{"title":"基于最小熵和牛顿迭代的MIMO-ISAR成像快速速度估计","authors":"J. Su, Weidong Jiang, B. Tian","doi":"10.1109/ICAICA50127.2020.9181850","DOIUrl":null,"url":null,"abstract":"In the process of ISAR imaging, since the velocity of the non-cooperative target is unknown, imaging may be blur and even unable to focus. Therefore, MIMO-ISAR radar is introduced, and the target velocity estimation is the key and difficulty in the process. Based on the velocity estimation method of minimum entropy that has been proposed, this paper proposes a fast velocity estimation methods based on minimum entropy and Newton iteration to shorten the time and improve the efficiency of velocity estimation. Analysis and simulation results verify the feasibility of the proposed algorithm, which is of vital importance for improving the quality of MIMO-ISAR imaging and motion compensation.","PeriodicalId":113564,"journal":{"name":"2020 IEEE International Conference on Artificial Intelligence and Computer Applications (ICAICA)","volume":"177 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Fast Velocity Estimation Based on Minimum Entropy and Newton Iteration in MIMO-ISAR Imaging\",\"authors\":\"J. Su, Weidong Jiang, B. Tian\",\"doi\":\"10.1109/ICAICA50127.2020.9181850\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In the process of ISAR imaging, since the velocity of the non-cooperative target is unknown, imaging may be blur and even unable to focus. Therefore, MIMO-ISAR radar is introduced, and the target velocity estimation is the key and difficulty in the process. Based on the velocity estimation method of minimum entropy that has been proposed, this paper proposes a fast velocity estimation methods based on minimum entropy and Newton iteration to shorten the time and improve the efficiency of velocity estimation. Analysis and simulation results verify the feasibility of the proposed algorithm, which is of vital importance for improving the quality of MIMO-ISAR imaging and motion compensation.\",\"PeriodicalId\":113564,\"journal\":{\"name\":\"2020 IEEE International Conference on Artificial Intelligence and Computer Applications (ICAICA)\",\"volume\":\"177 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-06-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2020 IEEE International Conference on Artificial Intelligence and Computer Applications (ICAICA)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICAICA50127.2020.9181850\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 IEEE International Conference on Artificial Intelligence and Computer Applications (ICAICA)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICAICA50127.2020.9181850","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Fast Velocity Estimation Based on Minimum Entropy and Newton Iteration in MIMO-ISAR Imaging
In the process of ISAR imaging, since the velocity of the non-cooperative target is unknown, imaging may be blur and even unable to focus. Therefore, MIMO-ISAR radar is introduced, and the target velocity estimation is the key and difficulty in the process. Based on the velocity estimation method of minimum entropy that has been proposed, this paper proposes a fast velocity estimation methods based on minimum entropy and Newton iteration to shorten the time and improve the efficiency of velocity estimation. Analysis and simulation results verify the feasibility of the proposed algorithm, which is of vital importance for improving the quality of MIMO-ISAR imaging and motion compensation.