Geometric Sequence Decomposition-Based Interference Cancellation in Automotive Radar Systems

Abstract

Radar signals generated from other vehicles can act as interference to ego-vehicle, which degrades the inherent detection performance of radar. In this paper, we address an efficient solution to the interference problem in frequency-modulated continuous wave (FMCW)-based automotive radar systems, named geometric sequence decomposition based interference cancellation (GSD-IC). With the method of GSD-IC, we can decompose the received signal into different non-orthogonal superposed signals, which means the interference signal and the signal reflected from the desired target are separated. It is based on the facts that 1) each single sampled signal can be interpreted as a geometric sequence and 2) the useful physical features, such as the time delay and the Doppler frequency, are extracted after converting the superposition of these geometric sequences into several transformed matrices. Through this approach, we can achieve effective interference signal cancellation while minimizing the loss of meaningful target information. Moreover, the proposed method does not require the generation of specific radar waveforms, and can mitigate interference through signal processing even with existing waveforms. Numerical results show that our algorithm outperforms existing methods in various scenarios.