Fusion of Data from Multiple Automotive Radars for High-Resolution DoA Estimation

Conference paper (2022)

Authors

Anusha Ravish Suvarna NXP Semiconductors

Arie Koppelaar NXP Semiconductors

Feike Jansen NXP Semiconductors

J. Wang

Alexander Yarovoy

DOI: https://doi.org/10.1109/RadarConf2248738.2022.9764277

MIMO Distributed radar OMP Automotive radar Compressive Sensing (CS) FOCUSS Block sparsity BOMP Incoherent processing Ambiguity function Single snap-shot DoA estimation

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Published Date

2022

Language

English

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Abstract

High angular resolution is in high demand in automotive radar. To achieve a high azimuth resolution a large aperture antenna array is required. Although MIMO technique can be used to form larger virtual apertures, a large number of transmitter-receiver channels are needed, which is still technologically challenging and costly. To circumvent this problem, we propose a high-resolution Direction of Arrival (DoA) estimation by using multiple small radar sensors distributed on the fascia of the automobile. To exploit the diversity gain due to different target observation angles by different radars, a block Focal Under determined System Solver based approach is proposed to incoherently fuse the data from multiple small MIMO sensors. This method significantly improves the DoA estimation compared to single sensor, decreases probability of false alarm and increases probability of multiple target detection. Its performance is demonstrated through both numerical simulations and experimental results.

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