Qiao Chen, N. Tong, Yibei Dong, Lei Bao, Shuai Chen, Lixun Han
{"title":"多测量向量稀疏度自适应算法实现了MIMO稀疏线性阵列的非正交波形分离","authors":"Qiao Chen, N. Tong, Yibei Dong, Lei Bao, Shuai Chen, Lixun Han","doi":"10.1109/ICEICT.2019.8846423","DOIUrl":null,"url":null,"abstract":"In order to solve the irregular crossing distance migration (IRCM) in the compression sensing waveform separation method, the paper studies the characteristics of the signal received by MIMO radar and explores the joint sparsity of the multiple measurement vector in different observation channels. Multiple measurement vector sparse recovery algorithm is used to separate the echo replaced the single-observation vector restoration algorithm. It cannot only reconstruct the one-dimensional distance image with high precision but also suppress the IRCM. Aiming at the problem that current joint sparse recovery algorithm has poor separation effect due to the unknown sparsity, a sparse degree adaptive joint sparse recovery algorithm is proposed to improve the effect of waveform separation.","PeriodicalId":382686,"journal":{"name":"2019 IEEE 2nd International Conference on Electronic Information and Communication Technology (ICEICT)","volume":"16 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Multiple Measurement Vector Sparsity Adaptive Algorithm Realize the non-orthogonal Waveform Separation of MIMO Sparse Linear Array\",\"authors\":\"Qiao Chen, N. Tong, Yibei Dong, Lei Bao, Shuai Chen, Lixun Han\",\"doi\":\"10.1109/ICEICT.2019.8846423\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In order to solve the irregular crossing distance migration (IRCM) in the compression sensing waveform separation method, the paper studies the characteristics of the signal received by MIMO radar and explores the joint sparsity of the multiple measurement vector in different observation channels. Multiple measurement vector sparse recovery algorithm is used to separate the echo replaced the single-observation vector restoration algorithm. It cannot only reconstruct the one-dimensional distance image with high precision but also suppress the IRCM. Aiming at the problem that current joint sparse recovery algorithm has poor separation effect due to the unknown sparsity, a sparse degree adaptive joint sparse recovery algorithm is proposed to improve the effect of waveform separation.\",\"PeriodicalId\":382686,\"journal\":{\"name\":\"2019 IEEE 2nd International Conference on Electronic Information and Communication Technology (ICEICT)\",\"volume\":\"16 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2019 IEEE 2nd International Conference on Electronic Information and Communication Technology (ICEICT)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICEICT.2019.8846423\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 IEEE 2nd International Conference on Electronic Information and Communication Technology (ICEICT)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICEICT.2019.8846423","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Multiple Measurement Vector Sparsity Adaptive Algorithm Realize the non-orthogonal Waveform Separation of MIMO Sparse Linear Array
In order to solve the irregular crossing distance migration (IRCM) in the compression sensing waveform separation method, the paper studies the characteristics of the signal received by MIMO radar and explores the joint sparsity of the multiple measurement vector in different observation channels. Multiple measurement vector sparse recovery algorithm is used to separate the echo replaced the single-observation vector restoration algorithm. It cannot only reconstruct the one-dimensional distance image with high precision but also suppress the IRCM. Aiming at the problem that current joint sparse recovery algorithm has poor separation effect due to the unknown sparsity, a sparse degree adaptive joint sparse recovery algorithm is proposed to improve the effect of waveform separation.