Adaptive Signal Detection in Auto-Regressive Interference with Gaussian Spectrum

A detector for the case of a radar target with known doppler and unknowncomplex amplitude in complex gaussian noise with unknown parameters has been derived.the detector assumes that the noise is an auto-regressive (ar) process with gaussianautocorrelation function which is a suitable model for ground clutter in most scenariosinvolving airborne radars. the detector estimates the unknown parameters by maximumlikelihood (ml) estimation for the use in the generalized likelihood ratio test (glrt).by computer simulations, it has been shown that for large data records, this detector isconstant false alarm rate (cfar) with respect to ar model driving noise variance. also,measurements show the detector excellent performance in a practical setting. the detector’sperformance in various simulated and actual conditions and the result of comparison withkelly’s glr and ar-glr detectors are also presented.