Signal Processing Challenges in Automotive Radar

Fuente: arXiv
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Autores principales: Rao, Sandeep, Narasimha, Rajan, Sun, Shunqiao
Formato: Preprint
Publicado: 2025
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author Rao, Sandeep
Narasimha, Rajan
Sun, Shunqiao
author_facet Rao, Sandeep
Narasimha, Rajan
Sun, Shunqiao
contents As automotive radars continue to proliferate, there is a continuous need for improved performance and several critical problems that need to be solved. All of this is driving research across industry and academia. This paper is an overview of research areas that are centered around signal processing. We discuss opportunities in the area of modulation schemes, interference avoidance, spatial resolution enhancement and application of deep learning. A rich list of references is provided. This paper should serve as a useful starting point for signal processing practitioners looking to work in the area of automotive radars.
format Preprint
id arxiv_https___arxiv_org_abs_2501_07649
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Signal Processing Challenges in Automotive Radar
Rao, Sandeep
Narasimha, Rajan
Sun, Shunqiao
Signal Processing
As automotive radars continue to proliferate, there is a continuous need for improved performance and several critical problems that need to be solved. All of this is driving research across industry and academia. This paper is an overview of research areas that are centered around signal processing. We discuss opportunities in the area of modulation schemes, interference avoidance, spatial resolution enhancement and application of deep learning. A rich list of references is provided. This paper should serve as a useful starting point for signal processing practitioners looking to work in the area of automotive radars.
title Signal Processing Challenges in Automotive Radar
topic Signal Processing
url https://arxiv.org/abs/2501.07649