Subspace Compressive GLRT Detector for MIMO Radar in the Presence of Clutter

Abstract

The problem of optimising the target detection performance of MIMO radar in the presence of clutter is considered. The increased false alarm rate which is a consequence of the presence of clutter returns is known to seriously degrade the target detection performance of the radar target detector, especially under low SNR conditions. In this paper, a mathematical model is proposed to optimise the target detection performance of a MIMO radar detector in the presence of clutter. The number of samples that are required to be processed by a radar target detector regulates the amount of processing burden while achieving a given detection reliability. While Subspace Compressive GLRT (SSC-GLRT) detector is known to give optimised radar target detection performance with reduced computational complexity, it however suffers a significant deterioration in target detection performance in the presence of clutter. In this paper we provide evidence that the proposed mathematical model for SSC-GLRT detector outperforms the existing detectors in the presence of clutter. The performance analysis of the existing detectors and the proposed SSC-GLRT detector for MIMO radar in the presence of clutter are provided in this paper.

Energy efficient target detection through waveform selection for multi-sensor RF sensing based Internet of Things

“…In the existing literature, various RF sensing based target detectors [7][8][9][10] have been proposed by the authors. However, existing RF sensing based target detection strategies are computationally intense for resource constrained sensor nodes within IoT.…”