{"title":"雷达自适应波束形成算法与架构","authors":"A. Finn, M. F. Griffin","doi":"10.1109/DASC.1990.111285","DOIUrl":null,"url":null,"abstract":"Adaptive beamforming algorithms and architectures for phased array radars are reviewed. In particular, the linearly constrained minimum variance (LCMV) beamformer with a normalized least mean square (LMS) weight update algorithm is examined for airborne surveillance applications. LCMV simulation results for realistic clutter, noise, and array miscalibration models are presented. The LCMV beamformer with a normalized LMS weight update algorithm is shown to offer good, performance with minimum computational complexity.<<ETX>>","PeriodicalId":141205,"journal":{"name":"9th IEEE/AIAA/NASA Conference on Digital Avionics Systems","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1990-10-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Radar adaptive beamforming algorithms and architectures\",\"authors\":\"A. Finn, M. F. Griffin\",\"doi\":\"10.1109/DASC.1990.111285\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Adaptive beamforming algorithms and architectures for phased array radars are reviewed. In particular, the linearly constrained minimum variance (LCMV) beamformer with a normalized least mean square (LMS) weight update algorithm is examined for airborne surveillance applications. LCMV simulation results for realistic clutter, noise, and array miscalibration models are presented. The LCMV beamformer with a normalized LMS weight update algorithm is shown to offer good, performance with minimum computational complexity.<<ETX>>\",\"PeriodicalId\":141205,\"journal\":{\"name\":\"9th IEEE/AIAA/NASA Conference on Digital Avionics Systems\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1990-10-15\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"9th IEEE/AIAA/NASA Conference on Digital Avionics Systems\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/DASC.1990.111285\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"9th IEEE/AIAA/NASA Conference on Digital Avionics Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/DASC.1990.111285","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Radar adaptive beamforming algorithms and architectures
Adaptive beamforming algorithms and architectures for phased array radars are reviewed. In particular, the linearly constrained minimum variance (LCMV) beamformer with a normalized least mean square (LMS) weight update algorithm is examined for airborne surveillance applications. LCMV simulation results for realistic clutter, noise, and array miscalibration models are presented. The LCMV beamformer with a normalized LMS weight update algorithm is shown to offer good, performance with minimum computational complexity.<>
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