Super-Resolution Angle Estimation Algorithm using Low Complexity MUSIC-Based RELAX for MIMO FMCW Radar

Abstract

A novel super-resolution angle estimation algorithm using low complexity-multiple signal classification (LC-MUSIC)-based relaxation (RELAX) for multiple-input multiple-output (MIMO) frequency-modulated continuous-wave (FMCW) radar is proposed in this paper. FMCW radar is widely used to estimate target location information in various fields, including autonomous driving, defense, and robotics. However, FMCW radar struggles to provide high-resolution direction of arrival (DOA) data. To obtain precise target positions, especially for multiple targets, FMCW radar with high-resolution DOA capability is needed. Conventional FMCW radar employs MIMO-based technology to improve angular resolution because of its low complexity and ease of implementation, but MIMO-based radar still struggles to provide precise angular resolution. To improve the angle resolution, we propose a novel super-resolution DOA algorithm in a MIMO scheme. The new method consists of RELAX-based CLEAN and LC-MUSIC. Combining the MIMO technique with the new super-resolution algorithm enables FMCW radar with high angular resolution to be obtained. To analyze the performance of the proposed estimation, Monte Carlo simulations are performed, and root-mean-square error results are analyzed. Using the FMCW radar module, experiments comparing the proposed and conventional algorithms were performed in an indoor environment. This is an Open-Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited. © Copyright The Korean Institute of Electromagnetic Engineering and Science.