In this paper, we consider a distributed multiple-input multiple-output (MIMO) radar which radiates waveforms with non-ideal cross- and auto-correlation functions and derive a novel subspace-based procedure to detect and localize multiple prospective targets. The proposed solution solves a sequence of composite binary hypothesis testing problems by resorting to the generalized information criterion (GIC); in particular, at each step, it aims to detect and localize one additional target, upon removing the interference caused by the previously-detected targets. An illustrative example is provided.
@article{arxiv.2205.08911,
title = {Subspace-Based Detection and Localization in Distributed MIMO Radars},
author = {Yangming Lai and Luca Venturino and Emanuele Grossi and Wei Yi},
journal= {arXiv preprint arXiv:2205.08911},
year = {2022}
}
Comments
Accepted for presentation at 2022 IEEE Sensor Array and Multichannel Signal Processing Workshop (SAM 2022)