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| Global Optimal Track Association Algorithm Based on Sequential Modified Grey Association Degree |
| Dong Kai Guan Xin Wang Hai-peng He You |
| Research Institute of Information Fusion, Naval Aeronautical and Astronautical University, Yantai 264001, China |
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Abstract Track association is a precondition of the distributed multi-sensor’s track fusion. Given the fact that the fusion center is not able to get the target states estimation covariance, a global optimal track association algorithm based on sequential modified grey association degree is proposed. The algorithm cancels the scope normalization, sequentially accumulates data array index absolute difference and modifies the grey association coefficient formulation to ensure exchangeability, thus yielding the sequential modified grey association degree between the sensors’ tracks. Then the global optimal track association is obtained by making the association degree as the global statistical vector. The simulation results show that the performance and robustness of the proposed algorithm is apparently better than the traditional algorithm under the condition of dense parallel formation, random cross targets and unshared observation in existence.
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Received: 24 September 2013
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Corresponding Authors:
Dong Kai
E-mail: 188dongkai@163.com
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2014, Vol. 36 
