Pub Date : 2022-12-06DOI: 10.1109/JMASS.2022.3227018
Wenjie Shen;Yun Lin;Yang Li;Wen Hong;Yanping Wang
Multiaspect SAR has the capability of providing a high-resolution image due to its long synthetic aperture feature. However, a moving target can generate long and complex signatures in a multiaspect SAR image, which may hamper the applications like image interpretation and target detection. In this article, two methods are proposed to remove the moving target signature in a single-channel multiaspect SAR image. The two methods are all based on logarithm background subtraction. The first one is a fast scheme with a cost of reduced resolution. While the second one focuses on preserving the high resolution, it takes more time than the previous one. The first method utilizes the fact of target signal position changes in subaperture image sequence to obtain the static background. The second method combines the detection results to exclude the moving target signal in each complex-valued subaperture image, then obtaining the high resolution of static background by coherent summation. The methods are validated by synthetic and real airborne SAR data.
{"title":"Moving Targets Artifacts Removal in Multiaspect SAR Imagery Based on Logarithm Background Subtraction","authors":"Wenjie Shen;Yun Lin;Yang Li;Wen Hong;Yanping Wang","doi":"10.1109/JMASS.2022.3227018","DOIUrl":"https://doi.org/10.1109/JMASS.2022.3227018","url":null,"abstract":"Multiaspect SAR has the capability of providing a high-resolution image due to its long synthetic aperture feature. However, a moving target can generate long and complex signatures in a multiaspect SAR image, which may hamper the applications like image interpretation and target detection. In this article, two methods are proposed to remove the moving target signature in a single-channel multiaspect SAR image. The two methods are all based on logarithm background subtraction. The first one is a fast scheme with a cost of reduced resolution. While the second one focuses on preserving the high resolution, it takes more time than the previous one. The first method utilizes the fact of target signal position changes in subaperture image sequence to obtain the static background. The second method combines the detection results to exclude the moving target signal in each complex-valued subaperture image, then obtaining the high resolution of static background by coherent summation. The methods are validated by synthetic and real airborne SAR data.","PeriodicalId":100624,"journal":{"name":"IEEE Journal on Miniaturization for Air and Space Systems","volume":"4 1","pages":"62-69"},"PeriodicalIF":0.0,"publicationDate":"2022-12-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49986621","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}
Pub Date : 2022-11-30DOI: 10.1109/JMASS.2022.3225766
Presents the 2022 author/subject index for this issue of the publication.
给出了本期出版物的2022年作者/主题索引。
{"title":"2022 Index IEEE Journal on Miniaturization for Air and Space Systems Vol. 3","authors":"","doi":"10.1109/JMASS.2022.3225766","DOIUrl":"https://doi.org/10.1109/JMASS.2022.3225766","url":null,"abstract":"Presents the 2022 author/subject index for this issue of the publication.","PeriodicalId":100624,"journal":{"name":"IEEE Journal on Miniaturization for Air and Space Systems","volume":"3 4","pages":"302-311"},"PeriodicalIF":0.0,"publicationDate":"2022-11-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/iel7/8253411/9961123/09966946.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49948498","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-11-23DOI: 10.1109/JMASS.2022.3219013
Presents a listing of the editorial board, board of governors, current staff, committee members, and/or society editors for this issue of the publication.
