TY - GEN
T1 - Parametric multichannel adaptive signal detection
T2 - 2012 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2012
AU - Wang, Pu
AU - Sahinoglu, Zafer
AU - Pun, Man On
AU - Li, Hongbin
PY - 2012
Y1 - 2012
N2 - This paper considers a parametric approach for adaptive multichannel signal detection, where the disturbance is modeled by a multichannel auto-regressive (AR) process. Motivated by the fact that a symmetric antenna geometry usually yields a persymmetric structure on the covariance matrix of disturbance, a new persymmetric AR (PAR) modeling for the disturbance is proposed and, accordingly, a persymmetric parametric adaptive matched filter (Per-PAMF) is developed. The developed Per-PAMF, while allowing a simple implementation like the traditional PAMF, extends the PAMF by developing the maximum likelihood (ML) estimation of unknown nuisance (disturbance-related) parameters under the persymmetric constraint. Numerical results show that the Per-PAMF provides significantly better detection performance than the conventional PAMF and other non-parametric detectors when the number of training signals is limited.
AB - This paper considers a parametric approach for adaptive multichannel signal detection, where the disturbance is modeled by a multichannel auto-regressive (AR) process. Motivated by the fact that a symmetric antenna geometry usually yields a persymmetric structure on the covariance matrix of disturbance, a new persymmetric AR (PAR) modeling for the disturbance is proposed and, accordingly, a persymmetric parametric adaptive matched filter (Per-PAMF) is developed. The developed Per-PAMF, while allowing a simple implementation like the traditional PAMF, extends the PAMF by developing the maximum likelihood (ML) estimation of unknown nuisance (disturbance-related) parameters under the persymmetric constraint. Numerical results show that the Per-PAMF provides significantly better detection performance than the conventional PAMF and other non-parametric detectors when the number of training signals is limited.
KW - Multichannel signal processing
KW - adaptive matched filter
KW - auto-regressive process
KW - maximum likelihood estimation
KW - multichannel
KW - persymmetry
UR - http://www.scopus.com/inward/record.url?scp=84867611229&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84867611229&partnerID=8YFLogxK
U2 - 10.1109/ICASSP.2012.6288411
DO - 10.1109/ICASSP.2012.6288411
M3 - Conference contribution
AN - SCOPUS:84867611229
SN - 9781467300469
T3 - ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
SP - 2449
EP - 2452
BT - 2012 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2012 - Proceedings
Y2 - 25 March 2012 through 30 March 2012
ER -