This paper focuses on the development and use of a nonlinear observer for tracking of vehicle motion trajectories while using a radar sensor. Previous results on vehicle tracking have typically used an interacting multiple model filter that needs different models for different modes of vehicle motion. This paper uses a single nonlinear vehicle model that can be used for all modes of vehicle motion. Previous nonlinear observer design results from the literature do not work for the nonlinear system under consideration due to the wide range of operating conditions that need to be accommodated. Hence, a new nonlinear observer design technique that utilizes better bounds on the coupled nonlinear functions in the dynamics is developed. The exponential stability of the observer is established using Lyapunov techniques. The observer design with the developed technique is then implemented in both simulations and experiments. Experimental results show that the observer can simultaneously and accurately estimate longitudinal position, lateral position, and velocity and orientation variables for the vehicle from radar measurements. Results are presented both for tracking of vehicle maneuvers on highways and of maneuvers on urban roads at traffic intersections where turns and significant changes in vehicle orientation can occur.
Bibliographical noteFunding Information:
Manuscript received June 11, 2018; revised October 9, 2018; accepted December 31, 2018. Date of publication January 11, 2019; date of current version April 16, 2019. Recommended by Technical Editor X. Jing. This work was supported in part by a research grant from the National Science Foundation under NSF Grant PFI-1631133. (Corresponding author: Rajesh Rajamani.) W. Jeon and R. Rajamani are with the Department of Mechanical Engineering, University of Minnesota, Minneapolis, MN 55455 USA (e-mail:,firstname.lastname@example.org; email@example.com).
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- Nonlinear observer
- vehicle motion estimation
- vehicle tracking