A joint tracking and classification algorithm with improved mutual feedback
Yunfei Guo, Huajie Chen, Dongliang Peng, Yuesong Lin, Anke Xue · 2010
For the joint tracking and classification (JTC) problem in FM-band passive air surveillance radar system, a particle filter approach with improved mutual feedback is presented. Delay and Doppler measurements are used to estimate dynamic state and recognize target class. The improved mutual feedback between tracker and classifier is realized by a classification probability dependent particle assignment technique, which utilizes feedback information completely and increases tracking performance of the higher probability target class. Simulation results show the efficiency of the proposed method.