Low-rank approximation for FMCW automotive radar

For making car driving a much safer experience, various forms of radar systems and other object detection systems are being installed. In this paper we consider frequency-modulated continuous-wave (FMCW) automotive radar systems which collect information in so-called Range-Doppler (RD) matrices. The large amount of data collected will soon overwhelm the capacity of automotive data interfaces, and efficient data representation, and compression schemes become increasingly important for the automotive industry. To this end we propose low-rank approximation of RD matrices provided by truncated singular value decomposition. We analytically and numerically investigate error estimates for our approach. We demonstrate that low-rank approximations of RD matrices with a compression factor of over twenty still capture all essential information contained in the original RD matrix.