Artificial neural networks for calculating the association probabilities in multi-target tracking


Turkmen I., Guney K.

IEE PROCEEDINGS-RADAR SONAR AND NAVIGATION, vol.151, no.4, pp.181-188, 2004 (SCI-Expanded) identifier identifier

Abstract

A simple method based on the multilayered perceptron neural network architecture for calculating the association probabilities used in target tracking is presented. The multilayered perceptron is trained with the Levenberg-Marquardt algorithm. The tracks estimated by using the proposed method for multiple targets in cluttered and non-cluttered environments are in good agreement with the original tracks. Better accuracy is obtained than when using the joint probabilistic data association filter or the cheap joint probabilistic data association filter methods.