A  B  C  D  E  F  G  H  I  J  K  L  M  N  O  P  Q  R  S  T  U  V  W  X  Y  Z  

  Subjects -> AERONAUTICS AND SPACE FLIGHT (Total: 124 journals)
The end of the list has been reached or no journals were found for your choice.
Similar Journals
Journal Cover
IEEE Journal on Miniaturization for Air and Space Systems
Number of Followers: 4  
 
  Hybrid Journal Hybrid journal (It can contain Open Access articles)
ISSN (Online) 2576-3164
Published by IEEE Homepage  [228 journals]
  • The Journal of Miniaturized Air and Space Systems

    • Free pre-print version: Loading...

      Pages: C2 - C2
      Abstract: null
      PubDate: FRI, 23 FEB 2024 09:16:55 -04
      Issue No: Vol. 5, No. 1 (2024)
       
  • IEEE Journal on Miniaturization for Air and Space Systems Special Issue on
           Network Intelligence for Unmanned Aerial Vehicles

    • Free pre-print version: Loading...

      Pages: 56 - 57
      Abstract: null
      PubDate: FRI, 23 FEB 2024 09:16:55 -04
      Issue No: Vol. 5, No. 1 (2024)
       
  • A Novel Two-Step DInSAR Phase Unwrapping for Large Gradient Mining
           Deformation

    • Free pre-print version: Loading...

      Authors: Yandong Gao;Nanshan Zheng;Shijin Li;Yansuo Zhang;Qiuzhao Zhang;Shubi Zhang;
      Pages: 2 - 8
      Abstract: Phase unwrapping (PhU) of the large gradient deformation in the coal mining subsidence center has always been the main problem in the differential interferometric synthetic aperture radar (DInSAR) data processing. The accuracy of PhU will directly affect the deformation results of the mining subsidence center. To address this issue, in this article, we proposed a two-step PhU method which combines $L^{1}$ -norm and $L^{2}$ -norm. This method can effectively obtain the PhU results of the large gradient deformation in the mining subsidence center. First, the filtered DInSAR interferometric phase is unwrapped using $L^{2}$ -norm, and the first-step unwrapped phase is obtained. Then, the first-step unwrapped phase is rewrapped, which performs conjugate multiplication with the original interferometric phase to obtain the residual phase. Moreover, the residual phase is unwrapped by the $L^{1}$ -norm method to obtain the second-step unwrapped phase. Finally, the final unwrapped phase is obtained by summing the first-step and second-step unwrapping results. Experiments are conducted with simulated and GaoFen-3 SAR data sets. To compare against the representative PhU method, the proposed method can effectively solve the problem of PhU in the large gradient deformation of the mining areas.
      PubDate: MON, 14 AUG 2023 10:03:24 -04
      Issue No: Vol. 5, No. 1 (2023)
       
  • An Improved Chaotic Self-Adapting Monkey Algorithm for Multi-UAV Task
           Assignment

    • Free pre-print version: Loading...

      Authors: Yujuan Cui;
      Pages: 9 - 15
      Abstract: To solve the task assignment problem of heterogeneous multi-unmanned aerial vehicle (UAV) with different loads, an improved monkey swarm algorithm is proposed. First, the complex combat tasks are divided into three types of subtasks, and the multi-UAV task assignment model is established based on the performance of UAVs with specific loads. Second, an improved chaotic self-adapting monkey algorithm (ICSAMA) is proposed by introducing chaos optimization into the monkey swarm algorithm through the adaptive mechanism. The optimization ability of the improved algorithm is verified by the classical benchmark function containing single/multipeaks. Finally, taking the actual heterogeneous multi-UAV task planning problem as an example, ICSAMA is applied to solve it. The simulation results show that ICSAMA has higher convergence accuracy and robustness than the standard monkey swarm algorithm.
      PubDate: THU, 26 OCT 2023 09:20:13 -04
      Issue No: Vol. 5, No. 1 (2023)
       
  • Hardware/Software Co-Design of a Feature-Based Satellite Pose Estimation
           System

    • Free pre-print version: Loading...

