Research Article | OPEN ACCESS
An Improved Data Correlation Algorithm for Multi-passive-sensor Tracking System
Lijing Zhang, Yuxiao Song and Li Zhou
School of Information and Electrical Engineering, Ludong University, Yantai 264025, China
Research Journal of Applied Sciences, Engineering and Technology 2014 10:2106-2111
Received: July 4, 2013 | Accepted: July 23, 2013 | Published: March 15, 2014
Abstract
For improving the performance of the optimal assignment problem of data correlation of multi-passive-sensor system, an improved optimal assignment algorithm based on multi-source information fusion is put forward. The new algorithm takes advantage of the optimal solution and a certain number of near-optimal solutions of the traditional optimal assignment problem to construct a set of effective multi-tuple of measurement and constructs correlation probability fusing multi-source information between above effective multi-tuple of measurement and target track by using combination rule of D-S evidence theory. The result of simulation experiments shows that, compared with the traditional optimal assignment algorithm, the new algorithm not only improves the accuracy of multi-target tracking in different degrees but also saves a lot of time. So it is an effective data correlation algorithm for multi-passive-sensor system.
Keywords:
Combination rule of D-S evidence theory, data correlation, multi-tuple of measurement, the optimal assignment algorithm,
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Competing interests
The authors have no competing interests.
Open Access Policy
This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.
Copyright
The authors have no competing interests.
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ISSN (Online): 2040-7467
ISSN (Print): 2040-7459 |
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