the correlations over time. There is no significant difference between eclipsing and noneclipsing satellites, and the frequency of the correlation exactly corresponds to the GPS draconitic year. Based on the residual analysis, the ECOM is the most appropriate for the Block IIR/IIR-M satellites but does not properly account for the behavior of either older Block IIA or newer IIF satellites. In addition, the daily mean residuals show a different pattern for satellite orbital planes. Therefore, the orbit model should be customized for the block types and orbital plane for better representation of multi-GNSS orbits.
      PubDate: Tue, 16 Apr 2019 14:05:31 +000
  • Experimental Study on the Application of BOTDA in the Overlying Strata
           Deformation Monitoring Induced by Coal Mining

    • Abstract: The coal mine working face overlying strata is often disturbed by multiple mining, leading to adverse effects on the working face’s safe production and ground surface movement. In the three-dimensional physical model test with the size of , after the overburden gets stable when the first working face had been extracted, by using three vertical distributed optical fibers based on the BOTDA principle, the deformation law of the overburden caused by the contiguous coal face mining is studied. Results show that, before the working face advanced to 840 mm (near the fiber), the stress law of the overburden was as follows: the middle of the model was under pressure state and the remaining part was under tension state, and the key stratum produced stress concentration phenomena caused by the secondary mining; when the face advanced to 840 mm (through the fiber), the frequency shift curve of the key stratum and the strata on it combined, and the stress concentration in the key stratum disappeared, indicating that the bearing structure of the key stratum gets unstable; compared with the previous monitoring data, when the working face far away from the fiber, the information reflected by the frequency shift data gradually gets single when the working face is far away from the fiber compared with the previous measurement data. The overburden deformation increased dramatically after the key stratum gets unstable. The surrounding rock and fiber will detach when the stratum goes though large deformation such as abscission layer, fracture, and collapse, and the frequency shift monitored by BOTDA cannot characterize the rock deformation in this situation. The experimental method and the results of this paper serve as useful reference for the application of BOTDA technology in geotechnical engineering.
      PubDate: Tue, 16 Apr 2019 08:05:28 +000
  • Sensing and Data-Driven Control for Smart Building and Smart City Systems

    • PubDate: Sun, 14 Apr 2019 11:05:10 +000
  • Automated Coregistration of Multisensor Orthophotos Generated from
           Unmanned Aerial Vehicle Platforms

    • Abstract: Image coregistration is a key preprocessing step to ensure the effective application of very-high-resolution (VHR) orthophotos generated from multisensor images acquired from unmanned aerial vehicle (UAV) platforms. The most accurate method to align an orthophoto is the installation of air-photo targets at a test site prior to flight image acquisition, and these targets were used as ground control points (GCPs) for georeferencing and georectification. However, there are time and cost limitations related to installing the targets and conducting field surveys on the targets during every flight. To address this problem, this paper presents an automated coregistration approach for orthophotos generated from VHR images acquired from multisensors mounted on UAV platforms. Spatial information from the orthophotos, provided by the global navigation satellite system (GNSS) at each image’s acquisition time, is used as ancillary information for phase correlation-based coregistration. A transformation function between the multisensor orthophotos is then estimated based on conjugate points (CPs), which are locally extracted over orthophotos using the phase correlation approach. Two multisensor datasets are constructed to evaluate the proposed approach. These visual and quantitative evaluations confirm the superiority of the proposed method.
      PubDate: Sun, 14 Apr 2019 09:05:22 +000
  • Delay-Free Tracking Differentiator Design Based on Variational Mode
           Decomposition: Application on MEMS Gyroscope Denoising

