Work

Signal Processing Challenges in Automotive Radar

Year: 2025

Type: conference-paper

Abstract: 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.

Source: IEEE International Conference on Acoustics Speech and Signal Processing

DOI: 10.1109/icassp49660.2025.10889506

Authors: Sandeep Rao, Rajan Narasimha, Shunqiao Sun

Institutions: Texas Instruments (India), Texas Instruments (United States), University of Alabama

Language: English

Topic: Radar Systems and Signal Processing

Subfield: Aerospace Engineering

Field: Engineering

Domain: Physical Sciences

Open Access status: green

Funder: National Science Foundation

Awards: CRII: CIF: A Sparse Framework Based Automotive Radar Sensing for Autonomous Vehicles, CAREER: Towards Fundamentals of Adaptive, Collaborative and Intelligent Radar Sensing and Perception