{"title":"基于LPA波束形成的多运动源递归跟踪阵列信号处理","authors":"V. Katkovnik, Yong-Hoon Kim","doi":"10.1109/SSP.2001.955340","DOIUrl":null,"url":null,"abstract":"The windowed linear local polynomial approximation (LPA) of the time-varying direction-of-arrival (DOA) is developed for nonparametric high-resolution estimation of multiple moving sources. The method gives the estimates of instantaneous values of the directions as well as their first derivatives. The asymptotic variance and bias of these estimates are derived and used for the optimal window size selection. Marginal beamformers are proposed for estimation and sources visualization. These marginal beamformers are able to localize and track every source individually nulling signals from all other moving sources. Recursive implementation of estimation algorithms are developed for two different tasks: estimation of DOAs with varying number of sources and multiple source tracking in time.","PeriodicalId":70952,"journal":{"name":"信号处理","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2001-08-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Array signal processing for recursive tracking of multiple moving sources based on LPA beamforming\",\"authors\":\"V. Katkovnik, Yong-Hoon Kim\",\"doi\":\"10.1109/SSP.2001.955340\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The windowed linear local polynomial approximation (LPA) of the time-varying direction-of-arrival (DOA) is developed for nonparametric high-resolution estimation of multiple moving sources. The method gives the estimates of instantaneous values of the directions as well as their first derivatives. The asymptotic variance and bias of these estimates are derived and used for the optimal window size selection. Marginal beamformers are proposed for estimation and sources visualization. These marginal beamformers are able to localize and track every source individually nulling signals from all other moving sources. Recursive implementation of estimation algorithms are developed for two different tasks: estimation of DOAs with varying number of sources and multiple source tracking in time.\",\"PeriodicalId\":70952,\"journal\":{\"name\":\"信号处理\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2001-08-06\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"信号处理\",\"FirstCategoryId\":\"1093\",\"ListUrlMain\":\"https://doi.org/10.1109/SSP.2001.955340\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"信号处理","FirstCategoryId":"1093","ListUrlMain":"https://doi.org/10.1109/SSP.2001.955340","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Array signal processing for recursive tracking of multiple moving sources based on LPA beamforming
The windowed linear local polynomial approximation (LPA) of the time-varying direction-of-arrival (DOA) is developed for nonparametric high-resolution estimation of multiple moving sources. The method gives the estimates of instantaneous values of the directions as well as their first derivatives. The asymptotic variance and bias of these estimates are derived and used for the optimal window size selection. Marginal beamformers are proposed for estimation and sources visualization. These marginal beamformers are able to localize and track every source individually nulling signals from all other moving sources. Recursive implementation of estimation algorithms are developed for two different tasks: estimation of DOAs with varying number of sources and multiple source tracking in time.
期刊介绍:
Journal of Signal Processing is an academic journal supervised by China Association for Science and Technology and sponsored by China Institute of Electronics. The journal is an academic journal that reflects the latest research results and technological progress in the field of signal processing and related disciplines. It covers academic papers and review articles on new theories, new ideas, and new technologies in the field of signal processing. The journal aims to provide a platform for academic exchanges for scientific researchers and engineering and technical personnel engaged in basic research and applied research in signal processing, thereby promoting the development of information science and technology. At present, the journal has been included in the three major domestic core journal databases "China Science Citation Database (CSCD), China Science and Technology Core Journals (CSTPCD), Chinese Core Journals Overview" and Coaj. It is also included in many foreign databases such as Scopus, CSA, EBSCO host, INSPEC, JST, etc.