ASCRL evaluation with parametrically constrained covariance matrix. Issue 11 (2nd May 2018) - Tan, Jie; Wang, Yikai; He, Zishu; Sun, Guohao
Abstract : In this Letter, the authors propose an approach to evaluate the average signal‐to‐clutter ratio loss (ASCRL) of an adaptive radar filter with a parametrically constrained clutter covariance matrix (CCM). The approach is a two‐step strategy, the constrained Cramér–Rao bound of the CCM estimate is first derived, and then it is used to derive the ASCRL. More specifically, the ASCRL of an adaptive filter with a trace constrained CCM is derived. Simulation results show that our approach performs well in evaluating the trace constrained ASCRL for both complex Gaussian clutter and compound‐Gaussian clutter.