Adaptive radar detection of targets embedded in Gaussian disturbance has represented an active field of research in the last decades.

Starting from the lack of a uniformly most powerful (UMP) test for the quoted problem, a variety of different solutions has been explored in open literature. However, these solutions may experience performance degradation in practice wherein the actual steering vector is not consistent with the nominal one.

A mismatched signal may appear subject to several causes, such as calibration and pointing errors, wavefront distortions and imperfect antenna shape. Moreover, most of existing papers deal with the case of a single cell under test, while the detection of multiple and/or distributed targets under mismatched signal models has not received much consideration until now. It naturally arises when data are collected by high resolution radars (HRRs) that can resolve a target into a number of scattering centers appearing into different range cells.

Scientists in the field of acoustics from home and abroad deal with the problem of detecting multiple point-like targets in the presence of steering vector mismatches and Gaussian disturbance.

Their research proposes two tunable detectors for multiple point-like targets and without a distinct set of secondary data. More precisely, it deals with the problem of detecting an unknown signal, lying in a conic set whose axis coincides with the nominal steering vector in the whitened observation space.

This model is a viable means to address adaptive detection in case of mismatched steering vectors. The performance assessment, conducted analytically for matched and mismatched signals, highlights that the proposed detectors achieve a visible performance improvement over the existing ones, especially in the presence of severe steering vector mismatches.

Nevertheless, for a large number of range cells contaminated by useful signals, the relative detection performance of the proposed detectors degrades. In order to circumvent this drawback, two persymmetric detectors based on the structure information of the disturbance covariance matrix (DCM) are proposed.

The performance of the persymmetric detectors show that the a-prior information on the covariance structure can lead to a noticeable performance improvement.

This research result was published online: http://jpier.org/PIER/pier.php?paper=12040208 and on the recently issued Progress In Electromagnetics Research (Vol. 129, Pages 231-250, 2012).