Signal Processing Challenges in Automotive Radar
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.
Authors
- Rajesh Narasimha
- Shunqiao Sun (ORCID: https://orcid.org/0000-0002-9975-1415)
- Sandeep Rao (ORCID: https://orcid.org/0000-0001-8793-6298)
Institutions
- University of Alabama (US)
- Texas Instruments (India) (IN)
- Texas Instruments (United States) (US)
Publication Details
- Published
- 2025-03-12
- DOI
- https://doi.org/10.1109/icassp49660.2025.10889506
- Citations
- 2
- Primary Topic
- Radar Systems and Signal Processing
- Type
- article
- Field-Weighted Citation Impact
- 9.99
Funders
- National Science Foundation