列出本刊的编辑委员会、理事会、现任工作人员、委员会成员和/或社团编辑。
{"title":"The Journal of Miniaturized Air and Space Systems","authors":"","doi":"10.1109/JMASS.2022.3219013","DOIUrl":"https://doi.org/10.1109/JMASS.2022.3219013","url":null,"abstract":"Presents a listing of the editorial board, board of governors, current staff, committee members, and/or society editors for this issue of the publication.","PeriodicalId":100624,"journal":{"name":"IEEE Journal on Miniaturization for Air and Space Systems","volume":"3 4","pages":"C2-C2"},"PeriodicalIF":0.0,"publicationDate":"2022-11-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/iel7/8253411/9961123/09961126.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49948740","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-11-10DOI: 10.1109/JMASS.2022.3221277
Shang-You Chiu;Katherine A. Kim
For low-Earth orbit nanosatellite development, small volume and high reliability are of primary concern. The electrical power system (EPS) is a critical subsystem that generates, stores, and distributes power within the nanosatellite. An EPS is typically made up of multiple power converters that are designed independently and then connected together. However, if the impedance interactions of the power converters are not properly analyzed, the converters can interact adversely in some conditions, leading to instability. Analyses using the impedance interaction factor and the extra element theorem are applied to the EPS. A design procedure and analysis tool, developed in MATLAB, is presented to ensure a robust EPS without converter interaction stability problems. A CubeSat EPS hardware prototype with four buck converters powered by photovoltaic panels is tested to verify the impedance analysis and stable system operation of the nanosatellite EPS.
{"title":"System Analysis and Design for Multiconverter Electrical Power Systems in Nanosatellites","authors":"Shang-You Chiu;Katherine A. Kim","doi":"10.1109/JMASS.2022.3221277","DOIUrl":"https://doi.org/10.1109/JMASS.2022.3221277","url":null,"abstract":"For low-Earth orbit nanosatellite development, small volume and high reliability are of primary concern. The electrical power system (EPS) is a critical subsystem that generates, stores, and distributes power within the nanosatellite. An EPS is typically made up of multiple power converters that are designed independently and then connected together. However, if the impedance interactions of the power converters are not properly analyzed, the converters can interact adversely in some conditions, leading to instability. Analyses using the impedance interaction factor and the extra element theorem are applied to the EPS. A design procedure and analysis tool, developed in MATLAB, is presented to ensure a robust EPS without converter interaction stability problems. A CubeSat EPS hardware prototype with four buck converters powered by photovoltaic panels is tested to verify the impedance analysis and stable system operation of the nanosatellite EPS.","PeriodicalId":100624,"journal":{"name":"IEEE Journal on Miniaturization for Air and Space Systems","volume":"4 1","pages":"41-53"},"PeriodicalIF":0.0,"publicationDate":"2022-11-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49986623","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}
Pub Date : 2022-11-01DOI: 10.1109/JMASS.2022.3218578
Wenlong Dong;Yuqi Wang;Guang-Cai Sun;Mengdao Xing
The frequency hopping (FH) signal has received much research interest due to its low interception probability. In the FH signal localization, the variation of signal frequency introduces error into localization methods involving phase or frequency information. In order to deal with the problem of positioning measurement estimation for unknown FH signal emitters, this article proposes a synthetic aperture passive positioning method. Baseband modulation of received signals is compensated by the time difference method. Then, the de-chirp method is introduced for carrier frequency estimation. The Doppler frequency of each pulse is compensated by a Doppler frequency compensation matrix, and the cost function related to the emitter position is constructed by 2-D focus results of the received signal at all frequencies. The emitter position is obtained through a gird search. Simulation and experimental data show that the proposed method is superior to several existing positioning methods especially when the signal-to-noise ratio (SNR) is low.
