Automotive Radar Processing With Spiking Neural Networks: Concepts and Challenges.

ABSTRACT: Frequency-modulated continuous wave radar sensors play an essential role for assisted and autonomous driving as they are robust under all weather and light conditions. However, the rising number of transmitters and receivers for obtaining a higher angular resolution increases the cost for digital signal processing. One promising approach for energy-efficient signal processing is the usage of brain-inspired spiking neural networks (SNNs) implemented on neuromorphic hardware. In this article we perform a step-by-step analysis of automotive radar processing and argue how spiking neural networks could replace or complement the conventional processing. We provide SNN examples for two processing steps and evaluate their accuracy and computational efficiency. For radar target detection, an SNN wi

SUBMITTER: Vogginger B 

PROVIDER: S-EPMC9012531 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature