{"title":"基于逆QRD-RLS的盲自适应波束形成","authors":"H. Hung, Yung-Ming Wei","doi":"10.1109/UT.2004.1405502","DOIUrl":null,"url":null,"abstract":"A novel blind adaptive beamforming algorithm is proposed for underwater communications. It uses the inverse QR decomposition-recursive least squares (IQRD- RLS) approach as an adaptive solution in the architecture of our recently proposed blind adaptive solution in the architecture of our recently proposed blind adaptive beamformer. Since the adaptation gain is evaluated via Givens rotation (QR decomposition), it has higher numerical stability and lower computational complexity than the RLS-based algorithm. As compared to the least mean squares (LMS)-based algorithm, it has faster convergence rate but higher computational complexity. The inherent parallel processing capability makes the systolic array implementation feasible. For performance evaluation, simulation results were obtained for the blind adaptive beamformer algorithms based on LMS, RLS and IQRD-RLS respectively. The merits of the IQRD-RLS beamformer algorithm are verified through the simulation results.","PeriodicalId":437450,"journal":{"name":"Proceedings of the 2004 International Symposium on Underwater Technology (IEEE Cat. No.04EX869)","volume":"8 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2004-04-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"Blind adaptive beamforming based on inverse QRD-RLS\",\"authors\":\"H. Hung, Yung-Ming Wei\",\"doi\":\"10.1109/UT.2004.1405502\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"A novel blind adaptive beamforming algorithm is proposed for underwater communications. It uses the inverse QR decomposition-recursive least squares (IQRD- RLS) approach as an adaptive solution in the architecture of our recently proposed blind adaptive solution in the architecture of our recently proposed blind adaptive beamformer. Since the adaptation gain is evaluated via Givens rotation (QR decomposition), it has higher numerical stability and lower computational complexity than the RLS-based algorithm. As compared to the least mean squares (LMS)-based algorithm, it has faster convergence rate but higher computational complexity. The inherent parallel processing capability makes the systolic array implementation feasible. For performance evaluation, simulation results were obtained for the blind adaptive beamformer algorithms based on LMS, RLS and IQRD-RLS respectively. The merits of the IQRD-RLS beamformer algorithm are verified through the simulation results.\",\"PeriodicalId\":437450,\"journal\":{\"name\":\"Proceedings of the 2004 International Symposium on Underwater Technology (IEEE Cat. No.04EX869)\",\"volume\":\"8 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2004-04-20\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the 2004 International Symposium on Underwater Technology (IEEE Cat. No.04EX869)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/UT.2004.1405502\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 2004 International Symposium on Underwater Technology (IEEE Cat. No.04EX869)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/UT.2004.1405502","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Blind adaptive beamforming based on inverse QRD-RLS
A novel blind adaptive beamforming algorithm is proposed for underwater communications. It uses the inverse QR decomposition-recursive least squares (IQRD- RLS) approach as an adaptive solution in the architecture of our recently proposed blind adaptive solution in the architecture of our recently proposed blind adaptive beamformer. Since the adaptation gain is evaluated via Givens rotation (QR decomposition), it has higher numerical stability and lower computational complexity than the RLS-based algorithm. As compared to the least mean squares (LMS)-based algorithm, it has faster convergence rate but higher computational complexity. The inherent parallel processing capability makes the systolic array implementation feasible. For performance evaluation, simulation results were obtained for the blind adaptive beamformer algorithms based on LMS, RLS and IQRD-RLS respectively. The merits of the IQRD-RLS beamformer algorithm are verified through the simulation results.