On Persymmetric Covariance Matrices in Adaptive Detection

In the general area of radar detection, estimation of the clutter covariance matrix is an important point. This matrix commonly exhibits a persymmetric structure: this is the case for instance for active systems using a symmetrically spaced linear array or pulse train. In this context, this paper provides a new Gaussian adaptive detector called the persymmetric adaptive matched filter (P-AMF). Its theoretical distribution is derived allowing adjustment of the detection threshold for a given probability of false alarm (PFA). Simulations results highlight the improvement in term of probability of detection (PD) of the P-AMF in comparison with the classical adaptive matched filter (AMF).