PreprintarXiv licencearXiv
Multi-Target Tracking of Cooperating Swarms by an Ensemble Gaussian Mixture Filter
Abstract
Per-target labeled random-finite-set filters, such as the state of the art δ-generalized labeled multi-Bernoulli filter, cannot represent cooperating, swarm-like, motion between targets. In this work, we present a new filter that can. The new particle filter couples the joint particle filter with ensemble Gaussian mixture filter such that a measurement updates the density at every particle instead of merely reweighting. We prove that the new particle filter converges to the joint particle filter in the limit of particle number and thus to the true Bayesian posterior, under certain assumptions. Experimental results on two coupled systems, the Vicsek model and coupled Brownian motion provide evidence on the efficacy of the filter.
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BibTeX
@misc{jabbar2026multitarget,
title = {{Multi-Target Tracking of Cooperating Swarms by an Ensemble Gaussian Mixture Filter}},
author = {Zain Jabbar and Andrey A. Popov},
howpublished = {arXiv},
year = {2026},
month = oct,
doi = {10.48550/arxiv.2610.04127},
eprint = {2610.04127},
archivePrefix = {arXiv},
url = {https://arxiv.org/abs/2610.04127},
}
RIS
TY - UNPB
TI - Multi-Target Tracking of Cooperating Swarms by an Ensemble Gaussian Mixture Filter
AU - Zain Jabbar
AU - Andrey A. Popov
PY - 2026
DA - 2026/10/02
PB - arXiv
DO - 10.48550/arxiv.2610.04127
UR - https://arxiv.org/abs/2610.04127
AB - Per-target labeled random-finite-set filters, such as the state of the art δ-generalized labeled multi-Bernoulli filter, cannot represent cooperating, swarm-like, motion between targets. In this work, we present a new filter that can. The new particle filter couples the joint particle filter with ensemble Gaussian mixture filter such that a measurement updates the density at every particle instead of merely reweighting. We prove that the new particle filter converges to the joint particle filter in the limit of particle number and thus to the true Bayesian posterior, under certain assumptions. Experimental results on two coupled systems, the Vicsek model and coupled Brownian motion provide evidence on the efficacy of the filter.
ER -