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Joint Kinematic and Feature Tracking of Ships with Satellite Electronic Information

Published online by Cambridge University Press:  30 April 2018

Yong Liu ,
Libo Yao ,
Wei Xiong  and
Zhimin Zhou
Yong Liu*
Affiliation:
(School of Electronic Science and Engineering, National University of Defense Technology, Changsha, China)
Libo Yao
Affiliation:
(Institute of Information Fusion, Naval Aeronautical and Astronautically University, Yantai, China)
Wei Xiong
Affiliation:
(Institute of Information Fusion, Naval Aeronautical and Astronautically University, Yantai, China)
Zhimin Zhou
Affiliation:
(School of Electronic Science and Engineering, National University of Defense Technology, Changsha, China)
*
(E-mail: xhliuyong@sina.com)
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Abstract

To track multiple ships and estimate the feature parameters of multiple emitters on board using electronic intelligence satellites under clutter interference, a long and random revisit time, and other complex conditions, a novel tracking algorithm using both kinematic (position and velocity) and feature information based on an improved Multiple Hypothesis Tracking (MHT) approach is proposed in this paper. Firstly, the characteristics of multi-ship tracking with multiple emitters using satellite electronic information are analysed, and a new model of an emitter is built as an extended target in geographical coordinates. Secondly, a pre-processing of measurements is utilised via hierarchical clustering using the location and feature information of emitters. Thirdly, feature information is incorporated into the MHT framework using Jensen-Shannon divergence distance and fuzzy C-means clustering to calculate track scores. Finally, we present the prediction and update of target states, especially the update of feature parameters, to realise joint kinematic and feature tracking of ships. The results of the simulation show that the proposed method has much better tracking performance than the standard MHT algorithm.

Keywords

Satellite electronic informationMultiple hypothesis trackingExtended target trackingClustering
Type
Research Article
Information
The Journal of Navigation , Volume 71 , Issue 5 , September 2018 , pp. 1178 - 1194
Copyright
Copyright © The Royal Institute of Navigation 2018 

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