    • Abstract: This paper presents a delay-free tracking differentiator based on variational mode decomposition (VMD) for extracting the useful signal from a noisy measurement of gyroscope. Sigmoid function-based tracking differentiator (STD) is a novel tracking differentiator with the advantages of noise-attenuation ability and dynamical performance. However, there is a contradiction in STD; i.e., selecting a larger acceleration factor may cause faster convergence but bad random noise reduction whereas selecting a smaller acceleration factor may lead to signal delay but effective random noise reduction. Here, multiscale transformation is introduced to overcome the contradiction of STD. VMD is selected to decompose the noisy signal into multiscale components, and the correlation coefficients between each component and original signal are calculated, then the component with biggest correlation coefficient is reserved and other components are filtered by the proposed adaptive STD algorithm based on the correlation coefficient of each component, and finally the denoising result is obtained after reconstruction. The prominent advantages of the proposed algorithm are as follows: (i) compared to traditional tracking differentiators, better noise suppression ability can be achieved with suppression of time delay; (ii) compared to other widely used denoising methods, a simpler structure but better denoising ability can be obtained.
      PubDate: Sun, 14 Apr 2019 09:05:19 +000
  • Designing a High-Precision AC Current Source to Measure the nm-Scale
           Displacements in Mechanical Systems

    • Abstract: Measuring the dynamics of a continuously moving target, at the nanoscale level, such as of a bearing raceway or any other vibrating element, requires a contactless measurement. A mission that can be easily carried out by a capacitive probe. The current flowing through the sensor has to remain constant regardless of the changes in the sensors’ output impedance. In this manner, the voltage across the probe is proportional to the distance between the probe and the target. However, the high impedance of the probe cannot be disregarded in comparison to the output impedance of the Howland source. To overcome this problem, we designed a voltage-controlled AC current source (VCCS). The new design consists of implementing two nested loops and uses two cascaded controllers, a fast but imprecise internal control loop tuned by a slow but precise outer control loop in order to obtain a high-precision AC output current. The performance of this device has been compared with the improved quad op-amp current source (IQOA). The results obtained during the numerical validation confirm the relevance of this device.
      PubDate: Thu, 11 Apr 2019 12:05:37 +000
  • Estimating Occupancy from Measurements and Knowledge Using the Bayesian
           Network for Energy Management

    • Abstract: A general approach is proposed to determine occupant behavior (occupancy and activity) in offices and residential buildings in order to use these estimates for improved energy management. Occupant behavior is modelled with a Bayesian network in an unsupervised manner. This algorithm makes use of domain knowledge gathered via questionnaires and recorded sensor data for motion detection, power, and hot water consumption as well as indoor CO2 concentration. Different case studies have been investigated with diversity according to their context (available sensors, occupancy or activity feedback, complexity of the environment, etc.). Furthermore, experiments integrating occupancy estimation and hot water production control show that energy efficiency can be increased by roughly 5% over known optimal control techniques and more than 25% over rule-based control while maintaining the same occupant comfort.
      PubDate: Wed, 10 Apr 2019 07:05:24 +000
  • Topological Characteristics and Vulnerability Analysis of Rural Traffic

    • Abstract: Rural traffic network (RTN), as a complex network, plays a significant role in the field of resisting natural disasters and emergencies. In this paper, we analyze the vulnerability of RTN via three traffic network models (i.e., No-power Traffic Network Model (NTNM), Distance Weight Traffic Network Model (DWTNM), and Road Level Weight Traffic Network Model (RLWTNM)). Firstly, based on the complex network theory, RTN is constructed by using road mapping method, according to the topological features. Secondly, Random Attack (RA) and Deliberate Attack (DA) strategies are used to analyze network vulnerability in three rural traffic network models. By analyzing the attack tolerance of RTN under the condition of different attack patterns, we find that the road level weight traffic network has a good performance to represent the vulnerability of RTN.
      PubDate: Tue, 09 Apr 2019 10:05:21 +000
  • Monitoring the Thaw Slump-Derived Thermokarst in the Qinghai-Tibet Plateau
           Using Satellite SAR Interferometry

    • Abstract: Thaw slumps are well-developed within a 10 km wide zone along the Qinghai-Tibet engineering corridor, especially along the Qinghai-Tibet highway and railway. Previous studies have focused on thaw slump instability such as its origin development, headwall retrogression rate, failure scale, and thermal regime, yet the intrinsic dynamic process of surface movement is relatively less known. In this study, we used InSAR based on the L-band ALOS PALSAR images acquired from January 2007 to October 2010 to investigate the distribution of thaw-induced slope failures containing retrogressive thaw slumps and active layer detachment failures along the Qinghai-Tibet highway (QTH). Our InSAR analysis reveals that the maximum annual average sedimentation rates are even up to -35 mm·yr−1 in the slope direction to the K3035 thaw slump, and the K3035W active layer detachment failure developed on the west side of K3035. The distribution, failure extent, and stability of the slope failures obtained by our InSAR analysis all agree well with the field investigations. Our study illustrates that InSAR is an effective tool for studying the distribution and processes of the thaw slump-derived thermokarst and provides useful references for evaluating permafrost degradation in response to climate warming and external disturbance on the Qinghai-Tibet plateau.
      PubDate: Mon, 08 Apr 2019 13:30:13 +000
  • Detection of Apple Lesions in Orchards Based on Deep Learning Methods of
           CycleGAN and YOLOV3-Dense

