Projector's weighting for W-MUSIC: An alternative to RMT. Ferréol, A. & Larzabal, P. In *2017 25th European Signal Processing Conference (EUSIPCO)*, pages 1966-1970, Aug, 2017.

Paper doi abstract bibtex

Paper doi abstract bibtex

In the last decade, modified subspace DoA estimation methods such as G-MUSIC have been proposed, in the context where the number of available snapshots N is of the same order of magnitude than the number of sensors M. In this context, the conventional MUSIC algorithm fails in presence of close sources because the empirical covariance matrix is a poor estimate of the true covariance matrix. The G-MUSIC algorithm is based on Marcenko-Pastur's works about the distribution of the eigenvalues of the empirical covariance matrix. A new modified MUSIC algorithm is proposed. It is based on the correction of the noise projector obtained by complex Wishart distribution of the empirical covariance matrix.

@InProceedings{8081553, author = {A. Ferréol and P. Larzabal}, booktitle = {2017 25th European Signal Processing Conference (EUSIPCO)}, title = {Projector's weighting for W-MUSIC: An alternative to RMT}, year = {2017}, pages = {1966-1970}, abstract = {In the last decade, modified subspace DoA estimation methods such as G-MUSIC have been proposed, in the context where the number of available snapshots N is of the same order of magnitude than the number of sensors M. In this context, the conventional MUSIC algorithm fails in presence of close sources because the empirical covariance matrix is a poor estimate of the true covariance matrix. The G-MUSIC algorithm is based on Marcenko-Pastur's works about the distribution of the eigenvalues of the empirical covariance matrix. A new modified MUSIC algorithm is proposed. It is based on the correction of the noise projector obtained by complex Wishart distribution of the empirical covariance matrix.}, keywords = {covariance matrices;direction-of-arrival estimation;eigenvalues and eigenfunctions;signal classification;G-MUSIC algorithm;covariance matrix;W-MUSIC;DoA estimation methods;Marcenko-Pasturs works;Wishart distribution;Multiple signal classification;Covariance matrices;Direction-of-arrival estimation;Signal processing algorithms;Sensors;Estimation;Perturbation methods;MUSIC;DoA estimation;Performances analysis;Wishart distribution;Random matrices}, doi = {10.23919/EUSIPCO.2017.8081553}, issn = {2076-1465}, month = {Aug}, url = {https://www.eurasip.org/proceedings/eusipco/eusipco2017/papers/1570346531.pdf}, }

