Abstract
Automotive radar is the commonly used sensor for autonomous driving and active safety. Modern automotive radars provide high spatial information on the host vehicle surroundings, and therefore, automotive radar targets appear as point clouds of radar detections. This work addresses the problem of discriminating between adjacent distributed targets using the distribution of radar detections in the range-azimuth domain. The proposed approach considers both the statistical information of the radar detections' distribution and the L-shape model of the target vehicles via the fuzzy L-shell clustering algorithm.
| Original language | English |
|---|---|
| Pages (from-to) | 1-13 |
| Number of pages | 13 |
| Journal | IEEE Transactions on Aerospace and Electronic Systems |
| DOIs | |
| State | Accepted/In press - 1 Jan 2024 |
Keywords
- Automotive engineering
- Automotive radar
- Distributed targets
- Fuzzy shell clustering
- Radar
- Radar detection
- Radar scattering
- Reliability
- Shape
- Target enumeration
- Targets discrimination
- Vectors
ASJC Scopus subject areas
- Aerospace Engineering
- Electrical and Electronic Engineering