Experimental Evaluation of Adaptive Beamforming for Automotive Radar Interference Suppression

Abstract

Mutual interference between automotive radars can make it difficult to detect targets, especially the weaker ones, such as cyclists and pedestrians. In this paper, the interference suppression performance of a Least Mean Squares (LMS) algorithm-based adaptive beamformer is evaluated using measurements from a 77 GHz Frequency Modulated Continuous Wave (FMCW) radar in an outdoor environment. It is shown that the adaptive beamformer increases detection performance and that the interference is suppressed down to the noise floor of the radar in the Range-Doppler domain. In the paper, real baseband sampling and complex-baseband sampling (IQ) radar receivers are compared in the context of interference suppression. The measurements show that IQ receivers are more beneficial in the presence of interference.