A Persymmetric AMF for range localization in partially homogenous environment

Abstract

In this paper, we focus on the problem of point-like targets detection in a partially homogeneous interference environment with unknown covariance matrix. To this end, we assume the disturbances in both the cell under test and the secondary data share the same covariance matrix up to an unknown power scaling factor. Specifically, we jointly exploit the spillover of target energy to consecutive range samples and the persymmetric structure of the disturbance covariance matrix to improve the performances of target detection and range estimation. An adaptive architecture, referred to as the persymmetric modified AMF for partially homogeneous environment, is developed by relying on the ad hoc modifications of the generalized likelihood ratio test. Finally, a preliminary performance assessment highlights that the proposed decision scheme guarantees better detection and range localization performance compared with their natural competitors in sample starved environment.