Persymmetric adaptive detection and range estimation of a small target

Abstract

In this paper, we address the problem of detecting relatively small targets in the presence of Gaussian disturbance with unknown covariance matrix. To this end, we jointly exploit the spillover of target energy to consecutive range samples and the particular persymmetric structure of the disturbance covariance matrix to improve the performances of detection and range localization. In this context, we derive two adaptive detectors relying on the generalized likelihood ratio test and on ad hoc design procedure. Remarkably, the new receivers ensure the constant false alarm rate property with respect to the disturbance covariance matrix. The performance assessments, conducted on both simulated data and real recorded datasets, demonstrate the effectiveness of the proposed detectors compared with both the traditional unstructured counterparts and the state-of-the-art persymmetric detectors that ignore the spillover.