{"title":"Passive Localization for Frequency Hopping Signal Emitter Based on Synthetic Aperture Principle","authors":"Wenlong Dong;Yuqi Wang;Guang-Cai Sun;Mengdao Xing","doi":"10.1109/JMASS.2022.3218578","DOIUrl":"https://doi.org/10.1109/JMASS.2022.3218578","url":null,"abstract":"The frequency hopping (FH) signal has received much research interest due to its low interception probability. In the FH signal localization, the variation of signal frequency introduces error into localization methods involving phase or frequency information. In order to deal with the problem of positioning measurement estimation for unknown FH signal emitters, this article proposes a synthetic aperture passive positioning method. Baseband modulation of received signals is compensated by the time difference method. Then, the de-chirp method is introduced for carrier frequency estimation. The Doppler frequency of each pulse is compensated by a Doppler frequency compensation matrix, and the cost function related to the emitter position is constructed by 2-D focus results of the received signal at all frequencies. The emitter position is obtained through a gird search. Simulation and experimental data show that the proposed method is superior to several existing positioning methods especially when the signal-to-noise ratio (SNR) is low.","PeriodicalId":100624,"journal":{"name":"IEEE Journal on Miniaturization for Air and Space Systems","volume":"4 1","pages":"33-40"},"PeriodicalIF":0.0,"publicationDate":"2022-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49953251","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}
The lidar reflective tomography (LRT) system transmits a laser signal and obtains laser reflection projections of the target, which shows great potential for further long-distance noncooperative target detection. However, the received projections are normally in an incomplete view state. Hence, in this article, an improved algebraic reconstruction technique (ART) utilizing the sparse regularization model and nonlocal means (NLMs) algorithm is introduced and proposed for LRT reconstruction to restore incomplete signals or projections. By using the designed LRT outfield system, the comparative experiments are carried out to validate the effectiveness of the proposed method. By considering different investigation states, the improved NLM-ART sparse method shows great capability for LRT of noncooperative targets in long distance.
{"title":"Lidar Reflective Tomography of the Target Under Incomplete View State","authors":"Rui Guo;Zhihan Jin;Wenbo Zhang;Yihua Hu;Zheyi Jiang;Bo Zang","doi":"10.1109/JMASS.2022.3217310","DOIUrl":"https://doi.org/10.1109/JMASS.2022.3217310","url":null,"abstract":"The lidar reflective tomography (LRT) system transmits a laser signal and obtains laser reflection projections of the target, which shows great potential for further long-distance noncooperative target detection. However, the received projections are normally in an incomplete view state. Hence, in this article, an improved algebraic reconstruction technique (ART) utilizing the sparse regularization model and nonlocal means (NLMs) algorithm is introduced and proposed for LRT reconstruction to restore incomplete signals or projections. By using the designed LRT outfield system, the comparative experiments are carried out to validate the effectiveness of the proposed method. By considering different investigation states, the improved NLM-ART sparse method shows great capability for LRT of noncooperative targets in long distance.","PeriodicalId":100624,"journal":{"name":"IEEE Journal on Miniaturization for Air and Space Systems","volume":"4 1","pages":"25-32"},"PeriodicalIF":0.0,"publicationDate":"2022-10-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49953258","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}
Pub Date : 2022-10-26DOI: 10.1109/JMASS.2022.3217278
Xinran Liu;Luoxiao Yang;Zhongju Wang;Long Wang;Chao Huang;Zijun Zhang;Xiong Luo
Unmanned aerial vehicle (UAV)-based autonomous equipment is increasingly employed by the Internet of Things (IoT) digital infrastructure of wind farms. Counting the number of wind turbines (WTs) of UAV-captured images can significantly improve the effectiveness of UAV inspection and the efficiency of wind farm operation and maintenance. However, existing counting methods generally require expensive object position annotations for instance-level supervision as well as a huge number of images to train models. In this article, we propose a two-stage algorithm that combines vision Transformer (ViT) and ensemble learning models to estimate the number of WTs of UAV-taken images. At the first stage, a ViT-based deep neural network is developed to automatically extract high-level features of input UAV images based on the self-attention mechanism. Next, at the second stage, an ensemble learning model, incorporating the deep forest and hist gradient boosting algorithms, is utilized to estimate the counts based on the extracted features. Experimental results show that the proposed algorithm can significantly improve the accuracy compared with the commonly considered and recently reported benchmarks.