      Authors: Yunjie Liu;Anne Bettens;Xiaofeng Wu;
      Pages: 16 - 26
      Abstract: Vision-based pose estimation is fundamental for close proximity satellite operations, especially for on-orbit service missions. While neural network methods for pose estimation are becoming more widespread, traditional computer vision techniques still offer unique benefits in terms of efficiency and reliability. This article presents an algorithm that uses feature point detection and random sample consensus (RANSAC) as a solution for satellite pose estimation. The proposed algorithm requires no initialization, previous pose, or motion state information, which significantly reduces processing time. A comparison was conducted between the proposed algorithm and neural-network-based approaches. It was found that the proposed method only needs minimal training samples and memory to produce high-precision pose estimation, making it appropriate for use on small satellite platforms, such as CubeSats. Moreover, the satellite pose estimation implementation was achieved through hardware/software (HW/SW) co-design, by implementing the feature point detection module on a field-programmable gate array (FPGA). This approach takes full advantage of an FPGA’s pipeline structure and the ability for parallel operation of software and hardware. Consequently, it offers an efficient solution for satellite pose estimation with improved operational efficiency, resource utilization, and low power consumption.
      PubDate: TUE, 31 OCT 2023 09:17:15 -04
      Issue No: Vol. 5, No. 1 (2023)
       
  • Dim and Small Target Detection Method via Gradient Features Guided Local
           Contrast

    • Free pre-print version: Loading...

      Authors: Wei Shi;Mingliang Chen;Junchao Zhang;
      Pages: 27 - 32
      Abstract: Small and dim target detection is a longstanding challenge in computer vision because of conditions, such as target scale variations and strong clutter. This article provides an innovative and efficient algorithm for detecting small targets. By utilizing a novel approach, our algorithm achieves superior performance in the presence of challenging environmental conditions, it suppresses the background and enhances the target via gradient features guided local contrast (GFLC). To begin, we leverage the gradient properties of the image to mitigate the background noise. Subsequently, local contrast features are utilized to accentuate the target area in the original image. The fusion map is then computed by combining the above features. Finally, the targets are efficiently extracted from the fusion map via segmentation. The findings indicate that the algorithm we presented achieves outstanding accuracy in detecting targets in images with intricate backgrounds and low contrast, and it effectively suppresses background noise.
      PubDate: FRI, 03 NOV 2023 09:17:20 -04
      Issue No: Vol. 5, No. 1 (2023)
       
  • Hybrid CNN and Transformer Network for Semantic Segmentation of UAV Remote
           Sensing Images

    • Free pre-print version: Loading...

      Authors: Xuanyu Zhou;Lifan Zhou;Shengrong Gong;Haizhen Zhang;Shan Zhong;Yu Xia;Yizhou Huang;
      Pages: 33 - 41
      Abstract: Semantic segmentation of unmanned aerial vehicle (UAV) remote sensing images is a recent research hotspot, offering technical support for diverse types of UAV remote sensing missions. However, unlike general scene images, UAV remote sensing images present inherent challenges. These challenges include the complexity of backgrounds, substantial variations in target scales, and dense arrangements of small targets, which severely hinder the accuracy of semantic segmentation. To address these issues, we propose a convolutional neural network (CNN) and transformer hybrid network for semantic segmentation of UAV remote sensing images. The proposed network follows an encoder–decoder architecture that merges a transformer-based encoder with a CNN-based decoder. First, we incorporate the Swin transformer as the encoder to address the limitations of CNN in global modeling, mitigating the interference caused by complex background information. Second, to effectively handle the significant changes in target scales, we design the multiscale feature integration module (MFIM) that enhances the multiscale feature representation capability of the network. Finally, the semantic feature fusion module (SFFM) is designed to filter the redundant noise during the feature fusion process, which improves the recognition of small targets and edges. Experimental results demonstrate that the proposed method outperforms other popular methods on the UAVid and Aeroscapes datasets.
      PubDate: WED, 15 NOV 2023 09:17:15 -04
      Issue No: Vol. 5, No. 1 (2023)
       
  • Design Methodology for Single-Feed Circularly Polarized X-Band Antenna
           Arrays for CubeSats Using Multilevel Sequential Rotation

    • Free pre-print version: Loading...

