Adaptive multichannel detectors for distributed target based on gradient test

Abstract This paper investigates the adaptive detection problem of a distributed target embedded in Gaussian noise with unknown covariance matrix, where the target signal is assumed to belong to a known subspace, but corresponding coordinate is unknown. Resorting to the gradient test, we propose two adaptive detectors for homogeneous environment (HE) and partially HE (PHE), respectively. These two detectors both ensure the constant false alarm rate (CFAR) property. Simulation results show that the proposed detectors outperform its competitors in some scenarios.