{"title":"基于交替迭代和LBFGS算法的ISAR成像非参数平移运动补偿算法","authors":"Yuexin Gao;Min Xue;Hanwen Yu;Jianlai Chen","doi":"10.1109/JSTARS.2025.3560365","DOIUrl":null,"url":null,"abstract":"A translational motion compensation method for a target with nonparametric translation in dechirping system is proposed in this paper. We establish the nonparametric translational motion compensation scheme based on the optimization of an image's sharpness. Since the impacts of the range shifts and phase errors on an image's quality are different, we convert the optimization into an alternating iteration of estimating two vectors. These two kinds of iterations are searching for range shifts and phase errors for each range profile, respectively. The Limited-Memory Broyden-Fletcher-Goldfarb-Shanno (BFGS) algorithm is used to solve the optimization problems with high efficiency. According to the application of the proposed algorithm to the real data, it is valid and could be faster and be of higher performance in comparison with some existing methods.","PeriodicalId":13116,"journal":{"name":"IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing","volume":"18 ","pages":"11623-11633"},"PeriodicalIF":4.7000,"publicationDate":"2025-04-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10964234","citationCount":"0","resultStr":"{\"title\":\"A Nonparametric Translational Motion Compensation Algorithm for ISAR Imaging by Using the Alternating Iteration and LBFGS Algorithm\",\"authors\":\"Yuexin Gao;Min Xue;Hanwen Yu;Jianlai Chen\",\"doi\":\"10.1109/JSTARS.2025.3560365\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"A translational motion compensation method for a target with nonparametric translation in dechirping system is proposed in this paper. We establish the nonparametric translational motion compensation scheme based on the optimization of an image's sharpness. Since the impacts of the range shifts and phase errors on an image's quality are different, we convert the optimization into an alternating iteration of estimating two vectors. These two kinds of iterations are searching for range shifts and phase errors for each range profile, respectively. The Limited-Memory Broyden-Fletcher-Goldfarb-Shanno (BFGS) algorithm is used to solve the optimization problems with high efficiency. According to the application of the proposed algorithm to the real data, it is valid and could be faster and be of higher performance in comparison with some existing methods.\",\"PeriodicalId\":13116,\"journal\":{\"name\":\"IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing\",\"volume\":\"18 \",\"pages\":\"11623-11633\"},\"PeriodicalIF\":4.7000,\"publicationDate\":\"2025-04-14\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10964234\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing\",\"FirstCategoryId\":\"5\",\"ListUrlMain\":\"https://ieeexplore.ieee.org/document/10964234/\",\"RegionNum\":2,\"RegionCategory\":\"地球科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"ENGINEERING, ELECTRICAL & ELECTRONIC\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing","FirstCategoryId":"5","ListUrlMain":"https://ieeexplore.ieee.org/document/10964234/","RegionNum":2,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENGINEERING, ELECTRICAL & ELECTRONIC","Score":null,"Total":0}
A Nonparametric Translational Motion Compensation Algorithm for ISAR Imaging by Using the Alternating Iteration and LBFGS Algorithm
A translational motion compensation method for a target with nonparametric translation in dechirping system is proposed in this paper. We establish the nonparametric translational motion compensation scheme based on the optimization of an image's sharpness. Since the impacts of the range shifts and phase errors on an image's quality are different, we convert the optimization into an alternating iteration of estimating two vectors. These two kinds of iterations are searching for range shifts and phase errors for each range profile, respectively. The Limited-Memory Broyden-Fletcher-Goldfarb-Shanno (BFGS) algorithm is used to solve the optimization problems with high efficiency. According to the application of the proposed algorithm to the real data, it is valid and could be faster and be of higher performance in comparison with some existing methods.
期刊介绍:
The IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing addresses the growing field of applications in Earth observations and remote sensing, and also provides a venue for the rapidly expanding special issues that are being sponsored by the IEEE Geosciences and Remote Sensing Society. The journal draws upon the experience of the highly successful “IEEE Transactions on Geoscience and Remote Sensing” and provide a complementary medium for the wide range of topics in applied earth observations. The ‘Applications’ areas encompasses the societal benefit areas of the Global Earth Observations Systems of Systems (GEOSS) program. Through deliberations over two years, ministers from 50 countries agreed to identify nine areas where Earth observation could positively impact the quality of life and health of their respective countries. Some of these are areas not traditionally addressed in the IEEE context. These include biodiversity, health and climate. Yet it is the skill sets of IEEE members, in areas such as observations, communications, computers, signal processing, standards and ocean engineering, that form the technical underpinnings of GEOSS. Thus, the Journal attracts a broad range of interests that serves both present members in new ways and expands the IEEE visibility into new areas.