Chapter 7 - Compound-Gaussian Models and Target Detection: A Unified View

As a radar operates, it generally receives clutter returns from the environment that must be distinguished from targets of interest. If one assumes that the clutter returns obey complex multivariate Gaussian statistics, then a straightforward application of statistical detection theory leads to an optimal detector in the form of the well-known matched filter (Chap. 2 of this book). The occurrence of Gaussian statistics is often justified on the basis of the Central Limit Theorem (CLT) applied to a phenomenological scattering picture that models the radar return as arising from contributions of a large number of scatterers in the radar resolution cell. In this case, the univariate intensity tail distribution is exponential. For early, low resolution radars, this model was adequate.