IEEE Journal on Miniaturization for Air and Space Systems最新文献_第7页

Data-Driven Decision Making and Near-Optimal Path Planning for Multiagent System in Games 游戏中多智能体系统的数据驱动决策和近最优路径规划

IEEE Journal on Miniaturization for Air and Space Systems Pub Date : 2023-07-04 DOI: 10.1109/JMASS.2023.3292259

Xindi Wang;Hao Liu;Qing Gao

引用次数: 0

UAV Remote-Sensing Image Semantic Segmentation Strategy Based on Thermal Infrared and Multispectral Image Features 基于热红外和多光谱图像特征的无人机遥感图像语义分割策略

IEEE Journal on Miniaturization for Air and Space Systems Pub Date : 2023-06-19 DOI: 10.1109/JMASS.2023.3286418

Pakezhamu Nuradili;Ji Zhou;Xiangbing Zhou;Jin Ma;Ziwei Wang;Lingxuan Meng;Wenbin Tang;Yizhen Meng

{"title":"UAV Remote-Sensing Image Semantic Segmentation Strategy Based on Thermal Infrared and Multispectral Image Features","authors":"Pakezhamu Nuradili;Ji Zhou;Xiangbing Zhou;Jin Ma;Ziwei Wang;Lingxuan Meng;Wenbin Tang;Yizhen Meng","doi":"10.1109/JMASS.2023.3286418","DOIUrl":"https://doi.org/10.1109/JMASS.2023.3286418","url":null,"abstract":"The availability of high-resolution imagery resources for semantic segmentation research has expanded significantly due to the rapid development of remote-sensing technology utilizing unmanned aerial vehicles (UAVs). These images provide researchers with a more accurate view of the region of interest and allow for more detailed analysis and interpretation of the images. However, semantic segmentation based on UAV remote-sensing imagery still faces new challenges in deriving ground objects. In contrast to the commonly used multispectral (MS) imagery, thermal infrared (TIR) imagery can record the emission of ground objects, making the temperature characteristics of TIR imagery and the color characteristics of MS imagery complementary. These two approaches can be used synergistically to provide more comprehensive image information. On this basis, we propose a strategy for semantic segmentation of UAV images by utilizing both TIR and MS image features. The approach combines principal component analysis (PCA) transformation with a deep learning semantic segmentation network, namely, Deeplv3. The effectiveness of the proposed strategy is evaluated by comparing it with both traditional supervised classification algorithms and deep learning algorithms. According to the results, the proposed strategy exhibits greater robustness, achieving a mean pixel accuracy (MPA) of 92.8% and a mean intersection over union (MIOU) of 73.5%. These results outperform several classical deep learning semantic segmentation algorithms that were also evaluated. The proposed strategy would be beneficial to promote the development of semantic segmentation technology for UAV remote-sensing images.","PeriodicalId":100624,"journal":{"name":"IEEE Journal on Miniaturization for Air and Space Systems","volume":"4 3","pages":"311-319"},"PeriodicalIF":0.0,"publicationDate":"2023-06-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49966668","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

Synthetic Aperture Passive Localization Method Based on Slant Range Orthogonal Expansion 基于斜距正交展开的合成孔径无源定位方法

IEEE Journal on Miniaturization for Air and Space Systems Pub Date : 2023-06-14 DOI: 10.1109/JMASS.2023.3286271

Xinsheng He;Ming Deng;Bingjie Chai;Wenlong Dong;Zhaohui Zhang;Chunmin Wu;Yuqi Wang

引用次数: 0

Development of a Hardware Demonstration Platform for Multispacecraft Reconnaissance of Small Bodies 小体多航天器侦察硬件演示平台的研制

IEEE Journal on Miniaturization for Air and Space Systems Pub Date : 2023-03-29 DOI: 10.1109/JMASS.2023.3279411

