基于一致关联数最大化的航迹关联算法

doi:10.7527/S1000-6893.2014.0179

Abstract

Abstract:

Track-to-track association (TTTA) is a fundamental problem in the multi-sensor data fusion system. It is the precondition for sensor bias estimation and track-to-track fusion. The inherent systematic biases of sensors may cause the position estimates of a target to deviate far from the real target state. TTTA algorithms based upon the global minimum distance criteria require accurate sensor bias estimate to register the sensors. For TTTA problem in the presence of sensor biases, we define a new concept of consistent association number on the basis of indirect evaluation upon the association matrix, propose the criteria of maximal consistent association number, and develop a new TTTA algorithm in the framework of robust alternate iteration. Compared with the distance function, the consistent association number, which is a discrete variable, can relax the high precision requirement for sensor bias estimation. Simulation results demonstrate the effectiveness of the proposed algorithm.

Key words: multi-sensor data fusion, track-to-track association, system bias, global minimum distance, misassociation, consistent association number

CLC Number:

V243.2
TN957

TIAN Wei, WANG Yue, SHAN Xiuming, YANG Jian. A Track-to-track Association Algorithm Based on Maximizing the Consistent Association Number[J]. ACTA AERONAUTICAET ASTRONAUTICA SINICA, 2014, 35(11): 3115-3122.

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A Track-to-track Association Algorithm Based on Maximizing the Consistent Association Number

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