TY - GEN
T1 - Multichannel parametric Rao detector
AU - Sohn, Kwang June
AU - Li, Hongbin
AU - Himed, Braham
PY - 2006
Y1 - 2006
N2 - The parametric Rao test for a multichannel adaptive signal detection problem is derived by modeling the disturbance signal as a multichannel autoregressive (AR) process. Interestingly, the parametric Rao test takes a form identical to that of the recently introduced parametric adaptive matched filter (PAMF) detector. The equivalence offers new insights into the performance and implementation of the PAMF detector. Specifically, the Rao/PAMF detector is asymptotically (for large samples) a parametric generalized likelihood ratio test (GLRT), due to an asymptotic equivalence between the Rao test and the GLRT. The asymptotic distribution of the Rao test statistic is obtained in closed-form, which follows an exponential distribution under H0 and, respectively, a non-central Chi-squared distribution with two degrees of freedom under H17. The non-centrality parameter of the non-central Chi-squared distribution is determined by the output signal-to-interference- plus-noise ratio (SINR) of a temporal whitening filter. Since the asymptotic distribution under Ho is independent of the unknown parameters, the Rao/PAMF asymptotically achieves constant false alarm rate (CFAR). Numerical results show that these results are accurate in predicting the performance of the parametric Rao/PAMF detector even with moderate data support.
AB - The parametric Rao test for a multichannel adaptive signal detection problem is derived by modeling the disturbance signal as a multichannel autoregressive (AR) process. Interestingly, the parametric Rao test takes a form identical to that of the recently introduced parametric adaptive matched filter (PAMF) detector. The equivalence offers new insights into the performance and implementation of the PAMF detector. Specifically, the Rao/PAMF detector is asymptotically (for large samples) a parametric generalized likelihood ratio test (GLRT), due to an asymptotic equivalence between the Rao test and the GLRT. The asymptotic distribution of the Rao test statistic is obtained in closed-form, which follows an exponential distribution under H0 and, respectively, a non-central Chi-squared distribution with two degrees of freedom under H17. The non-centrality parameter of the non-central Chi-squared distribution is determined by the output signal-to-interference- plus-noise ratio (SINR) of a temporal whitening filter. Since the asymptotic distribution under Ho is independent of the unknown parameters, the Rao/PAMF asymptotically achieves constant false alarm rate (CFAR). Numerical results show that these results are accurate in predicting the performance of the parametric Rao/PAMF detector even with moderate data support.
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M3 - Conference contribution
AN - SCOPUS:33947617699
SN - 142440469X
SN - 9781424404698
T3 - ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
SP - IV1101-IV1104
BT - 2006 IEEE International Conference on Acoustics, Speech, and Signal Processing - Proceedings
T2 - 2006 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2006
Y2 - 14 May 2006 through 19 May 2006
ER -