A Survey of Automotive Radar Misalignment Detection Techniques
The integration of reliable and accurate sensors is critical to the performance and safety of autonomous vehicles in the automotive industry. Sensors like LiDAR, cameras, and radar are essential to ensure proper vehicle functioning and perception capabilities. Failure or misalignment of any of these sensors degrades system performance and poses significant safety risks. In particular, radar is suitable for applications such as adaptive cruise control, collision avoidance, and lane change assistance systems and plays a crucial role in autonomous vehicle systems. Misalignments in radar, vertical or horizontal, can lead to severe performance degradation in these applications. This survey paper comprehensively analyzes radar misalignment issues, reviewing detection techniques that address various types of offset. Through a comparative evaluation of existing methods, this work aims to identify current gaps and provide valuable information to researchers to improve the reliability and accuracy of radar systems in autonomous vehicles.
Authors
- Gyu Sang Choi (ORCID: https://orcid.org/0000-0002-0854-768X)
- Sheriff Murtala (ORCID: https://orcid.org/0000-0003-2695-2838)
- Danish Sharif
Institutions
- Yeungnam University (KR)
Publication Details
- Journal
- IEEE Access
- Published
- 2025-01-01
- DOI
- https://doi.org/10.1109/access.2025.3584454
- Primary Topic
- Engineering Applied Research
- Type
- article
- Field-Weighted Citation Impact
- 0.00