      Authors: Daylon Hester;Seokhee Han;Mark Adams;
      Pages: 42 - 50
      Abstract: This article presents a streamlined design methodology for single-feed circularly polarized antenna arrays for CubeSats. The presented method was created with student-led teams in mind and employs a geometrically simple approach, opting for circular patches and ring-shaped feed networks instead of complex geometries. High- and low-impedance radiating elements are designed, and design restrictions are introduced such that all other geometries may be solved through a set of simple cascading equations. These deliberate choices minimize the number of design parameters and simplify the design process. Circular polarization is achieved through a multilevel implementation of sequentially arranged linearly polarized circular patches fed in a series-parallel fashion by ring-shaped feed lines of constant impedance. This article also demonstrates a $4\times 4$ right-hand circularly polarized (RHCP) CubeSat downlink array antenna designed for operation in the 8025–8400-MHz Earth exploration satellite band which was developed using the proposed methodology. The antenna comprises four sequentially rotated RHCP subarrays, each consisting of four sequentially rotated linearly polarized circular patches. The antenna’s boresight RHCP gain exceeds 16.19 dBic at 8.389 GHz with a simulated 27.9% 3-dB axial ratio bandwidth, a 20° half-power beamwidth, and an aperture efficiency of 53%. The antenna has a sub-2 VSWR bandwidth of 26.6%, and its radiation efficiency ranges from 60% to 82% across the target band. Its compact size of 9 cm $\times $ 9 cm enables it to fit on one face of a 10 cm $\times $ 10 cm CubeSat unit.
      PubDate: FRI, 17 NOV 2023 09:20:12 -04
      Issue No: Vol. 5, No. 1 (2023)
       
  • A 2-D Frequency-Domain Algorithm to Remove GRACE Stripe Noise

    • Free pre-print version: Loading...

      Authors: Yuwei Lan;Taoli Yang;Yong Wang;
      Pages: 51 - 55
      Abstract: The gravity recovery and climate experiment (GRACE) sensors observe changes in the Earth’s mass distribution between water storage compartments, estimating the terrestrial water stage (TWS). Unfortunately, the estimation is affected by noise, characterized by primary north–south-oriented stripes. The noise impact is severe in tropical areas. Existing denoising algorithms remove the stripes, but the noise removal and signal preservation can be further improved. Thus, a new 2-D frequency-domain filtering algorithm is proposed, consisting of notch filter banks and a low-pass filter. Also, the relative sum absolute difference (RSAD) is proposed to evaluate noise removal and signal preservation effectiveness. The proposed algorithm removed stripe noise and preserved signal in simulated noisy GRACE Level-2 data. The denoised results were satisfactory qualitatively and quantitatively assessed by the RSAD. In addition, the proposed algorithm outperforms three existing denoising algorithms in noise removal and signal preservation.
      PubDate: FRI, 17 NOV 2023 09:20:12 -04
      Issue No: Vol. 5, No. 1 (2023)
       
 
JournalTOCs
School of Mathematical and Computer Sciences
Heriot-Watt University
Edinburgh, EH14 4AS, UK
Email: journaltocs@hw.ac.uk
Tel: +00 44 (0)131 4513762
 


Your IP address: 44.220.62.183
 
Home (Search)
API
About JournalTOCs
News (blog, publications)
JournalTOCs on Twitter   JournalTOCs on Facebook

JournalTOCs © 2009-
JournalTOCs
 
 

 A  B  C  D  E  F  G  H  I  J  K  L  M  N  O  P  Q  R  S  T  U  V  W  X  Y  Z  

  Subjects -> AERONAUTICS AND SPACE FLIGHT (Total: 124 journals)
The end of the list has been reached or no journals were found for your choice.
Similar Journals
Similar Journals
HOME > Browse the 73 Subjects covered by JournalTOCs  
SubjectTotal Journals
 
 
JournalTOCs
School of Mathematical and Computer Sciences
Heriot-Watt University
Edinburgh, EH14 4AS, UK
Email: journaltocs@hw.ac.uk
Tel: +00 44 (0)131 4513762
 


Your IP address: 44.220.62.183
 
Home (Search)
API
About JournalTOCs
News (blog, publications)
JournalTOCs on Twitter   JournalTOCs on Facebook

JournalTOCs © 2009-