Ravi Teja Nallapu;Yinan Xu;Tristan Schuler;Jekan Thangavelautham

{"title":"Development of a Hardware Demonstration Platform for Multispacecraft Reconnaissance of Small Bodies","authors":"Ravi Teja Nallapu;Yinan Xu;Tristan Schuler;Jekan Thangavelautham","doi":"10.1109/JMASS.2023.3279411","DOIUrl":"https://doi.org/10.1109/JMASS.2023.3279411","url":null,"abstract":"The next frontier in space exploration involves visiting some of the 2 million small bodies scattered throughout the solar system. However, these missions are expected to be challenging due to the surface irregularities of these bodies and the very low gravity, which makes steps like getting into orbit very complex. For these reasons, reconnaissance is crucial for small-body exploration before taking on ambitious orbital, surface, and sample-return missions. Our previous work developed IDEAS, an automated design software for small-body reconnaissance mission development using spacecraft swarms. A critical challenge to furthering such designs is the lack of hardware demonstration platforms for interplanetary spacecraft operations. In this article, we present multiagent photogrammetry of small bodies (MAPS), a hardware platform to demonstrate critical reconnaissance operations of multispacecraft missions identified by the IDEAS framework. MAPS uses unmanned air vehicles (UAVs) as the autonomous agents that perform reconnaissance operations. The UAVs use their visual feed to generate a 3-D surface map of a small-body mockup, which is encountered along their flight path. In this article, we examine the various design elements of a small-body surface reconstruction mission inside the MAPS testbed. These elements are used for designing reference trajectories of the participating UAVs, which is enforced using a tracking feedback control law. We then formulate the small-body mapping problem as a mixed-integer nonlinear programming problem, which is handled by the Automated Swarm Designer module of the IDEAS framework. The solutions are implemented inside the MAPS, and shape models generated from the UAV feeds are compared.","PeriodicalId":100624,"journal":{"name":"IEEE Journal on Miniaturization for Air and Space Systems","volume":"4 3","pages":"283-304"},"PeriodicalIF":0.0,"publicationDate":"2023-03-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49966670","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

The Journal of Miniaturized Air and Space Systems 小型化航空航天系统杂志

IEEE Journal on Miniaturization for Air and Space Systems Pub Date : 2023-03-23 DOI: 10.1109/JMASS.2023.3273095

引用次数: 0

An On-Board Imaging Processing Algorithm for Stripmap Mode of Azimuth Multichannel Spaceborne SAR 方位角多通道星载SAR条带图模式的星载成像处理算法

IEEE Journal on Miniaturization for Air and Space Systems Pub Date : 2023-03-22 DOI: 10.1109/JMASS.2023.3278572

Yanbin Liu;Dongxu Chen;Wenjie Xing;Xuan Zhou;Guang-Cai Sun;Jiarong Xiao;Yue Cao;Shuai Jiang;Shuchen Guo;Zhongjun Yu;Mengdao Xing

{"title":"An On-Board Imaging Processing Algorithm for Stripmap Mode of Azimuth Multichannel Spaceborne SAR","authors":"Yanbin Liu;Dongxu Chen;Wenjie Xing;Xuan Zhou;Guang-Cai Sun;Jiarong Xiao;Yue Cao;Shuai Jiang;Shuchen Guo;Zhongjun Yu;Mengdao Xing","doi":"10.1109/JMASS.2023.3278572","DOIUrl":"10.1109/JMASS.2023.3278572","url":null,"abstract":"In the traditional processing methods of azimuth multichannel spaceborne synthetic aperture radar (SAR), the azimuth spectrum reconstruction and subsequent azimuth focusing are always via full-aperture processing. However, if the multichannel full-aperture echo data are stored on the satellite, and then the full-aperture algorithms are used for the on-board imaging processing, the huge amount of echo data will require more on-board storage resources and computing resources, and the imaging processing time will become longer. To solve the above problems, a novel on-board imaging processing algorithm via the idea that the data acquisition and the on-board imaging processing of the subaperture data are carried out simultaneously is proposed in this article. In the algorithm, the azimuth spectrum ambiguity is eliminated by the subaperture azimuth spectrum reconstruction. Then, the range cell migration correction (RCMC) and the range compression for the unambiguous subaperture signals are accomplished by the chirp scaling algorithm (CSA). After that, the low-resolution subaperture images are got via the subaperture focusing. By coherently combining all subaperture images, the final result with high resolution of all echo data can be obtained. Finally, the simulation for the point targets is given to verify the effectiveness of the proposed algorithm.","PeriodicalId":100624,"journal":{"name":"IEEE Journal on Miniaturization for Air and Space Systems","volume":"4 4","pages":"330-335"},"PeriodicalIF":0.0,"publicationDate":"2023-03-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82540240","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Discrete-Time Prescribed Performance Control of an Air-Vehicle’s Seeker Stabilized Platform 飞行器导引头稳定平台的离散时间规定性能控制

