Multiple Extended Target Tracking with Labelled Random Finite Sets

Abstract

Targets that generate multiple measurements at a given instant in time are commonly known as extended targets. These present a challenge for many tracking algorithms, as they violate one of the key assumptions of the standard measurement model. In this paper, a new algorithm is proposed for tracking multiple extended targets in clutter, that is capable of estimating the number of targets, as well the trajectories of their states, comprising the kinematics, measurement rates and extents. The proposed technique is based on modelling the multi-target state as a generalised labelled multi-Bernoulli (GLMB) random finite set (RFS), within which the extended targets are modelled using gamma Gaussian inverse Wishart (GGIW) distributions. A cheaper variant of the algorithm is also proposed, based on the labelled multi-Bernoulli (LMB) filter. The proposed GLMB/LMB-based algorithms are compared with an extended target version of the cardinalised probability hypothesis density (CPHD) filter, and simulation results show that the (G)LMB has improved estimation and tracking performance.

arXiv comment13 pages, 10 figures, submitted to IEEE Transactions on Signal Processing

References in corpus (1)

• Labeled Random Finite Sets and the Bayes Multi-Target Tracking Filter

Cited by in corpus (13)

• Extended Object Tracking: Introduction, Overview and Applications
• Poisson multi-Bernoulli conjugate prior for multiple extended object filtering
• Scalable Detection and Tracking of Geometric Extended Objects
• A Poisson multi-Bernoulli mixture filter for coexisting point and extended targets
• Bayesian Smoothing for the Extended Object Random Matrix Model
• An Overview of Multi-Object Estimation via Labeled Random Finite Set
• Poisson multi-Bernoulli mixture filter with general target-generated measurements and arbitrary clutter
• Fast 3D Extended Target Tracking using NURBS Surfaces
• The Greedy Dirichlet Process Filter - An Online Clustering Multi-Target Tracker
• The Adaptive Labeled Multi-Bernoulli Filter
• Poisson Multi-Bernoulli Approximations for Multiple Extended Object Filtering
• Extended target Poisson multi-Bernoulli mixture trackers based on sets of trajectories
• An Improved Random Matrix Prediction Model for Manoeuvring Extended Targets