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Proceedings Paper

A GLMB filter for unified multitarget multisensor management
Author(s): Ronald Mahler
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Paper Abstract

The generalized labeled multi-Bernoulli (GLMB) filter of Vo and Vo is an exact closed-form solution of the multitarget Bayes' filter and is, therefore, provably Bayes-optimal. Its recent implementations are extremely fast, with computational order O(n2m) where n,m are the current numbers of tracks resp. measurements. This paper generalizes the GLMB filter to fully integrated multitarget tracking and sensor management, in which dynamically moving sensors can appear and disappear and in which the states of these sensors are estimated via measurements collected by internal actuator sensors.

Paper Details

Date Published: 7 May 2019
PDF: 12 pages
Proc. SPIE 11018, Signal Processing, Sensor/Information Fusion, and Target Recognition XXVIII, 110180D (7 May 2019); doi: 10.1117/12.2520129
Show Author Affiliations
Ronald Mahler, Random Sets LLC (United States)

Published in SPIE Proceedings Vol. 11018:
Signal Processing, Sensor/Information Fusion, and Target Recognition XXVIII
Ivan Kadar; Erik P. Blasch; Lynne L. Grewe, Editor(s)

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