    • Abstract: Plant disease is one of the primary causes of crop yield reduction. With the development of computer vision and deep learning technology, autonomous detection of plant surface lesion images collected by optical sensors has become an important research direction for timely crop disease diagnosis. In this paper, an anthracnose lesion detection method based on deep learning is proposed. Firstly, for the problem of insufficient image data caused by the random occurrence of apple diseases, in addition to traditional image augmentation techniques, Cycle-Consistent Adversarial Network (CycleGAN) deep learning model is used in this paper to accomplish data augmentation. These methods effectively enrich the diversity of training data and provide a solid foundation for training the detection model. In this paper, on the basis of image data augmentation, densely connected neural network (DenseNet) is utilized to optimize feature layers of the YOLO-V3 model which have lower resolution. DenseNet greatly improves the utilization of features in the neural network and enhances the detection result of the YOLO-V3 model. It is verified in experiments that the improved model exceeds Faster R-CNN with VGG16 NET, the original YOLO-V3 model, and other three state-of-the-art networks in detection performance, and it can realize real-time detection. The proposed method can be well applied to the detection of anthracnose lesions on apple surfaces in orchards.
      PubDate: Mon, 08 Apr 2019 12:05:16 +000
  • Demonstration of Time-Series InSAR Processing in Beijing Using a Small
           Stack of Gaofen-3 Differential Interferograms

    • Abstract: More and more synthetic aperture radar (SAR) satellites in orbit provide abundant data for remote sensing applications. In August 2016, China launched a new Earth observation SAR satellite, Gaofen-3 (GF-3). In this paper, we utilize a small stack of GF-3 differential interferograms to map land subsidence in Beijing (China) using the time-series SAR interferometry (InSAR) technique. The small stack of differential interferograms is generated with 5 GF-3 SAR images from March 2017 to January 2018. Orbit errors are carefully addressed and removed during differential InSAR (DInSAR) processing. Truncated singular-value decomposition (TSVD) is applied to strengthen the robustness of deformation rate estimation. To validate the results of GF-3 data, an additional deformation measurement using 26 Sentinel-1B images from March 2017 to February 2018 is carried out using the persistent scatterer interferometry (PSI) technique. By implementing a cross-comparison, we find that the retrieved results from GF-3 images and Sentinel-1 images are spatially consistent. The standard deviation of vertical deformation rate differences between two data stacks is 11.24 mm/y in the study area. The results shown in this paper demonstrate the reasonable potential of GF-3 SAR images to monitor land subsidence.
      PubDate: Mon, 08 Apr 2019 12:05:14 +000
  • Influence of Encryption Algorithms on Power Consumption in Energy
           Harvesting Systems

    • Abstract: Autonomous energy harvesting sensors present one of the most attractive areas of microelectronics at the moment. They are a part of Internet of Things (IoT) systems so the data need to be protected across transmission. One way for data protection is encryption and the other way is digital signature. However, energy consumption of those systems is increased using protections algorithms, and it should be considered because these are energy harvesting systems. The paper describes the ways in which data encryption and digital signature algorithms can be implemented in resource limited systems based on an 8-bit microcontroller. Alongside the implementation method, the paper deals with the energy demands of the selected encryption algorithms and digital signatures. The execution time, energy consumption, and memory consumption will be considered.
      PubDate: Mon, 08 Apr 2019 08:05:33 +000
  • Nondestructive Quantification of the Ripening Process in Banana (Musa AAB
           Simmonds) Using Multispectral Imaging