IEEE Journal on Miniaturization for Air and Space Systems Pub Date : 2023-03-22 DOI: 10.1109/JMASS.2023.3278569

Xiangwei Bu;Zongcheng Liu

引用次数: 1

Health Observation of the Capital Airport South Expressway Based on Improved MT-InSAR Technology 基于改进MT-InSAR技术的首都机场南高速公路健康观测

IEEE Journal on Miniaturization for Air and Space Systems Pub Date : 2023-03-21 DOI: 10.1109/JMASS.2023.3260098

Xuemin Xing;Li Huang;Zhongming He;Tengfei Zhang;Yikai Zhu

{"title":"Health Observation of the Capital Airport South Expressway Based on Improved MT-InSAR Technology","authors":"Xuemin Xing;Li Huang;Zhongming He;Tengfei Zhang;Yikai Zhu","doi":"10.1109/JMASS.2023.3260098","DOIUrl":"https://doi.org/10.1109/JMASS.2023.3260098","url":null,"abstract":"Objectives: The Airport South Expressway in China is built in a soft soil area, which may induce great hidden danger to airport traffic safety operations. Technology or Method: A new method to improve multitemporal interferometric synthetic aperture radar (MT-InSAR) technology, based on a novel time-series InSAR deformation model and an improved parameter estimation algorithm, is proposed for soft soil expressways monitoring. The functional relationship between the deformation and the creep parameters (viscosity and elastic modulus) based on the Maxwell model in 1-D linear rheology replaces the traditional InSAR linear model, and the creep physical parameters can be solved simultaneously in the solution process. The least squares method with inequality constraints (LSICs) is induced to solve the unknown parameters. In total, 19 TerraSAR-X radar satellite images covering the South Expressway were utilized to validate the proposed method. The creep parameters for each pixel along the expressways and the time-series deformation sequences from January 2012 to July 2014 were obtained. Results: As the results showed, the maximum settlement along the expressway was up to 125 mm, and the accuracy verification results showed that the modeling accuracy was 1.6 mm, with an improvement of 36.0% compared to the traditional linear model; the internal accuracy of the deformation results was ±1.9 mm, accounting for 1.5% of the maximum deformation. Clinical or Biological Impact: Our method can provide data support and a reference for long-term health monitoring and early warning of infrastructure and traffic operation management in poor soil regions.","PeriodicalId":100624,"journal":{"name":"IEEE Journal on Miniaturization for Air and Space Systems","volume":"4 3","pages":"232-241"},"PeriodicalIF":0.0,"publicationDate":"2023-03-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49966951","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

Deep-Learning-Based Mask-Cut Method for InSAR Phase Unwrapping 基于深度学习的掩模切割InSAR相位展开方法

IEEE Journal on Miniaturization for Air and Space Systems Pub Date : 2023-03-16 DOI: 10.1109/JMASS.2023.3258379

