A Poisson multi-Bernoulli mixture filter for coexisting point and extended targets
Journal article, 2021

This paper proposes a Poisson multi-Bernoulli mixture (PMBM) filter for coexisting point and extended targets, i.e., for scenarios where there may be simultaneous point and extended targets. The PMBM filter provides a recursion to compute the multi-target filtering posterior based on probabilistic information on data associations, and single-target predictions and updates. In this paper, we first derive the PMBM filter update for a generalised measurement model, which can include measurements originated from point and extended targets. Second, we propose a single-target space that accommodates both point and extended targets and derive the filtering recursion that propagates Gaussian densities for single targets and gamma Gaussian inverse Wishart densities for extended targets. As a computationally efficient approximation of the PMBM filter, we also develop a Poisson multi-Bernoulli (PMB) filter for coexisting point and extended targets. The resulting filters are analysed via numerical simulations.

point targets

Multiple target filtering

extended targets

Author

Angel Garcia

University of Liverpool

Jason L. Williams

Commonwealth Scientific and Industrial Research Organisation (CSIRO)

Lennart Svensson

Chalmers, Electrical Engineering, Signal Processing and Biomedical Engineering

Yuxuan Xia

Chalmers, Electrical Engineering, Signal Processing and Biomedical Engineering

IEEE Transactions on Signal Processing

1053-587X (ISSN) 1941-0476 (eISSN)

Vol. 69 2600-2610 9399297

Deep multi-object tracking for ground truth trajectory estimation

VINNOVA (2017-05521), 2018-07-01 -- 2022-06-30.

Subject Categories

Probability Theory and Statistics

Control Engineering

Signal Processing

DOI

10.1109/TSP.2021.3072006

More information

Latest update

8/19/2021