Multi-Target Location and Doppler Estimation in Multistatic Automotive Radar Applications
Ali Moussa, Wei Liu, Yimin D. Zhang, Maria Greco
Abstract
In this paper, we develop a multistatic automotive radar scheme for enhanced localization and Doppler estimation of multiple targets exploiting cooperative roadside sensors. As the range between a target and a sensing vehicle cannot be directly measured, intermediate calculations are required to convert the measured bistatic range to the radial range of the targets of interest. Using the Fourier transform, the range resolution is thereby limited by the Rayleigh criterion applied to the total bistatic range. Developing a sparse representation for the bistatic automotive scenario can not only bypass the intermediate calculation step, but also add super-resolution sensing capability beyond the Rayleigh limit. As this application can benefit from the communication capabilities of the fifth-generation (5G) new radio (NR), multiple cooperative roadside transmitters are employed along a smart highway, forming a multistatic configuration. In order to process multiple realisations of the reflected signals simultaneously, we propose a solution employing the concept of group sparsity. Then, we show through computer simulations that, for some added complexity, better positioning performance can be achieved when compared to the state-of-art.