Automotive Radar Interference Mitigation Using Two-Stage Signal Decomposition Approach

Abstract

The mutual interference between automotive radar sensors is inevitable due to their increasing demand in automotive applications. To reliably estimate the target parameters, this interference needs to be detected and mitigated. This paper proposes a two-stage approach for suppressing the mutual interference between frequency modulated continuous wave (FMCW) radars. In the first stage, the signals corresponding to the strong interference components or targets are separated using the singular value decomposition (SVD) technique across the spatial domain. Following this, each separated signal at each receive channel is further decomposed into different frequency components using various mode decomposition techniques such as empirical mode decomposition (EMD), ensemble empirical mode decomposition (EEMD), and variational mode decomposition (VMD) methods. The performance comparison of these different mode decomposition approaches with our proposed idea is presented through a simulation and a real experiment.