A New Multi-sensor Particle CPHD Filtering Algorithm for Bearings-only Multi-target Tracking

DOI

10.2991/eee-19.2019.24How to use a DOI?

Keywords

CPHD filter, Bearings-only multi-target tracking, Particle filter, Multi-sensor

Abstract

Aiming at bearings-only multi-target tracking, a new multi-sensor particle CPHD filtering algorithm is proposed, which analyses the structure information of mixed linear/nonlinear state space models and combines particle filter and Kalman filter to predict and estimate the states of multiple targets to enhance the estimating performance of the PHD and cardinality distribution. The target state estimates are extracted by utilizing the kernel density estimation theory and mean-shift method. Simulation results are presented to demonstrate the improved performance of the proposed filtering algorithm.

Copyright

© 2019, 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  - Jun-gen Zhang
PY  - 2019/07
DA  - 2019/07
TI  - A New Multi-sensor Particle CPHD Filtering Algorithm for Bearings-only Multi-target Tracking
BT  - Proceedings of the 2nd International Conference on Electrical and Electronic Engineering (EEE 2019)
PB  - Atlantis Press
SP  - 141
EP  - 146
SN  - 2352-5401
UR  - https://doi.org/10.2991/eee-19.2019.24
DO  - 10.2991/eee-19.2019.24
ID  - Zhang2019/07
ER  -