Multi-sensor Target Tracking Using the Bernoulli Filter

DOI

10.2991/icmmita-15.2015.259How to use a DOI?

Keywords

Bernoulli filter; Multi-sensor; Sequential Monte Carlo.

Abstract

This paper proposes a novel multi-sensor Bernoulli filter (MSBF) based on the finite set statistics (FISST) for tracking a single target under the presence of detection uncertainty and clutter. The proposed algorithm is an extension of original Bernoulli filter in multi-sensor tracking. First, FISST is used to derive multi-sensor likelihood function of the MSBF, and then the sequential Monte Carlo (SMC) method is applied to implement the MSBF. Eventually, the simulation results are provided to demonstrate the effectiveness of the MSBF.

Copyright

© 2015, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Yong Qin
AU  - Hong Ma
AU  - Li Cheng
AU  - De Yu
AU  - Yang Li
AU  - Xueqin Zhou
PY  - 2015/11
DA  - 2015/11
TI  - Multi-sensor Target Tracking Using the Bernoulli Filter
BT  - Proceedings of the 2015 3rd International Conference on Machinery, Materials and Information Technology Applications
PB  - Atlantis Press
SP  - 1399
EP  - 1405
SN  - 2352-538X
UR  - https://doi.org/10.2991/icmmita-15.2015.259
DO  - 10.2991/icmmita-15.2015.259
ID  - Qin2015/11
ER  -