{"title":"范数正则化方法及其在雷达方位超分辨中的应用","authors":"Zou Jian-wu, Zhu Ming-bo, Li Xiang-ping, Dong Wei","doi":"10.1109/TENCON.2013.6718840","DOIUrl":null,"url":null,"abstract":"The azimuth super resolution is a technique problem which has been explored for years in the field of radar. The L2 norm regularization method was used for the solution, because of the ill-condition encountered in the solution process. L1 norm regularization model was also established for the lack of L2 norm method and the sparse nature of the target signal. In order to improve the computational efficiency, L1 norm regularization model was transformed into semi-definite programming model which was solved by predictor-corrector primal-dual path-following method. The computer simulation for different signal-to-noise ratio(SNR) was made, the preliminary findings shows that both methods can distinguish the point targets, the performance of L1 norm regularization method is better under the same conditions, it has a strong noise adoptive ability, and the resolution is increased by 1.7 times, when SNR is 0dB.","PeriodicalId":425023,"journal":{"name":"2013 IEEE International Conference of IEEE Region 10 (TENCON 2013)","volume":"23 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"8","resultStr":"{\"title\":\"Norm regularization method and its application in radar azimuth super-resolution\",\"authors\":\"Zou Jian-wu, Zhu Ming-bo, Li Xiang-ping, Dong Wei\",\"doi\":\"10.1109/TENCON.2013.6718840\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The azimuth super resolution is a technique problem which has been explored for years in the field of radar. The L2 norm regularization method was used for the solution, because of the ill-condition encountered in the solution process. L1 norm regularization model was also established for the lack of L2 norm method and the sparse nature of the target signal. In order to improve the computational efficiency, L1 norm regularization model was transformed into semi-definite programming model which was solved by predictor-corrector primal-dual path-following method. The computer simulation for different signal-to-noise ratio(SNR) was made, the preliminary findings shows that both methods can distinguish the point targets, the performance of L1 norm regularization method is better under the same conditions, it has a strong noise adoptive ability, and the resolution is increased by 1.7 times, when SNR is 0dB.\",\"PeriodicalId\":425023,\"journal\":{\"name\":\"2013 IEEE International Conference of IEEE Region 10 (TENCON 2013)\",\"volume\":\"23 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2013-10-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"8\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2013 IEEE International Conference of IEEE Region 10 (TENCON 2013)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/TENCON.2013.6718840\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2013 IEEE International Conference of IEEE Region 10 (TENCON 2013)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/TENCON.2013.6718840","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Norm regularization method and its application in radar azimuth super-resolution
The azimuth super resolution is a technique problem which has been explored for years in the field of radar. The L2 norm regularization method was used for the solution, because of the ill-condition encountered in the solution process. L1 norm regularization model was also established for the lack of L2 norm method and the sparse nature of the target signal. In order to improve the computational efficiency, L1 norm regularization model was transformed into semi-definite programming model which was solved by predictor-corrector primal-dual path-following method. The computer simulation for different signal-to-noise ratio(SNR) was made, the preliminary findings shows that both methods can distinguish the point targets, the performance of L1 norm regularization method is better under the same conditions, it has a strong noise adoptive ability, and the resolution is increased by 1.7 times, when SNR is 0dB.