Subspace gradient tests for range‐spread target detection in structured interference plus Gaussian clutter

Abstract

This study considers the problem of detecting range-spread targets embedded in subspace interference plus Gaussian clutter with an unknown covariance matrix. The target and interference signals are modeled in terms of deterministic signals belonging to two known subspaces, respectively. Based on the Gradient test criterion, two adaptive detectors are devised for rejecting subspace interference in homogeneous and partially homogeneous environments, respectively. Both of the proposed detectors theoretically exhibit a desirable property of a constant false alarm rate with respect to the clutter covariance matrix as well as the power level. Furthermore, the numerical results show that, compared with their existing counterparts, the proposed detectors exhibit better detection performance and satisfactory suppression performance for the interference.

A novel two-step detection algorithm for range spread target

“…For the multi-rank model, the extended target adaptive detector is used in cases where the power level of background noise and the covariance matrix are unknown. Two adaptive detectors are developed for subspace interference rejection in both homogeneous and partially homogeneous environments, guided by the Gradient test criterion 13 . A method for non-Gaussian clutter background involves utilizing the anti-symmetric structural information of clutter covariance matrix in a radar receiver unit's spatial or time-centered symmetric detection scenario.…”