Downloads: 0

{"_id":"f5MX2vgvA3Qtp2LDQ","bibbaseid":"ferrol-larzabal-projectorsweightingforwmusicanalternativetormt-2017","authorIDs":[],"author_short":["Ferréol, A.","Larzabal, P."],"bibdata":{"bibtype":"inproceedings","type":"inproceedings","author":[{"firstnames":["A."],"propositions":[],"lastnames":["Ferréol"],"suffixes":[]},{"firstnames":["P."],"propositions":[],"lastnames":["Larzabal"],"suffixes":[]}],"booktitle":"2017 25th European Signal Processing Conference (EUSIPCO)","title":"Projector's weighting for W-MUSIC: An alternative to RMT","year":"2017","pages":"1966-1970","abstract":"In the last decade, modified subspace DoA estimation methods such as G-MUSIC have been proposed, in the context where the number of available snapshots N is of the same order of magnitude than the number of sensors M. In this context, the conventional MUSIC algorithm fails in presence of close sources because the empirical covariance matrix is a poor estimate of the true covariance matrix. The G-MUSIC algorithm is based on Marcenko-Pastur's works about the distribution of the eigenvalues of the empirical covariance matrix. A new modified MUSIC algorithm is proposed. It is based on the correction of the noise projector obtained by complex Wishart distribution of the empirical covariance matrix.","keywords":"covariance matrices;direction-of-arrival estimation;eigenvalues and eigenfunctions;signal classification;G-MUSIC algorithm;covariance matrix;W-MUSIC;DoA estimation methods;Marcenko-Pasturs works;Wishart distribution;Multiple signal classification;Covariance matrices;Direction-of-arrival estimation;Signal processing algorithms;Sensors;Estimation;Perturbation methods;MUSIC;DoA estimation;Performances analysis;Wishart distribution;Random matrices","doi":"10.23919/EUSIPCO.2017.8081553","issn":"2076-1465","month":"Aug","url":"https://www.eurasip.org/proceedings/eusipco/eusipco2017/papers/1570346531.pdf","bibtex":"@InProceedings{8081553,\n author = {A. Ferréol and P. Larzabal},\n booktitle = {2017 25th European Signal Processing Conference (EUSIPCO)},\n title = {Projector's weighting for W-MUSIC: An alternative to RMT},\n year = {2017},\n pages = {1966-1970},\n abstract = {In the last decade, modified subspace DoA estimation methods such as G-MUSIC have been proposed, in the context where the number of available snapshots N is of the same order of magnitude than the number of sensors M. In this context, the conventional MUSIC algorithm fails in presence of close sources because the empirical covariance matrix is a poor estimate of the true covariance matrix. The G-MUSIC algorithm is based on Marcenko-Pastur's works about the distribution of the eigenvalues of the empirical covariance matrix. A new modified MUSIC algorithm is proposed. It is based on the correction of the noise projector obtained by complex Wishart distribution of the empirical covariance matrix.},\n keywords = {covariance matrices;direction-of-arrival estimation;eigenvalues and eigenfunctions;signal classification;G-MUSIC algorithm;covariance matrix;W-MUSIC;DoA estimation methods;Marcenko-Pasturs works;Wishart distribution;Multiple signal classification;Covariance matrices;Direction-of-arrival estimation;Signal processing algorithms;Sensors;Estimation;Perturbation methods;MUSIC;DoA estimation;Performances analysis;Wishart distribution;Random matrices},\n doi = {10.23919/EUSIPCO.2017.8081553},\n issn = {2076-1465},\n month = {Aug},\n url = {https://www.eurasip.org/proceedings/eusipco/eusipco2017/papers/1570346531.pdf},\n}\n\n","author_short":["Ferréol, A.","Larzabal, P."],"key":"8081553","id":"8081553","bibbaseid":"ferrol-larzabal-projectorsweightingforwmusicanalternativetormt-2017","role":"author","urls":{"Paper":"https://www.eurasip.org/proceedings/eusipco/eusipco2017/papers/1570346531.pdf"},"keyword":["covariance matrices;direction-of-arrival estimation;eigenvalues and eigenfunctions;signal classification;G-MUSIC algorithm;covariance matrix;W-MUSIC;DoA estimation methods;Marcenko-Pasturs works;Wishart distribution;Multiple signal classification;Covariance matrices;Direction-of-arrival estimation;Signal processing algorithms;Sensors;Estimation;Perturbation methods;MUSIC;DoA estimation;Performances analysis;Wishart distribution;Random matrices"],"metadata":{"authorlinks":{}}},"bibtype":"inproceedings","biburl":"https://raw.githubusercontent.com/Roznn/EUSIPCO/main/eusipco2017url.bib","creationDate":"2021-02-13T16:38:25.732Z","downloads":0,"keywords":["covariance matrices;direction-of-arrival estimation;eigenvalues and eigenfunctions;signal classification;g-music algorithm;covariance matrix;w-music;doa estimation methods;marcenko-pasturs works;wishart distribution;multiple signal classification;covariance matrices;direction-of-arrival estimation;signal processing algorithms;sensors;estimation;perturbation methods;music;doa estimation;performances analysis;wishart distribution;random matrices"],"search_terms":["projector","weighting","music","alternative","rmt","ferréol","larzabal"],"title":"Projector's weighting for W-MUSIC: An alternative to RMT","year":2017,"dataSources":["2MNbFYjMYTD6z7ExY"]}