Kai Yang;Zhihui Yuan;Xuemin Xing;Lifu Chen

{"title":"Deep-Learning-Based Mask-Cut Method for InSAR Phase Unwrapping","authors":"Kai Yang;Zhihui Yuan;Xuemin Xing;Lifu Chen","doi":"10.1109/JMASS.2023.3258379","DOIUrl":"https://doi.org/10.1109/JMASS.2023.3258379","url":null,"abstract":"Two-dimensional phase unwrapping (2D-PU) is a key processing step for interferometric synthetic aperture radar (InSAR) and it plays an important role in InSAR data processing. For the phase unwrapping (PU) problem, many scholars began to consider using the deep learning (DL) technology in the field of artificial intelligence. By accumulating InSAR PU processing experience through DL, the learning-based PU method can surpass the traditional PU algorithm sometimes. Therefore, this article designs a mask-cuts (MCs) deployment network based on DL, which is named MCNet, and the PU method based on this network is also known as MCNet-PU. First, the residues images and its corresponding MCs images are obtained by using the traditional MC method as the training data and testing data. Second, the relationship between residues and MCs is learned through the training of the self-built MCNet. Then, the trained MCNet is used to obtain the MCs corresponding to the interferogram to be unwrapped. Finally, the unwrapped result is obtained by phase integration using the traditional flood fill method. Compared with the traditional MC method, MCNet does not need to use the quality map to guide the deployment of the MCs, nor does it need to refine the MCs, and it can make the deployment of the MCs more accurate. Experiments on simulated and real InSAR data show that the MCNet-PU method can improve the phase unwrapping success ratio (PUSR) by about 4%–15%, which shows the effectiveness of the method.","PeriodicalId":100624,"journal":{"name":"IEEE Journal on Miniaturization for Air and Space Systems","volume":"4 2","pages":"221-230"},"PeriodicalIF":0.0,"publicationDate":"2023-03-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49964255","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 3

Precision Terrain Modeling Approach in Complex Mountainous Areas Based on Compact UAV Ka-InSAR Data 基于Ka-InSAR数据的复杂山区精确地形建模方法

IEEE Journal on Miniaturization for Air and Space Systems Pub Date : 2023-03-16 DOI: 10.1109/JMASS.2023.3276949

Fei Liu;Shuang Li;Yaoquan Jing;Jia Liu;Han Hu;Quan Gan;Tingting Zhao;Yuling Ding;Xing Pan;Shuo Deng;Qing Zhu

{"title":"Precision Terrain Modeling Approach in Complex Mountainous Areas Based on Compact UAV Ka-InSAR Data","authors":"Fei Liu;Shuang Li;Yaoquan Jing;Jia Liu;Han Hu;Quan Gan;Tingting Zhao;Yuling Ding;Xing Pan;Shuo Deng;Qing Zhu","doi":"10.1109/JMASS.2023.3276949","DOIUrl":"https://doi.org/10.1109/JMASS.2023.3276949","url":null,"abstract":"A high-precision digital elevation model (DEM) is useful for disaster investigation and evaluation in cloudy, rainy, and complex mountainous areas. However, clouds and rain make the optical images and laser point-cloud data acquisition difficult, while noise prohibits obtaining accurate surface information. Additionally, the complex elevation difference in mountainous areas increases the data processing difficulty, such as phase unwrapping (PU) and filtering. To overcome these problems, first, we introduce a new airborne multibaseline Ka-interferometric synthetic aperture radar (InSAR) system developed by the Beijing Institute of Radio Measurement. The system affords high resolution and small volume, is lightweight, has a good top-view angle, and is flexible. Thus, it reduces the flight platform’s dependence and improves the aircraft’s adaptability and universality. Moreover, a multibaseline PU method of a two-stage programming approach (TSPA) is selected to overcome the influence of severe noise and the phase continuity assumption limitation. Additionally, an adaptive filtering method for InSAR point clouds considering coherence and optimal bending energy is proposed. This method’s validity is verified using stereo satellite images, ground observation point precision checks, and geomorphic texture analysis against existing DEM results. The experimental results demonstrate that the proposed scheme has a good filtering effect on noise, vegetation, residential building areas, and bridges, significantly reducing manual intervention. Moreover, the results highlight that our method is well integrated with stereo images and has more texture details than conventional stereo mapping results, with a mean square error of elevation of 1.938 m.","PeriodicalId":100624,"journal":{"name":"IEEE Journal on Miniaturization for Air and Space Systems","volume":"4 3","pages":"257-266"},"PeriodicalIF":0.0,"publicationDate":"2023-03-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49966673","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0