Multiple-Target Localization by Millimeter-Wave Radars With Trapezoid Virtual Antenna Arrays

Abstract

We consider the problem of localizing multiple targets by millimeter wave (mmWave) radars with irregular antenna placement, i.e., trapezoid virtual antenna array. The goal is to estimate both the number of targets and their 3-D locations. While many well-known algorithms have been developed for either problems, they still suffer from several limitations, such as the need for a large amount of sampled radar data and high computation complexity. In this work, we develop an efficient solution by exploring the received signal structure in two steps: 1) estimating the number of targets and their ranges by extending Barone’s method to handle data from multiple antennas and 2) estimating the angle of arrival of each target by a Least-Square algorithm optimization. The proposed algorithm has been evaluated through Monte-Carlo simulations and an indoor testbed. By comparing with baseline algorithms, including 2D-FFT and multiple signal classification (MUSIC), we find that the proposed algorithm has the best performance in high signal-to-noise ratio regimes.