The PAMF detector is a parametric rao test

Hongbin Li, Kwang June Sohn, Braham Himed

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

10 Scopus citations

Abstract

The Rao test for an adaptive signal detection problem in space-time adaptive processing (STAP) applications is derived by modeling the disturbance signal as a multichannel autoregressive (AR) process. Interestingly, the Rao test takes a form identical to that of the recently introduced parametric adaptive matched filter (PAMF) detector. The equivalence corroborates that the Rao/PAMF detector is an asymptotic generalized likelihood ratio test (GLRT). The asymptotic distribution of the test statistic is obtained in closed-form, which is a central Chisquared distribution with two degrees of freedom under H 0 and, respectively, a noncentral Chi-squared distribution with two degrees of freedom and a noncentrality parameter determined by the output signal-to-noise-and-interference (SINR) ratio of a temporal whitening filter. Therefore, the Rao/PAMF achieves asymptotic constant false alarm rate (CFAR). Numerical results show that these results are accurate in predicting the performance of the Rao/PAMF detector even with moderate data support.

Original languageEnglish
Title of host publicationConference Record of The Thirty-Ninth Asilomar Conference on Signals, Systems and Computers
Pages1311-1315
Number of pages5
StatePublished - 2005
Event39th Asilomar Conference on Signals, Systems and Computers - Pacific Grove, CA, United States
Duration: 28 Oct 20051 Nov 2005

Publication series

NameConference Record - Asilomar Conference on Signals, Systems and Computers
Volume2005
ISSN (Print)1058-6393

Conference

Conference39th Asilomar Conference on Signals, Systems and Computers
Country/TerritoryUnited States
CityPacific Grove, CA
Period28/10/051/11/05

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