Rectangular Extended Object Tracking with Box Particle Filter Using Dynamic Constraints

• Published in: DF&TT 2014 : IET Conference on Data Fusion & Target Tracking 2014 : Algorithms and Applications : 30 April 2014 p. 2.1
• Main Authors: Petrov, N, Mihaylova, L, Gning, A
• Format: Conference Proceeding
• Language: English
• Published: Stevenage, UK IET 2014; The Institution of Engineering & Technology
• Subjects: Filtering methods in signal processing; Signal processing theory; rectangular extended object tracking; data association problem; box PF approach; shape parameter estimation; particle filtering (numerical methods); object tracking; parameter estimation; sensor fusion; kinematic state estimation; box particle filter approach; dynamic calculated constraint
• DOI: 10.1049/cp.2014.0525
• ISBN: 9781849198639; 1849198632

Extended objects generate multiple measurements and are characterised with their size or volume. They require methods able to deal with the data association problem and at the same time to estimate both their kinematic states and shape parameters. This paper presents a solution to the extended object tracking for rectangular extended objects, with the Box Particle filter (Box PF) approach. The Box PF is implemented based on dynamically calculated constraints. Promising results are demonstrated.