{"title":"一种低复杂度制导最小方差波束形成算法及其在弱目标检测中的应用","authors":"Zhu Daizhu, Guo Haoquan","doi":"10.1109/ICICSP50920.2020.9232126","DOIUrl":null,"url":null,"abstract":"Although the character of high azimuth resolution and without side lobe, steered minimum variance(STMV) beamforming algorithm is limited to engineering application because of its computational cost. A low complexity steered minimum variance(LCSTMV) beamforming algorithm is proposed in this paper. The block matrix iterative inversion formula is deduced, the computation complexity of the traditional STMV algorithm with M array elements is reduced to nearly 1/4M. The simulation data analysis shows that its performance is in good agreement with that of the traditional STMV algorithm. And the processing with the sea trial data shows that the LCSTMV algorithm inherits all of the ability of STMV while computational amount reduced sharply.","PeriodicalId":117760,"journal":{"name":"2020 IEEE 3rd International Conference on Information Communication and Signal Processing (ICICSP)","volume":"265 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A Low-complexity Steered Minimum Variance Beamforming Algorithm and Its Application on Weak-target Detection\",\"authors\":\"Zhu Daizhu, Guo Haoquan\",\"doi\":\"10.1109/ICICSP50920.2020.9232126\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Although the character of high azimuth resolution and without side lobe, steered minimum variance(STMV) beamforming algorithm is limited to engineering application because of its computational cost. A low complexity steered minimum variance(LCSTMV) beamforming algorithm is proposed in this paper. The block matrix iterative inversion formula is deduced, the computation complexity of the traditional STMV algorithm with M array elements is reduced to nearly 1/4M. The simulation data analysis shows that its performance is in good agreement with that of the traditional STMV algorithm. And the processing with the sea trial data shows that the LCSTMV algorithm inherits all of the ability of STMV while computational amount reduced sharply.\",\"PeriodicalId\":117760,\"journal\":{\"name\":\"2020 IEEE 3rd International Conference on Information Communication and Signal Processing (ICICSP)\",\"volume\":\"265 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-09-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2020 IEEE 3rd International Conference on Information Communication and Signal Processing (ICICSP)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICICSP50920.2020.9232126\",\"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 3rd International Conference on Information Communication and Signal Processing (ICICSP)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICICSP50920.2020.9232126","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A Low-complexity Steered Minimum Variance Beamforming Algorithm and Its Application on Weak-target Detection
Although the character of high azimuth resolution and without side lobe, steered minimum variance(STMV) beamforming algorithm is limited to engineering application because of its computational cost. A low complexity steered minimum variance(LCSTMV) beamforming algorithm is proposed in this paper. The block matrix iterative inversion formula is deduced, the computation complexity of the traditional STMV algorithm with M array elements is reduced to nearly 1/4M. The simulation data analysis shows that its performance is in good agreement with that of the traditional STMV algorithm. And the processing with the sea trial data shows that the LCSTMV algorithm inherits all of the ability of STMV while computational amount reduced sharply.