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    Abstract
2014 (Vol. 7, Issue: 10)
Article Information:

An Improved Data Correlation Algorithm for Multi-passive-sensor Tracking System

Lijing Zhang, Yuxiao Song and Li Zhou
Corresponding Author:  Li Zhou 

Key words:  Combination rule of D-S evidence theory, data correlation, multi-tuple of measurement, the optimal assignment algorithm, , ,
Vol. 7 , (10): 2106-2111
Submitted Accepted Published
July 4, 2013 July 23, 2013 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.
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  Cite this Reference:
Lijing Zhang, Yuxiao Song and Li Zhou, 2014. An Improved Data Correlation Algorithm for Multi-passive-sensor Tracking System.  Research Journal of Applied Sciences, Engineering and Technology, 7(10): 2106-2111.
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ISSN (Online):  2040-7467
ISSN (Print):   2040-7459
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