TY - JOUR
T1 - A GLRT for multichannel radar detection in the presence of both compound Gaussian clutter and additive white Gaussian noise
AU - Liu, Bin
AU - Chen, Biao
AU - Michels, James H.
N1 - Funding Information:
Keywords: Maximum likelihood estimate; Generalized likelihood ratio test; Spherically invariant random processes; Multichannel radar detection ✩ This work was supported by the Air Force Research Laboratory under Cooperative Agreement F30602-01-2-0525. This paper was presented in part at the Second IEEE Sensor Array and Multichannel Signal Processing Workshop (SAM ’02), Rosslyn, VA, August 2002. E-mail addresses: [email protected] (B. Liu), [email protected] (B. Chen), [email protected] (J.H. Michels). 1 Fax: +1 315 443 2583.
PY - 2005/9
Y1 - 2005/9
N2 - Motivated by multichannel radar detection applications in the presence of both white Gaussian noise and Gaussian clutter with unknown power, we develop maximum likelihood parameter estimates for the disturbance process. Both cases with known and unknown white noise variance are treated. As the estimators do not admit closed-form solutions, numerical iterative procedures are developed that are guaranteed to at least converge to the local maximum. The developed estimates allow us to construct a generalized likelihood ratio test (GLRT) for the detection of a signal with constant but unknown amplitude. This GLRT has important applications in multichannel radar detection involving both white Gaussian noise and spherically invariant random process clutter and is shown to have better detection performance and CFAR property compared with existing statistics.
AB - Motivated by multichannel radar detection applications in the presence of both white Gaussian noise and Gaussian clutter with unknown power, we develop maximum likelihood parameter estimates for the disturbance process. Both cases with known and unknown white noise variance are treated. As the estimators do not admit closed-form solutions, numerical iterative procedures are developed that are guaranteed to at least converge to the local maximum. The developed estimates allow us to construct a generalized likelihood ratio test (GLRT) for the detection of a signal with constant but unknown amplitude. This GLRT has important applications in multichannel radar detection involving both white Gaussian noise and spherically invariant random process clutter and is shown to have better detection performance and CFAR property compared with existing statistics.
KW - Generalized likelihood ratio test
KW - Maximum likelihood estimate
KW - Multichannel radar detection
KW - Spherically invariant random processes
UR - http://www.scopus.com/inward/record.url?scp=24144474971&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=24144474971&partnerID=8YFLogxK
U2 - 10.1016/j.dsp.2005.01.010
DO - 10.1016/j.dsp.2005.01.010
M3 - Article
AN - SCOPUS:24144474971
SN - 1051-2004
VL - 15
SP - 437
EP - 454
JO - Digital Signal Processing: A Review Journal
JF - Digital Signal Processing: A Review Journal
IS - 5
ER -