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Proceedings Paper

Multi-Bernoulli filtering for initially unresolved targets in clutter
Author(s): Qin Lu; Karl Granström; Yaakov Bar-Shalom; Peter Willett
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Paper Abstract

Multiple target tracking (MTT) is a challenging task that aims to estimate the number of targets and their states in the presence of process noise, measurement noise and data association uncertainty. This paper considers a special MTT problem characterized by additional complexity. In this problem, multiple targets are launched simultaneously in nearby locations at the same speed with slightly different directions. As the distances be-tween the initial locations of these targets are smaller than the resolution of the sensor, this results in merged measurements, i.e., unresolved tracks at the very beginning. To deal with this problem, the recently proposed Multi-Bernoulli (MB) filter is applied. Using a model for the merged measurements, simulation results with 2-D Cartesian measurements in an optical sensor’s focal plane in the presence of clutter show that the initially unresolved tracks become resolved with MB filtering a few time steps after the measurements become resolved. Thus, the MB filter is capable of keeping track of the number of targets and their corresponding states when they are initially unresolved.

Paper Details

Date Published: 17 May 2016
PDF: 12 pages
Proc. SPIE 9842, Signal Processing, Sensor/Information Fusion, and Target Recognition XXV, 98421J (17 May 2016); doi: 10.1117/12.2229638
Show Author Affiliations
Qin Lu, Univ. of Connecticut (United States)
Karl Granström, Chalmers Univ. of Technology (Sweden)
Yaakov Bar-Shalom, Univ. of Connecticut (United States)
Peter Willett, Univ. of Connecticut (United States)


Published in SPIE Proceedings Vol. 9842:
Signal Processing, Sensor/Information Fusion, and Target Recognition XXV
Ivan Kadar, Editor(s)

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