    • Abstract: The ripening process in bananas causes the waste of a significant part of the production of this fruit. The aim of this research is to find a new technique useful for identifying, registering, and quantifying the ripening process of a banana (Musa AAB Simmonds) at the seventh stage of the growing process. This quantification is proposed with a nondestructive technique based on processing multispectral images. This experiment used a set of multispectral imagery registered in a range of 270-1000 nm (from UV to IR) with the aid of a monochromatic camera and a set of 10 optical filters. Multispectral images were analyzed with three different techniques: Fourier fractal analysis, Hotelling transform, and homogeneity texture analysis based on cooccurrence matrix. First, a characteristic index was computed for each technique for a daily set of multispectral imagery. These indexes are slope index, for Fourier fractals; the average of the computed eigenvalues, with Hotelling transform; and the texture homogeneity value. These indexes were evaluated using the behavior of the resulting graphs for a seven-day period, being preferred those graphs with a tendency of decreasing values. Finally, the repeatability of each technique was evaluated by reproducing similar values for each day during the evaluation period. These three methods will be compared in this article in order to select the one with the best performance for measuring the ripening process in bananas. The obtained results show that it is possible to effectively isolate the brown spots from the banana peel with the Hotelling transform by using only 2 optical filters: visible (410-690 nm) and Near-IR (820-910 nm). With the resulting spectral image fusion it was possible to effectively describe the evolution of the brown spots present in the ripening process through the texture homogeneity criteria.
      PubDate: Sun, 07 Apr 2019 14:15:04 +000
  • Corrigendum to “Application of Fractional Differential Calculation in
           Pretreatment of Saline Soil Hyperspectral Reflectance Data”

    • PubDate: Sun, 07 Apr 2019 09:05:32 +000
  • Miniature All-Silica Microbubble-Based Fiber Optic Fabry-Perot Pressure
           Sensor with Pressure Leading-In Tube

    • Abstract: A novel all-silica fiber optic Fabry-Perot (FP) pressure sensor with pressure leading-in tube based on microbubble structure is developed and experimentally demonstrated. The FP cavity is formed by fixing the end face of the single-mode fiber (SMF) parallel to the outer surface of the microbubble, in which the microbubble with a diameter of about 318 μm is constructed at the end of silica hollow tube. When external pressure is transmitted on the inner surface of the microbubble by the pressure leading-in tube, the FP cavity length changes with the diameter of microbubble. Experimental results show that such a sensor has a linear sensitivity of approximately 4.84 nm/MPa at room temperature over the pressure range of 1.1 MPa; the sensor has a very low temperature coefficient of approximately 2 pm/°C from room temperature to 600°C. The sensor has advantages of extremely low temperature coefficient, compact structure, and small size, which has potential applications for measuring pressure in high-temperature environment.
      PubDate: Wed, 03 Apr 2019 10:05:27 +000
  • Investigation of Applicability of an Embedded EM Sensor to Measure the
           Tension of a PSC Girder

    • Abstract: This study investigates the applicability of an embedded EM sensor using a series of experimental studies. To verify the embedded EM sensor, the magnetic hysteresis of various types of PS tendons is measured. After that, the embedded EM sensor is embedded into the concrete and the possibility of obtaining measurements is verified. Finally, the downscaled PSC girder specimen having a sheath with a different curvature is fabricated and the influence of the sheath curvature is investigated. The magnetic hysteresis was changed constantly even though the type of PS tendon was changed, and the embedded EM sensor can measure the magnetic hysteresis, even in the concrete and curved sheath. The area of magnetic hysteresis was decreased according to the increase in the tension force, but the actual values were different according to the number and cross-sectional area of tendons and the initial state of sensors. To compensate for the measured data, the tensile force was converted to the tensile stress and the area ratio was used to compensate for the initial value of the EM sensor. According to the test results, the embedded EM sensor could be applied to the actual PS girder and it can measure the actual tension, which includes the friction loss.
      PubDate: Sun, 31 Mar 2019 12:05:32 +000
  • ECG-Based Subject Identification Using Common Spatial Pattern and SVM

