Asymptotic analysis of a GLRT for detection with large sensor arrays. Hiltunen, S., Loubaton, P., & Chevalier, P. In *2014 22nd European Signal Processing Conference (EUSIPCO)*, pages 2160-2164, Sep., 2014.

Paper abstract bibtex

Paper abstract bibtex

This paper addresses the performance analysis of two GLRT receivers in the case where the number of sensors M is of the same order of magnitude as the sample size N. In the asymptotic regime where M and N converge towards ∞ at the same rate, the corresponding asymptotic means and variances are characterized using large random matrix theory, and compared to the standard situation where N → +∞ and M is fixed. This asymptotic analysis allows to understand the behavior of the considered receivers, even for relatively small values of N and M.

@InProceedings{6952772, author = {S. Hiltunen and P. Loubaton and P. Chevalier}, booktitle = {2014 22nd European Signal Processing Conference (EUSIPCO)}, title = {Asymptotic analysis of a GLRT for detection with large sensor arrays}, year = {2014}, pages = {2160-2164}, abstract = {This paper addresses the performance analysis of two GLRT receivers in the case where the number of sensors M is of the same order of magnitude as the sample size N. In the asymptotic regime where M and N converge towards ∞ at the same rate, the corresponding asymptotic means and variances are characterized using large random matrix theory, and compared to the standard situation where N → +∞ and M is fixed. This asymptotic analysis allows to understand the behavior of the considered receivers, even for relatively small values of N and M.}, keywords = {array signal processing;matrix algebra;signal detection;statistical testing;GLRT asymptotic analysis;large sensor arrays;GLRT receiver performance analysis;large random matrix theory;signal detection;generalized likelihood test;Standards;Gaussian distribution;Context;Synchronization;Noise;Training;Covariance matrices;Multichannel detection;asymptotic analysis;large random matrices}, issn = {2076-1465}, month = {Sep.}, url = {https://www.eurasip.org/proceedings/eusipco/eusipco2014/html/papers/1569925435.pdf}, }

Downloads: 0

{"_id":"AaZe5nARrBszCcgr8","bibbaseid":"hiltunen-loubaton-chevalier-asymptoticanalysisofaglrtfordetectionwithlargesensorarrays-2014","authorIDs":[],"author_short":["Hiltunen, S.","Loubaton, P.","Chevalier, P."],"bibdata":{"bibtype":"inproceedings","type":"inproceedings","author":[{"firstnames":["S."],"propositions":[],"lastnames":["Hiltunen"],"suffixes":[]},{"firstnames":["P."],"propositions":[],"lastnames":["Loubaton"],"suffixes":[]},{"firstnames":["P."],"propositions":[],"lastnames":["Chevalier"],"suffixes":[]}],"booktitle":"2014 22nd European Signal Processing Conference (EUSIPCO)","title":"Asymptotic analysis of a GLRT for detection with large sensor arrays","year":"2014","pages":"2160-2164","abstract":"This paper addresses the performance analysis of two GLRT receivers in the case where the number of sensors M is of the same order of magnitude as the sample size N. In the asymptotic regime where M and N converge towards ∞ at the same rate, the corresponding asymptotic means and variances are characterized using large random matrix theory, and compared to the standard situation where N → +∞ and M is fixed. This asymptotic analysis allows to understand the behavior of the considered receivers, even for relatively small values of N and M.","keywords":"array signal processing;matrix algebra;signal detection;statistical testing;GLRT asymptotic analysis;large sensor arrays;GLRT receiver performance analysis;large random matrix theory;signal detection;generalized likelihood test;Standards;Gaussian distribution;Context;Synchronization;Noise;Training;Covariance matrices;Multichannel detection;asymptotic analysis;large random matrices","issn":"2076-1465","month":"Sep.","url":"https://www.eurasip.org/proceedings/eusipco/eusipco2014/html/papers/1569925435.pdf","bibtex":"@InProceedings{6952772,\n author = {S. Hiltunen and P. Loubaton and P. Chevalier},\n booktitle = {2014 22nd European Signal Processing Conference (EUSIPCO)},\n title = {Asymptotic analysis of a GLRT for detection with large sensor arrays},\n year = {2014},\n pages = {2160-2164},\n abstract = {This paper addresses the performance analysis of two GLRT receivers in the case where the number of sensors M is of the same order of magnitude as the sample size N. In the asymptotic regime where M and N converge towards ∞ at the same rate, the corresponding asymptotic means and variances are characterized using large random matrix theory, and compared to the standard situation where N → +∞ and M is fixed. This asymptotic analysis allows to understand the behavior of the considered receivers, even for relatively small values of N and M.},\n keywords = {array signal processing;matrix algebra;signal detection;statistical testing;GLRT asymptotic analysis;large sensor arrays;GLRT receiver performance analysis;large random matrix theory;signal detection;generalized likelihood test;Standards;Gaussian distribution;Context;Synchronization;Noise;Training;Covariance matrices;Multichannel detection;asymptotic analysis;large random matrices},\n issn = {2076-1465},\n month = {Sep.},\n url = {https://www.eurasip.org/proceedings/eusipco/eusipco2014/html/papers/1569925435.pdf},\n}\n\n","author_short":["Hiltunen, S.","Loubaton, P.","Chevalier, P."],"key":"6952772","id":"6952772","bibbaseid":"hiltunen-loubaton-chevalier-asymptoticanalysisofaglrtfordetectionwithlargesensorarrays-2014","role":"author","urls":{"Paper":"https://www.eurasip.org/proceedings/eusipco/eusipco2014/html/papers/1569925435.pdf"},"keyword":["array signal processing;matrix algebra;signal detection;statistical testing;GLRT asymptotic analysis;large sensor arrays;GLRT receiver performance analysis;large random matrix theory;signal detection;generalized likelihood test;Standards;Gaussian distribution;Context;Synchronization;Noise;Training;Covariance matrices;Multichannel detection;asymptotic analysis;large random matrices"],"metadata":{"authorlinks":{}}},"bibtype":"inproceedings","biburl":"https://raw.githubusercontent.com/Roznn/EUSIPCO/main/eusipco2014url.bib","creationDate":"2021-02-13T17:43:41.773Z","downloads":0,"keywords":["array signal processing;matrix algebra;signal detection;statistical testing;glrt asymptotic analysis;large sensor arrays;glrt receiver performance analysis;large random matrix theory;signal detection;generalized likelihood test;standards;gaussian distribution;context;synchronization;noise;training;covariance matrices;multichannel detection;asymptotic analysis;large random matrices"],"search_terms":["asymptotic","analysis","glrt","detection","large","sensor","arrays","hiltunen","loubaton","chevalier"],"title":"Asymptotic analysis of a GLRT for detection with large sensor arrays","year":2014,"dataSources":["A2ezyFL6GG6na7bbs"]}