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Document type:
Zeitschriftenaufsatz
Author(s):
Vogginger, Bernhard; Kreutz, Felix; López-Randulfe, Javier; Liu, Chen; Dietrich, Robin; Gonzalez, Hector A; Scholz, Daniel; Reeb, Nico; Auge, Daniel; Hille, Julian; Arsalan, Muhammad; Mirus, Florian; Grassmann, Cyprian; Knoll, Alois; Mayr, Christian
Title:
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 pe...    »
Keywords:
spiking neural networks, FMCW, radar processing, MIMO, automotive, neuromorphic computing, signal processing
Journal title:
Frontiers in Neuroscience
Year:
2022
Reviewed:
ja
Language:
en
Fulltext / DOI:
doi:10.3389/fnins.2022.851774
WWW:
https://www.frontiersin.org/articles/10.3389/fnins.2022.851774/full
Status:
Verlagsversion / published
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