{"_id":"qw5asowstT8zy4Ahe","bibbaseid":"santamaria-via-scharf-wang-aglrtapproachfordetectingcorrelatedsignalsinwhitenoiseintwomimochannels-2017","authorIDs":[],"author_short":["Santamaria, I.","Via, J.","Scharf, L. L.","Wang, Y."],"bibdata":{"bibtype":"inproceedings","type":"inproceedings","author":[{"firstnames":["I."],"propositions":[],"lastnames":["Santamaria"],"suffixes":[]},{"firstnames":["J."],"propositions":[],"lastnames":["Via"],"suffixes":[]},{"firstnames":["L.","L."],"propositions":[],"lastnames":["Scharf"],"suffixes":[]},{"firstnames":["Y."],"propositions":[],"lastnames":["Wang"],"suffixes":[]}],"booktitle":"2017 25th European Signal Processing Conference (EUSIPCO)","title":"A GLRT approach for detecting correlated signals in white noise in two MIMO channels","year":"2017","pages":"1395-1399","abstract":"In this work, we consider a second-order detection problem where rank-p signals are structured by an unknown, but common, p-dimensional random vector and then received through unknown M × p matrices at each of two M-element arrays. The noises in each channel are independent with identical variances. We derive generalized likelihood ratio (GLR) tests for this problem when the noise variance is either known or unknown. The resulting detection problems may be phrased as two-channel factor analysis problems.","keywords":"covariance matrices;Gaussian noise;maximum likelihood detection;MIMO radar;radar detection;radar signal processing;signal detection;statistical analysis;vectors;white noise;second-order detection problem;MIMO channels;white noise;correlated signals;GLRT approach;two-channel factor analysis problems;noise variance;generalized likelihood ratio tests;M-element arrays;unknown M × p matrices;p-dimensional random vector;rank-p signals;Covariance matrices;Surveillance;Antenna arrays;Maximum likelihood estimation;Load modeling;MIMO;Radar antennas;Passive detection;MIMO channels;passive radar;generalized likelihood ratio","doi":"10.23919/EUSIPCO.2017.8081438","issn":"2076-1465","month":"Aug","url":"https://www.eurasip.org/proceedings/eusipco/eusipco2017/papers/1570346642.pdf","bibtex":"@InProceedings{8081438,\n author = {I. Santamaria and J. Via and L. L. Scharf and Y. Wang},\n booktitle = {2017 25th European Signal Processing Conference (EUSIPCO)},\n title = {A GLRT approach for detecting correlated signals in white noise in two MIMO channels},\n year = {2017},\n pages = {1395-1399},\n abstract = {In this work, we consider a second-order detection problem where rank-p signals are structured by an unknown, but common, p-dimensional random vector and then received through unknown M × p matrices at each of two M-element arrays. The noises in each channel are independent with identical variances. We derive generalized likelihood ratio (GLR) tests for this problem when the noise variance is either known or unknown. The resulting detection problems may be phrased as two-channel factor analysis problems.},\n keywords = {covariance matrices;Gaussian noise;maximum likelihood detection;MIMO radar;radar detection;radar signal processing;signal detection;statistical analysis;vectors;white noise;second-order detection problem;MIMO channels;white noise;correlated signals;GLRT approach;two-channel factor analysis problems;noise variance;generalized likelihood ratio tests;M-element arrays;unknown M × p matrices;p-dimensional random vector;rank-p signals;Covariance matrices;Surveillance;Antenna arrays;Maximum likelihood estimation;Load modeling;MIMO;Radar antennas;Passive detection;MIMO channels;passive radar;generalized likelihood ratio},\n doi = {10.23919/EUSIPCO.2017.8081438},\n issn = {2076-1465},\n month = {Aug},\n url = {https://www.eurasip.org/proceedings/eusipco/eusipco2017/papers/1570346642.pdf},\n}\n\n","author_short":["Santamaria, I.","Via, J.","Scharf, L. L.","Wang, Y."],"key":"8081438","id":"8081438","bibbaseid":"santamaria-via-scharf-wang-aglrtapproachfordetectingcorrelatedsignalsinwhitenoiseintwomimochannels-2017","role":"author","urls":{"Paper":"https://www.eurasip.org/proceedings/eusipco/eusipco2017/papers/1570346642.pdf"},"keyword":["covariance matrices;Gaussian noise;maximum likelihood detection;MIMO radar;radar detection;radar signal processing;signal detection;statistical analysis;vectors;white noise;second-order detection problem;MIMO channels;white noise;correlated signals;GLRT approach;two-channel factor analysis problems;noise variance;generalized likelihood ratio tests;M-element arrays;unknown M × p matrices;p-dimensional random vector;rank-p signals;Covariance matrices;Surveillance;Antenna arrays;Maximum likelihood estimation;Load modeling;MIMO;Radar antennas;Passive detection;MIMO channels;passive radar;generalized likelihood ratio"],"metadata":{"authorlinks":{}},"downloads":0},"bibtype":"inproceedings","biburl":"https://raw.githubusercontent.com/Roznn/EUSIPCO/main/eusipco2017url.bib","creationDate":"2021-02-13T16:38:25.670Z","downloads":0,"keywords":["covariance matrices;gaussian noise;maximum likelihood detection;mimo radar;radar detection;radar signal processing;signal detection;statistical analysis;vectors;white noise;second-order detection problem;mimo channels;white noise;correlated signals;glrt approach;two-channel factor analysis problems;noise variance;generalized likelihood ratio tests;m-element arrays;unknown m × p matrices;p-dimensional random vector;rank-p signals;covariance matrices;surveillance;antenna arrays;maximum likelihood estimation;load modeling;mimo;radar antennas;passive detection;mimo channels;passive radar;generalized likelihood ratio"],"search_terms":["glrt","approach","detecting","correlated","signals","white","noise","two","mimo","channels","santamaria","via","scharf","wang"],"title":"A GLRT approach for detecting correlated signals in white noise in two MIMO channels","year":2017,"dataSources":["2MNbFYjMYTD6z7ExY","uP2aT6Qs8sfZJ6s8b"]}