Neural network data association with application to multiple-target tracking

Henry Leung

doi:10.1117/1.600661

1 March 1996 Neural network data association with application to multiple-target tracking

Henry Leung

Optical Engineering, Vol. 35, Issue 3, (March 1996). https://doi.org/10.1117/1.600661

Data association is the process of relating sensor measurements in a data fusion system. It can be structured in a basic framework very similar to that of the classic traveling salesman problem. The derivation of the energy function is presented, and the solution is based on a modified Hopfield network which uses the Runge–Kutta method and Aiyer’s network structure. The neural data association is then applied to the problem of multiple-target tracking (MTT). The proposed neural MTT system consists of a modified Hough transform track initiator, a Kalman filter state estimator and the Hopfield probabilistic data association. Real-life air surveillance data are used to evaluate the practicality of the neural MTT system, and the results show that the neural system works efficiently in real-life tracking environments.

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Henry Leung "Neural network data association with application to multiple-target tracking," Optical Engineering 35(3), (1 March 1996). https://doi.org/10.1117/1.600661

Published: 1 March 1996

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