    • Abstract: In this paper, a nonfiducial electrocardiogram (ECG, the process of recording the electrical activity of the heart over a period of time using electrodes placed on the skin) identification system based on the common spatial pattern (CSP) feature extraction technique is presented. The single- and multilead ECG signals of each subject are divided into nonoverlapping segments, and different segment lengths (1, 3, 5, 7, 10, or 15 seconds) are investigated. Features are extracted from each signal segment through projection on a CSP projection matrix. The extracted features are then used to train a radial basis function kernel-based Support Vector Machine (SVM) classifier, which is then employed in the identification phase. The proposed identification system was evaluated on 10, 20, …, 200 reference subjects of the Physikalisch-Technische Bundesanstalt (PTB) ECG database. Using a single limb-based lead (I) with 200 reference subjects, the system achieved an identification rate of 95.15% and equal error rate of 0.1. The use of a single chest-based lead (V3) for 200 reference subjects resulted in an identification rate of 98.92% and equal error rate of 0.08.
      PubDate: Sun, 31 Mar 2019 10:05:40 +000
  • Modeling of Label-Free Optical Waveguide Biosensors with Surfaces Covered
           Partially by Vertically Homogeneous and Inhomogeneous Films

    • Abstract: Optical Waveguide Lightmode Spectroscopy (OWLS) is widely applied to monitor protein adsorption, polymer self-assembly, and living cells on the surface of the sensor in a label-free manner. Typically, to determine the optogeometrical parameters of the analyte layer (adlayer), the homogeneous and isotropic thin adlayer model is used to analyze the recorded OWLS data. However, in most practical situations, the analyte layer is neither homogeneous nor isotropic. Therefore, the measurement with two waveguide modes and the applied model cannot supply enough information about the parameters of the possible adlayer inhomogeneity and anisotropy. Only the so-called quasihomogeneous adlayer refractive index, layer thickness, and surface mass can be determined. In the present work, we construct an inhomogeneous adlayer model. In our model, the adlayer covers the waveguide surface only partially and it has a given refractive index profile perpendicular to the surface of the sensor. Using analytical and numerical model calculations, the step-index and exponential refractive index profiles are investigated with varying surface coverages from 0 to 100%. The relevant equations are summarized and three typically employed waveguide sensor structures are studied in detail. We predict the errors in the calculated optogeometrical parameters of the adlayer by simulating the OWLS measurement on an assumed inhomogeneous adlayer. We found that the surface coverage has negligible influence on the calculated refractive index below film thicknesses of 5 nm; the calculated refractive index is close to the refractive index of the adlayer islands. But the determined quasihomogeneous adlayer refractive index and surface mass are always underrated; the calculated quasihomogeneous thickness is heavily influenced by the surface coverage. Depending on the refractive index profile, waveguide geometry, and surface coverage, the thickness obtained from the homogeneous and isotropic modeling can even take negative and largely overestimated values, too. Therefore, experimentally obtained unrealistic adlayer values, which were dismissed previously, might be important indicators of layer structure.
      PubDate: Sun, 31 Mar 2019 10:05:38 +000
  • Deep Learning-Based GNSS Network-Based Real-Time Kinematic Improvement for
           Autonomous Ground Vehicle Navigation

    • Abstract: Much navigation over the last several decades has been aided by the global navigation satellite system (GNSS). In addition, with the advent of the multi-GNSS era, more and more satellites are available for navigation purposes. However, the navigation is generally carried out by point positioning based on the pseudoranges. The real-time kinematic (RTK) and the advanced technology, namely, the network RTK (NRTK), were introduced for better positioning and navigation. Further improved navigation was also investigated by combining other sensors such as the inertial measurement unit (IMU). On the other hand, a deep learning technique has been recently evolving in many fields, including automatic navigation of the vehicles. This is because deep learning combines various sensors without complicated analytical modeling of each individual sensor. In this study, we structured the multilayer recurrent neural networks (RNN) to improve the accuracy and the stability of the GNSS absolute solutions for the autonomous vehicle navigation. Specifically, the long short-term memory (LSTM) is an especially useful algorithm for time series data such as navigation with moderate speed of platforms. From an experiment conducted in a testing area, the LSTM algorithm developed the positioning accuracy by about 40% compared to GNSS-only navigation without any external bias information. Once the bias is taken care of, the accuracy will significantly be improved up to 8 times better than the GNSS absolute positioning results. The bias terms of the solution need to be estimated within the model by optimizing the layers as well as the nodes each layer, which should be done in further research.
      PubDate: Sun, 31 Mar 2019 00:06:07 +000
  • A Novel Sensor for Noninvasive Detection of In Situ Stem Water Content
           Based on Standing Wave Ratio

