A Comparison of Channel Matrix-Based and Covariance-Based Clutter Models

In this study, we analyze the performance of Generalized Likelihood Ratio Test (GLRT) statistics in MIMO radar systems under two distinct clutter modeling approaches: one that models clutter as an output of the channel matrix and another that models it within the covariance of the data distribution. This comparison reveals key trade-offs in adaptive detection performance between covariance-based and mean-based clutter modeling. By simulating a simple numerical example, we demonstrate the performance differences and identify scenarios where each model excels, providing practical insights into the conditions favoring one approach over the other for enhanced adaptive detection.