Weize Sun, Chuanshan Xu, Yingying Huang, Lei Huang
{"title":"传感器故障时准平稳信号的欠定DOA估计","authors":"Weize Sun, Chuanshan Xu, Yingying Huang, Lei Huang","doi":"10.1109/SAM48682.2020.9104339","DOIUrl":null,"url":null,"abstract":"This paper address the problem of direction-of-arrival (DOA) estimation of quasi-stationary signals based on uniform linear array with malfunctioning sensors. By utilizing the subspace structures of the local second-order statistics of quasi-stationary signals, a Khatri-Rao subspace approach is developed. Our scheme first collects the local covariance matrices of the source signals and then transfers them into a new virtual linear array which can identify at least twice as much DOAs as to the original physical one. It is also shown that the coprime configuration is a special case of the proposed model therefore the same techniques can be applied directly. Simulations are also carried out for the comparison of the proposed algorithm and state-of-the-art approaches.","PeriodicalId":6753,"journal":{"name":"2020 IEEE 11th Sensor Array and Multichannel Signal Processing Workshop (SAM)","volume":"7 1","pages":"1-5"},"PeriodicalIF":0.0000,"publicationDate":"2020-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Underdetermined DOA Estimation of Quasi-Stationary Signals in the Presence of Malfunctioning Sensors\",\"authors\":\"Weize Sun, Chuanshan Xu, Yingying Huang, Lei Huang\",\"doi\":\"10.1109/SAM48682.2020.9104339\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper address the problem of direction-of-arrival (DOA) estimation of quasi-stationary signals based on uniform linear array with malfunctioning sensors. By utilizing the subspace structures of the local second-order statistics of quasi-stationary signals, a Khatri-Rao subspace approach is developed. Our scheme first collects the local covariance matrices of the source signals and then transfers them into a new virtual linear array which can identify at least twice as much DOAs as to the original physical one. It is also shown that the coprime configuration is a special case of the proposed model therefore the same techniques can be applied directly. Simulations are also carried out for the comparison of the proposed algorithm and state-of-the-art approaches.\",\"PeriodicalId\":6753,\"journal\":{\"name\":\"2020 IEEE 11th Sensor Array and Multichannel Signal Processing Workshop (SAM)\",\"volume\":\"7 1\",\"pages\":\"1-5\"},\"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 11th Sensor Array and Multichannel Signal Processing Workshop (SAM)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/SAM48682.2020.9104339\",\"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 11th Sensor Array and Multichannel Signal Processing Workshop (SAM)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SAM48682.2020.9104339","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Underdetermined DOA Estimation of Quasi-Stationary Signals in the Presence of Malfunctioning Sensors
This paper address the problem of direction-of-arrival (DOA) estimation of quasi-stationary signals based on uniform linear array with malfunctioning sensors. By utilizing the subspace structures of the local second-order statistics of quasi-stationary signals, a Khatri-Rao subspace approach is developed. Our scheme first collects the local covariance matrices of the source signals and then transfers them into a new virtual linear array which can identify at least twice as much DOAs as to the original physical one. It is also shown that the coprime configuration is a special case of the proposed model therefore the same techniques can be applied directly. Simulations are also carried out for the comparison of the proposed algorithm and state-of-the-art approaches.