Approximate multi-sensor multi-target joint probabilistic data association algorithm applicable to complex information fusion system

Liu Chengxia Wang Baoshu

Volume 25 Issue 10

Oct. 2003

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Article Navigation > Journal of Electronics & Information Technology > 2003 > 25(10): 1355-1360

Liu Chengxia Wang Baoshu. Approximate multi-sensor multi-target joint probabilistic data association algorithm applicable to complex information fusion system[J]. Journal of Electronics & Information Technology, 2003, 25(10): 1355-1360.

Citation:

Liu Chengxia Wang Baoshu. Approximate multi-sensor multi-target joint probabilistic data association algorithm applicable to complex information fusion system[J]. Journal of Electronics & Information Technology, 2003, 25(10): 1355-1360.

Citation:

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Approximate multi-sensor multi-target joint probabilistic data association algorithm applicable to complex information fusion system

Liu Chengxia Wang Baoshu

Received Date: 2002-03-18
Rev Recd Date: 2002-11-14
Publish Date: 2003-10-19

Abstract

Abstract

To reduce the incorrect association rate using NN (Nearest, Neighbor) algorithm in complex environment in clutter, a new plot-track association algorithm-Approximate Multi-Sensor multi-target Joint Probabilistic Data Association (AMSJPDA) is presented in the pa-per. It uses all the measurements in the tracking gate and every measurement has its own power, Added the measurements multiplied by their power the near optimal track estimation is achieved. AMSJPDA, based on the Approximate probabilistic Computing (AC) and Direct probabilistic Computing (DC) brought forward by B. Zhou, is the amelioration of MS JPDA and demands less time than MSJPDA. It meets the need of large scale plates and the real-time performance of data fusion system. At the end of the paper the comparison result of AMSJPDA and the NN is given.

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References(1)

References

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