Performance prediction modelling for high resolution radar with scan-to-scan processing

Performance prediction modelling is a useful tool for assessing the target detection characteristics of a radar system given a statistical description of its environment. Typical approaches include analytic results, Monte-Carlo simulation or using numerical representations of the distribution functions. The latter approach avoids difficult analytic solutions and the processing overhead of Monte-Carlo simulations. This paper presents a numerical implementation of a detection scheme for an airborne radar system that is difficult to model analytically. The signal processing includes range stretching followed by an autoregressive scan-to-scan integration. Two cases are considered for the stretch processing depending on whether the clutter is spatially correlated or uncorrelated.