Multi-Bernoulli Filtering for Initially Unresolved Targets in Clutter
Paper in proceeding, 2016

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 between 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.

Unresolved Targets

Clutter

Multi-Bernoulli Filtering

Multiple Target Tracking

Author

Q. Lu

University of Connecticut

Karl Granström

Chalmers, Signals and Systems, Signal Processing and Biomedical Engineering

Y. Bar-Shalom

University of Connecticut

P. Willett

University of Connecticut

Proceedings of SPIE - The International Society for Optical Engineering

0277786X (ISSN) 1996756X (eISSN)

Vol. 9842 UNSP 98421J- 98421J
978-1-5106-0083-6 (ISBN)

Subject Categories

Computer Vision and Robotics (Autonomous Systems)

DOI

10.1117/12.2229638

ISBN

978-1-5106-0083-6

More information

Created

10/8/2017