    • Abstract: Stem water content (StWC = volume of water : volume of stem) is an important physiological parameter for vascular plants. And a better understanding of StWC contributes to solving some research hotspots in forestry, such as drought resistance, cold resistance, precise irrigation, and health assessment. However, there are few noninvasive, in situ, real-time, safe, and low-cost methods for detecting StWC of woody plants. This article presents a novel sensor for noninvasive detection of in situ StWC based on standing wave ratio. Moreover, extensive experiments were conducted to analyze the performance of this sensor including sensitive distance, measuring range, influence factors, and measuring accuracy. The experimental results show that the sensitive distance of StWC sensor is approximately 53 mm in axial direction and 20 mm in radial direction with the measuring range from 0.01 to 1.00 cm3 cm-3. The combined effects of stem EC and temperature on sensor output are significant and it is necessary to correct the error caused by the two factors. Compared with the oven-drying method, StWC sensor has higher measuring accuracy than Testo 606-2 which is a sensor for measuring wood water content and its average error is less than 0.01 cm3 cm-3. In addition, StWC sensor performed very well on the crape myrtle with high sensitivity equal to 1022.1 mV (cm3 cm-3)-1 and measuring results also accorded with the diurnal dynamics of stem water content.
      PubDate: Wed, 27 Mar 2019 09:05:40 +000
  • Tree Species Classification by Employing Multiple Features Acquired from
           Integrated Sensors

    • Abstract: Explicit information of tree species composition provides valuable materials for the management of forests and urban greenness. In recent years, scholars have employed multiple features in tree species classification, so as to identify them from different perspectives. Most studies use different features to classify the target tree species in a specific growth environment and evaluate the classification results. However, the data matching problems have not been discussed; besides, the contributions of different features and the performance of different classifiers have not been systematically compared. Remote sensing technology of the integrated sensors helps to realize the purpose with high time efficiency and low cost. Benefiting from an integrated system which simultaneously acquired the hyperspectral images, LiDAR waveform, and point clouds, this study made a systematic research on different features and classifiers in pixel-wised tree species classification. We extracted the crown height model (CHM) from the airborne LiDAR device and multiple features from the hyperspectral images, including Gabor textural features, gray-level co-occurrence matrix (GLCM) textural features, and vegetation indices. Different experimental schemes were tested at two study areas with different numbers and configurations of tree species. The experimental results demonstrated the effectiveness of Gabor textural features in specific tree species classification in both homogeneous and heterogeneous growing environments. The GLCM textural features did not improve the classification accuracy of tree species when being combined with spectral features. The CHM feature made more contributions to discriminating tree species than vegetation indices. Different classifiers exhibited similar performances, and support vector machine (SVM) produced the highest overall accuracy among all the classifiers.
      PubDate: Tue, 26 Mar 2019 08:05:43 +000
  • Parameter Optimization on FNN/PID Compound Controller for a Three-Axis
           Inertially Stabilized Platform for Aerial Remote Sensing Applications

    • Abstract: This paper presents a composite parameter optimization method based on the chaos particle swarm optimization and the back propagation algorithms for a fuzzy neural network/proportion integration differentiation compound controller, which is applied for an aerial inertially stabilized platform for aerial remote sensing applications. Firstly, a compound controller combining both the adaptive fuzzy neural network and traditional PID control methods is developed to deal with the contradiction between the control precision and robustness due to disturbances. Then, on the basis of both the chaos particle swarm optimization and the back propagation compound algorithms, the parameters of the fuzzy neural network/PID compound controller are optimized offline and fine-tuned online, respectively. In this way, the compound controller can achieve good adaptive convergence so as to get high stabilization precision under the multisource dynamic disturbance environment. To verify the method, the simulations are carried out. The results show that the composite parameter optimization method can effectively enhance the convergence of the controller, by which the stabilization precision and disturbance rejection capability of the proposed fuzzy neural network/PID compound controller are improved obviously.
      PubDate: Tue, 26 Mar 2019 07:05:32 +000
  • Performance Evaluation of Free-Space Fibre Optic Detection in a
           Lab-on-Chip for Microorganism

