Interference Mitigation for Automotive FMCW Radar With Tensor Decomposition

Abstract

With the surge of vehicles and transportation, sensing obstacles and warning drivers to avoid accidents have become a great concern in recent years. In the current roadworthy electromagnetic environment, the number of frequency modulated continuous wave (FMCW) millimeter-wave (MMW) automotive radars has exploded due to their unique advantages in environmental sensing. However, the frequency band of the automotive radars is limited from 77 to 81 GHz, hence the burgeoning of radars on the road is bound to cause mutual interference and jeopardize further target detection and parameter estimation. In this paper, two basic schemes are considered to mitigate mutual interference of automotive radars. First, we consider the sparse characteristics of the mutual interference in the two-dimensional (2-D) time domain and employ a sparse interference extraction (SIE) method to tackle the mutual interference. Next, we further consider the low-rank property of the useful echoes across multiple channels and propose a novel three-dimensional (3-D) tensor decomposition (TD) method to decompose the received signals into mutual interference and useful echoes. Several numerical simulations are fulfilled to test the robustness of the proposed TD method, especially for multiple input and multiple output (MIMO) systems under complex electromagnetic circumstances. Furthermore, more experiments are implemented to demonstrate its feasibility in practical applications in comparison to multiple state-of-the-art methods.