A Poisson multi-Bernoulli mixture filter for coexisting point and extended targets
Artikel i vetenskaplig tidskrift, 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

Författare

Angel Garcia

University of Liverpool

Jason L. Williams

Commonwealth Scientific and Industrial Research Organisation (CSIRO)

Lennart Svensson

Chalmers, Elektroteknik, Signalbehandling och medicinsk teknik

Yuxuan Xia

Chalmers, Elektroteknik, Signalbehandling och medicinsk teknik

IEEE Transactions on Signal Processing

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

Vol. 69 2600-2610 9399297

Målföljning och djup maskininlärning för trajektorieskattning med tillämpning mot noggranna referenssystem

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

Ämneskategorier

Sannolikhetsteori och statistik

Reglerteknik

Signalbehandling

DOI

10.1109/TSP.2021.3072006

Mer information

Senast uppdaterat

2021-08-19