    • Abstract: This paper describes the development of a lab-on-chip (LOC) device that can perform reliable online detection in continuous-flow systems for microorganisms. The objective of this work was to examine the performance of a fibre optic detection system integrated into a LOC device. The microfluidic system was fabricated using dry film resist (DFR), integrated with multimode fibre pigtails in the LOC. Subsequently, the performance of the fibre optic detection was evaluated by its absorbance spectra, detection limit, repeatability and reproducibility, and response time. The analysis was carried out using a constant flow rate for three different types of microorganisms which are Escherichia coli, Saccharomyces cerevisiae, and Aeromonas hydrophila. Under the experimental conditions used in this study, the detection limit of cells/mL for both A. hydrophila and E. coli, while a detection limit of cells/mL for S. cerevisiae cells were measured. The results also revealed that the device showed good repeatability with standard deviations less than 0.2 for A. hydrophila and E. coli, while standard deviations for S. cerevisiae were larger than 1.0. The response times for A. hydrophila, E. coli, and S. cerevisiae were 104 s, 122 s, and 78 s, respectively, although significant errors were recorded for all three species for reproducibility experiment. It was found that the device showed generally good sensitivity, with the highest sensitivity towards S. cerevisiae. These findings suggest that an integrated LOC device, with embedded multimode fibre pigtails, can be a reliable instrument for microorganism detection.
      PubDate: Sun, 24 Mar 2019 08:05:40 +000
  • Health Monitoring of Bolt Looseness in Timber Structures Using PZT-Enabled
           Time-Reversal Method

    • Abstract: A prestressed bolt connection is one of the crucial connection types in timber structures. The daily checking and maintenance of bolt connections have to be carried out in order to avoid the collapse of timber structures due to bolt looseness. Real-time health monitoring of bolt connections can not only reduce the daily maintenance cost of timber structures, but it can also avoid property loss and casualties by giving early warning if the bolt connection is loosened in timber structures. This paper proposes a method of prestress monitoring of bolt joints in timber structures by pasting lead zirconate titanate (PZT) patches on the surface of timber structures, and the time-reversal method is applied to denote the connection status of bolts in timber structures. The prestress loss index of timber structural bolts based on wavelet analysis is designed to quantify the bolt looseness of the timber structure. The experimental timber specimen was fabricated consisting of two timber panels, one bolt, and two PZT patches. One of the PZT patches acted as an actuator to emit the stress waves, and another one acted as a sensor to receive the stress wave propagating through the connection interface. The experimental results showed that the amplitude of the focused signal increases significantly with the increase of the prestress value of the bolts, which verify that the proposed method can be utilized to monitor the looseness of bolts in timber structures. The analysis results of the focused signal is proof that the prestress loss index of timber structural bolts designed based on wavelet analysis can reflect the looseness of timber structural bolts.
      PubDate: Sun, 24 Mar 2019 07:05:32 +000
  • Design and Real-Time Implementation of a 3-Stage CnW Heading System on an
           Ubuntu Linux-Embedded Board

    • Abstract: This paper describes the design and real-time implementation of a proposed algorithm for deriving an accurate heading system by fusing data from various inexpensive sensor devices that is comparable to more expensive maritime navigation systems. The proposed algorithm is a 3-Stage Classification N’ Weighing (CnW) Heading System with forward azimuth (FAz) and extended Kalman filter (EKF). Data from three Global Positioning System devices, an inertial measurement unit, and an electronic compass were fed into the algorithm that can be generally described as Classification N’ Weighing-Stage 1 → forward azimuth → Classification N’ Weighing-Stage 2 → extended Kalman filter → Classification N’ Weighing-Stage 3. The proposed algorithm is shown to be comparably accurate as an expensive marine navigation system, and it has less processing time compared to our previous work. The Qt-anywhere-based system developed on a Linux desktop was successfully downloaded onto an Ubuntu Linux-embedded board for real-time implementation. Important notes related to device naming problems when deploying the system on a Linux-embedded board are also given as reference for those interested to address it.
      PubDate: Sun, 24 Mar 2019 07:05:30 +000
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