Clutter-Aware MIMO-OFDM Based Target Detection: Algorithm Design and Experimental Test

Wireless sensing aided by well-established communication systems is an important research direction in the area of integrated sensing and communications (ISAC). In this work, we investigate the clutter-aware target detection based on the commonly used multiple-input multiple-output orthogonal frequency division multiplexing (MIMO-OFDM) communication framework. Specifically, under the premise that the clutter covariance matrix is unknown, we develop two generalized likelihood ratio test (GLRT) based detection methods for the scenarios with unknown and known noise variance, respectively. We adopt practical fifth-generation (5G) new radio (NR) frames to perform both simulation and experiment, which show that the proposed methods yield remarkable performance gains compared to the traditional energy detector. Furthermore, when the noise variance is known, the proposed detector exhibits near-optimal performance.