Multichannel Adaptive Detection Based on Gradient Test and Durbin Test in Deterministic Interference and Structure Nonhomogeneity
Mengru Sun, Weijian Liu, Jun Liu, Chengpeng Hao
Abstract
In this letter, we consider the problem of detecting a multichannel subspace signal in the presence of deterministic interference and structure nonhomogeneity. We derive the gradient test, Durbin test, and their two-step (2S) variants. The gradient test and its 2S variant have the same form as the existing generalized likelihood ratio test for the same detection problem, whereas the Durbin test and its 2S variant are new detectors. Numerical examples show that the two proposed new detectors, i.e., the Durbin test and its 2S variant, can provide better detection performance in some scenarios. In particular, they are robust to signal mismatch, and can perform well when the structure nonhomogeneity is not serious.