Track to track fusion based on NFE model
Taifan Quan, Mei Liu, Shuang Fang · 2004
Due to the bad performance of the common method for track to track fusion under complicated disturbing environment and radar netting dynamically, an algorithm for track to track fusion based on NFE model (neural network-fuzzy reasoning-expert system) is proposed. By making good use of the self-learning, self-reasoning ability and robustness of fuzzy neural network and expert system, this approach can adapt to the changes of the system environment and find the optimal algorithm. Simulation results show that this algorithm can still get results with high precision even under various complicated conditions such as sensors' reliabilities being low, a large amount of outliers existing in the whole measurement data set, sensors broken down or destroyed, radars netting over again, and so on.