Radar-based Environment Perception for Pre-Crash Safety Systems
type: CreativeWork
description: In this thesis, methods for radar-based environment perception from the vehicle safety point of view are presented. The proposed methods comprise advanced topics of radar-based target detection and tracking in dynamic pre-crash scenarios, as well as ghost object identification. The problem of a wandering dominant scatter point on the target surface and corresponding challenge for accurate target tracking in low-range configurations is considered. The proposed method presents a procedure to estimate target wheel positions and corresponding bulk velocities to serve as fixed scatter points on the target surface. Input to this method are raw radar data. The technique spatially resolves the micro-Doppler signals, generated by the rotating wheels of the target vehicle, to determine characteristic scatter points on the target surface. A micro-Doppler parameter is defined to quantify detections that are with high probability generated by the rotating target wheels. This group of detections is processed to estimate the wheel position and corresponding bulk velocities of the target, referred to as wheel hypotheses. The proposed method is evaluated in dynamic driving scenarios, where the driver performs an emergency evading action to avoid a collision. Subsequently, the detected wheel hypotheses serve as input to a developed tracking framework, which is used to estimate the target object static and dynamic states. Since the number of detected wheel hypotheses varies, a random-finite-set-based measurement model is used to incorporate multiple wheel hypotheses detected for one extended target object. The tracking performance is evaluated in critical evading scenarios using real vehicles as the target object. In addition, the thesis emphasized the problem of ghost object generation due to multipath propagation in pre-crash scenarios. Radar sensors, perceiving the immediate vehicle environment, show an elevated ghost object presence due to a higher probability illuminating potenti…
abstract: In this thesis, methods for radar-based environment perception from the vehicle safety point of view are presented. The proposed methods comprise advanced topics of radar-based target detection and tracking in dynamic pre-crash scenarios, as well as ghost object identification. The problem of a wandering dominant scatter point on the target surface and corresponding challenge for accurate target tracking in low-range configurations is considered. The proposed method presents a procedure to estimate target wheel positions and corresponding bulk velocities to serve as fixed scatter points on the target surface. Input to this method are raw radar data. The technique spatially resolves the micro-Doppler signals, generated by the rotating wheels of the target vehicle, to determine characteristic scatter points on the target surface. A micro-Doppler parameter is defined to quantify detections that are with high probability generated by the rotating target wheels. This group of detections is processed to estimate the wheel position and corresponding bulk velocities of the target, referred to as wheel hypotheses. The proposed method is evaluated in dynamic driving scenarios, where the driver performs an emergency evading action to avoid a collision. Subsequently, the detected wheel hypotheses serve as input to a developed tracking framework, which is used to estimate the target object static and dynamic states. Since the number of detected wheel hypotheses varies, a random-finite-set-based measurement model is used to incorporate multiple wheel hypotheses detected for one extended target object. The tracking performance is evaluated in critical evading scenarios using real vehicles as the target object. In addition, the thesis emphasized the problem of ghost object generation due to multipath propagation in pre-crash scenarios. Radar sensors, perceiving the immediate vehicle environment, show an elevated ghost object presence due to a higher probability illuminating potenti…
author: Kamann, Alexander
keywords: environment perception, digital signal processing, frequency modulated continous wave radar, fmcw, automotive safety
date published: 2020-11-24
date modified: 2026-07-24T03:56:21Z
provider: QUCOSA
publisher: Networked Digital Library of Theses and Dissertations
type: WebPage
source organization: Technische Universität Chemnitz