Extended Target Tracking Using Polynomials With Applications to Road-Map Estimation, Report no. LiTH-ISY-R-2982

This paper presents an extended target tracking framework which uses polynomials in order to model extended objects in the scene of interest from imagery sensor data. State space models are proposed for the extended objects which enables the use of Kalman lters in tracking. Di erent methodologies of designing measurement equations are investigated. A general target tracking algorithm that utilizes a speci c data association method for the extended targets is presented. The overall algorithm must always use some form of prior information in order to detect and initialize extended tracks from the point tracks in the scene. This aspect of the problem is illustrated on a real life example of road-map estimation from automotive radar reports along with the results of the study.