Title :
An auto-regressive GLR algorithm for adaptive radar detection
Author :
Sheikhi, A. ; Nayebi, M.M.
Abstract :
A detector for the case of a radar target with known Doppler and unknown complex amplitude in colored noise of unknown covariance has been derived. The detector assumes that the noise is an autoregressive process and estimates the unknown parameters by maximum likelihood estimation for the use in the generalized likelihood ratio test. The asymptotic performance of this detector has been derived and it has been shown that for large data records this detector is CFAR. By computer simulation it has been shown that for a moderate size of data record, the performance of this detector approaches the asymptotic results
Keywords :
Doppler effect; adaptive radar; adaptive signal detection; autoregressive processes; covariance analysis; maximum likelihood estimation; noise; radar detection; CFAR; Doppler amplitude; adaptive radar detection; asymptotic performance; asymptotic results; auto-regressive GLR algorithm; autoregressive process; colored noise; complex amplitude; computer simulation; covariance; generalized likelihood ratio test; large data records; maximum likelihood estimation; noise; parameter estimation; performance; radar target; Autoregressive processes; Colored noise; Detectors; Doppler radar; Maximum likelihood detection; Maximum likelihood estimation; Parameter estimation; Radar detection; Signal to noise ratio; Testing;
Conference_Titel :
Radar Conference, 1998. RADARCON 98. Proceedings of the 1998 IEEE
Conference_Location :
Dallas, TX
Print_ISBN :
0-7803-4492-8
DOI :
10.1109/NRC.1998.678016
