Position and Velocity Fusion Using Multiple Monostatic Radar Sensors for Automotive Applications
Schüßler C, Hoffmann M, Ebelt R, Weber I, Vossiek M (2021)
Publication Type: Conference contribution, Original article
Publication year: 2021
Original Authors: Christian Schusler, Marcel Hoffmann, Randolf Ebelt, Ingo Weber, Martin Vossiek
Event location: Atlanta, GA
ISBN: 9781728176093
DOI: 10.1109/RadarConf2147009.2021.9455309
Abstract
In order to protect vulnerable road users (VRU), it is essential to detect and track them reliably and to predict their direction of motion i.e., their velocity vector relative to a vehicle's driving direction. A fusion approach for monostatic radar sensors, which computes target positions and the assigned two-dimensional instantaneous velocities, is proposed to realize these functionalities. These fused detections are used to cluster extended objects. Afterwards their position, velocity, and covariance matrices are estimated. A converted measurement Kalman filter is utilized to track these detected objects. Both velocity and position can be very accurately measured with the proposed fusion algorithm. Tracking by two separated radar stations greatly outperforms a single sensor setup, as verified by test data.
Authors with CRIS profile
Christian Schüßler
Lehrstuhl für Hochfrequenztechnik (LHFT)
Marcel Hoffmann
Lehrstuhl für Hochfrequenztechnik (LHFT)
Martin Vossiek
Lehrstuhl für Hochfrequenztechnik (LHFT)
Additional Organisation(s)
Involved external institutions
Germany (DE)How to cite
APA:
Schüßler, C., Hoffmann, M., Ebelt, R., Weber, I., & Vossiek, M. (2021). Position and Velocity Fusion Using Multiple Monostatic Radar Sensors for Automotive Applications. In Proceedings of the 2021 IEEE Radar Conference (RadarConf21). Atlanta, GA, US.
MLA:
Schüßler, Christian, et al. "Position and Velocity Fusion Using Multiple Monostatic Radar Sensors for Automotive Applications." Proceedings of the 2021 IEEE Radar Conference (RadarConf21), Atlanta, GA 2021.
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