Performance Analysis of a Robust Matched Subspace Detector

Abstract

The area of robust detection in the presence of partly unknown useful signal or interference is a widespread task in many signal processing applications. In this paper, we consider the robustness of a matched subspace detector in additive white Gaussian noise, under the condition that the noise power is known under null hypothesis, and unknown under alternative hypothesis when the useful signal triggers an variation of noise power, and we also consider the mismatch between the signal subspace and receiver matched filter. The test statistic of this detection problem is derived based on generalized likelihood ratio test, and the distribution of the test statistic is analysis. The computer simulation is used to validate the performance analysis and the robustness of this algorithm at low SNR, compared with other matched subspace detectors.