{"title":"基于随机矩阵的非高斯噪声条件下大规模MIMO雷达DOD和DOA联合估计方法","authors":"Hong Jiang, Yiwei Lu, Shunyou Yao","doi":"10.1109/ICASSP.2016.7472234","DOIUrl":null,"url":null,"abstract":"Traditional methods of target parameter estimation in MIMO radar are carried out under the assumption that the number of observations is much larger than the number of array elements. However, their estimation performance will decline for the MIMO radar with large arrays and insufficient observations. In this paper, we investigate the situation in bistatic MIMO radar that the product of the numbers of the transmit and receive elements and the number of observations grow at the same rate. We propose a robust method for joint direction-of-departure (DOD) and direction-of-arrival (DOA) estimation in non-Gaussian noise environment. The method uses robust M-estimator to form an estimate of the covariance matrix, and then applies random matrix theory (RMT) and polynomial rooting algorithm to receive accurate DOD and DOA estimates for large scale MIMO radar. The simulation results demonstrate the robustness and improvement in accuracy.","PeriodicalId":165321,"journal":{"name":"2016 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","volume":"33 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-03-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"12","resultStr":"{\"title\":\"Random matrix based method for joint DOD and DOA estimation for large scale MIMO radar in non-Gaussian noise\",\"authors\":\"Hong Jiang, Yiwei Lu, Shunyou Yao\",\"doi\":\"10.1109/ICASSP.2016.7472234\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Traditional methods of target parameter estimation in MIMO radar are carried out under the assumption that the number of observations is much larger than the number of array elements. However, their estimation performance will decline for the MIMO radar with large arrays and insufficient observations. In this paper, we investigate the situation in bistatic MIMO radar that the product of the numbers of the transmit and receive elements and the number of observations grow at the same rate. We propose a robust method for joint direction-of-departure (DOD) and direction-of-arrival (DOA) estimation in non-Gaussian noise environment. The method uses robust M-estimator to form an estimate of the covariance matrix, and then applies random matrix theory (RMT) and polynomial rooting algorithm to receive accurate DOD and DOA estimates for large scale MIMO radar. The simulation results demonstrate the robustness and improvement in accuracy.\",\"PeriodicalId\":165321,\"journal\":{\"name\":\"2016 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)\",\"volume\":\"33 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2016-03-20\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"12\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2016 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICASSP.2016.7472234\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICASSP.2016.7472234","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Random matrix based method for joint DOD and DOA estimation for large scale MIMO radar in non-Gaussian noise
Traditional methods of target parameter estimation in MIMO radar are carried out under the assumption that the number of observations is much larger than the number of array elements. However, their estimation performance will decline for the MIMO radar with large arrays and insufficient observations. In this paper, we investigate the situation in bistatic MIMO radar that the product of the numbers of the transmit and receive elements and the number of observations grow at the same rate. We propose a robust method for joint direction-of-departure (DOD) and direction-of-arrival (DOA) estimation in non-Gaussian noise environment. The method uses robust M-estimator to form an estimate of the covariance matrix, and then applies random matrix theory (RMT) and polynomial rooting algorithm to receive accurate DOD and DOA estimates for large scale MIMO radar. The simulation results demonstrate the robustness and improvement in accuracy.