An auto-regressive GLR algorithm for adaptive radar detection

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.