{"title":"UAV-Assisted Wind Turbine Counting With an Image-Level Supervised Deep Learning Approach","authors":"Xinran Liu;Luoxiao Yang;Zhongju Wang;Long Wang;Chao Huang;Zijun Zhang;Xiong Luo","doi":"10.1109/JMASS.2022.3217278","DOIUrl":"https://doi.org/10.1109/JMASS.2022.3217278","url":null,"abstract":"Unmanned aerial vehicle (UAV)-based autonomous equipment is increasingly employed by the Internet of Things (IoT) digital infrastructure of wind farms. Counting the number of wind turbines (WTs) of UAV-captured images can significantly improve the effectiveness of UAV inspection and the efficiency of wind farm operation and maintenance. However, existing counting methods generally require expensive object position annotations for instance-level supervision as well as a huge number of images to train models. In this article, we propose a two-stage algorithm that combines vision Transformer (ViT) and ensemble learning models to estimate the number of WTs of UAV-taken images. At the first stage, a ViT-based deep neural network is developed to automatically extract high-level features of input UAV images based on the self-attention mechanism. Next, at the second stage, an ensemble learning model, incorporating the deep forest and hist gradient boosting algorithms, is utilized to estimate the counts based on the extracted features. Experimental results show that the proposed algorithm can significantly improve the accuracy compared with the commonly considered and recently reported benchmarks.","PeriodicalId":100624,"journal":{"name":"IEEE Journal on Miniaturization for Air and Space Systems","volume":"4 1","pages":"18-24"},"PeriodicalIF":0.0,"publicationDate":"2022-10-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49953257","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}
Pub Date : 2022-10-25DOI: 10.1109/JMASS.2022.3216854
Rong Li;Xianming Xie
A Gaussian particle swarm optimization-based phase unwrapping (PU) technique is presented to recover unwrapped phases reflecting the deformation or height of the observed objects from measured interferograms composed of wrapped phases. First, the Gaussian particle swarm optimization strategy is exploited into PU for measured interferograms, and a robust PU program based on the Gaussian particle filter is constructed by combining a robust phase slope estimation technique demonstrated well previously. Second, an efficient path-following approach is exploited to route the paths of PU to improve the accuracy and efficiency in PU for interferograms. Finally, the performances of the proposed method are fully demonstrated with the experiments of PU for the simulated and measured interferograms, and the advantages of this method in the accuracy of PU for interferograms are also shown, with respect to some other traditional methods and representative methods.
{"title":"A Gaussian Particle Swarm Optimization-Based Phase Unwrapping Algorithm","authors":"Rong Li;Xianming Xie","doi":"10.1109/JMASS.2022.3216854","DOIUrl":"https://doi.org/10.1109/JMASS.2022.3216854","url":null,"abstract":"A Gaussian particle swarm optimization-based phase unwrapping (PU) technique is presented to recover unwrapped phases reflecting the deformation or height of the observed objects from measured interferograms composed of wrapped phases. First, the Gaussian particle swarm optimization strategy is exploited into PU for measured interferograms, and a robust PU program based on the Gaussian particle filter is constructed by combining a robust phase slope estimation technique demonstrated well previously. Second, an efficient path-following approach is exploited to route the paths of PU to improve the accuracy and efficiency in PU for interferograms. Finally, the performances of the proposed method are fully demonstrated with the experiments of PU for the simulated and measured interferograms, and the advantages of this method in the accuracy of PU for interferograms are also shown, with respect to some other traditional methods and representative methods.","PeriodicalId":100624,"journal":{"name":"IEEE Journal on Miniaturization for Air and Space Systems","volume":"4 1","pages":"9-17"},"PeriodicalIF":0.0,"publicationDate":"2022-10-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49953256","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}
Pub Date : 2022-10-25DOI: 10.1109/JMASS.2022.3216815
Genwang Liu;Jie Zhang;Xi Zhang;Yi Zhang;Gui Gao;Junmin Meng;Yongjun Jia;Xiaochen Wang
Synthetic aperture radar (SAR) ship target detection under nonhomogeneous sea conditions is changeable. In this article, according to the characteristics of the target and ocean during SAR imaging, the polarization-time–frequency coherent optimal detector PTFO is constructed, and then the constant false alarm rate method is used to detect ship targets with a stable scattering in SAR images. Four quad-polarimetric RADARSAT-2 data are used to analyze the ship–clutter contrast enhancement capability of PTFO quantitatively, and the appropriate number of time–frequency decompositions is determined to be 3. The proposed method can obtain an FOM of 0.95, which is better than other classical methods to control the detection accuracy and suppress the appearance of false alarm targets.
