Extended Target Tracking Using Polynomials With Applications to Road-Map Estimation

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Lundquist C., Orguner U., Gustafsson F.

IEEE TRANSACTIONS ON SIGNAL PROCESSING, vol.59, no.1, pp.15-26, 2011 (SCI-Expanded) identifier identifier

  • Publication Type: Article / Article
  • Volume: 59 Issue: 1
  • Publication Date: 2011
  • Doi Number: 10.1109/tsp.2010.2081983
  • Journal Name: IEEE TRANSACTIONS ON SIGNAL PROCESSING
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Page Numbers: pp.15-26
  • Keywords: Automotive radar, data association, EIV, errors in output, errors in variables, extended target tracking, parabola, polynomial, road map, TOTAL LEAST-SQUARES, ALGORITHM
  • Middle East Technical University Affiliated: No

Abstract

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 filters in tracking. Different methodologies of designing measurement equations are investigated. A general target tracking algorithm that utilizes a specific 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.