An analysis of noncoherent adaptive detection scheme

A nonstationary adaptive detection scheme based on a generalized likelihood ratio test (GLRT) formulation where the radar returned signal amplitude and the true covariance matrix are unknown is presented. The probability density function of the GLR test under the noise-only hypothesis is central χ², and the appropriate threshold value to a desired probability of false alarm rate is readily obtained. Under the signal plus noise hypothesis, an exact statistical characterization of the test cannot be obtained, and therefore a Chernoff bound is derived. The performance of the GLR test in terms of the probability of detection versus signal-to-noise ratio (SNR) is evaluated using Monte Carlo simulations. The test´s performance is compared with results obtained from the Chernoff bound and the optimal matched filter (known covariance matrix) case. The noncoherent detector´s performance asymptotically approaches matched filter performance levels