{"title":"Ship Detection in Nonhomogeneous Sea Clutter Based on Polarization-Time–Frequency Optimal Using Polarimetric SAR","authors":"Genwang Liu;Jie Zhang;Xi Zhang;Yi Zhang;Gui Gao;Junmin Meng;Yongjun Jia;Xiaochen Wang","doi":"10.1109/JMASS.2022.3216815","DOIUrl":"https://doi.org/10.1109/JMASS.2022.3216815","url":null,"abstract":"Synthetic aperture radar (SAR) ship target detection under nonhomogeneous sea conditions is changeable. In this article, according to the characteristics of the target and ocean during SAR imaging, the polarization-time–frequency coherent optimal detector PTFO is constructed, and then the constant false alarm rate method is used to detect ship targets with a stable scattering in SAR images. Four quad-polarimetric RADARSAT-2 data are used to analyze the ship–clutter contrast enhancement capability of PTFO quantitatively, and the appropriate number of time–frequency decompositions is determined to be 3. The proposed method can obtain an FOM of 0.95, which is better than other classical methods to control the detection accuracy and suppress the appearance of false alarm targets.","PeriodicalId":100624,"journal":{"name":"IEEE Journal on Miniaturization for Air and Space Systems","volume":"4 1","pages":"2-8"},"PeriodicalIF":0.0,"publicationDate":"2022-10-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49953255","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}
Pub Date : 2022-10-20DOI: 10.1109/JMASS.2022.3215982
Yuqi Wang;Wenlong Dong;Guang-Cai Sun;Zijing Zhang;Mengdao Xing;Xiaoniu Yang
In passive localization, the received signal may come from multiple signal sources with different modulations. The modulations are usually resolved by high-order spectrum (HOS) processing. However, the processing causes multiple intersignal cross terms, resulting in a degradation of localization performance. To resolve the problem, this article proposes a CLEAN-based synthetic aperture passive positioning algorithm for multiple signal sources. The main idea is to locate the same modulated signal by focusing and then filtering out the located signal. Signals with the same modulation are located through the synthetic aperture passive localization method. Then, the located signals are removed and the remaining signals are recovered through inverse focusing. The multiple signals are focused, extracted, and separated according to the modulation. The effect of cross terms and multiplicative noise in the HOS is dramatically reduced. The simulation experiments show that the proposed algorithm can effectively improve localization accuracy.
{"title":"A CLEAN-Based Synthetic Aperture Passive Localization Algorithm for Multiple Signal Sources","authors":"Yuqi Wang;Wenlong Dong;Guang-Cai Sun;Zijing Zhang;Mengdao Xing;Xiaoniu Yang","doi":"10.1109/JMASS.2022.3215982","DOIUrl":"https://doi.org/10.1109/JMASS.2022.3215982","url":null,"abstract":"In passive localization, the received signal may come from multiple signal sources with different modulations. The modulations are usually resolved by high-order spectrum (HOS) processing. However, the processing causes multiple intersignal cross terms, resulting in a degradation of localization performance. To resolve the problem, this article proposes a CLEAN-based synthetic aperture passive positioning algorithm for multiple signal sources. The main idea is to locate the same modulated signal by focusing and then filtering out the located signal. Signals with the same modulation are located through the synthetic aperture passive localization method. Then, the located signals are removed and the remaining signals are recovered through inverse focusing. The multiple signals are focused, extracted, and separated according to the modulation. The effect of cross terms and multiplicative noise in the HOS is dramatically reduced. The simulation experiments show that the proposed algorithm can effectively improve localization accuracy.","PeriodicalId":100624,"journal":{"name":"IEEE Journal on Miniaturization for Air and Space Systems","volume":"3 4","pages":"294-301"},"PeriodicalIF":0.0,"publicationDate":"2022-10-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49948497","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}
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