ESM/Radar Track Association Based on BP Neural Network
Pan Heng-huia · Modern Radar · 2009
Based on distributed data fusion,the problem of BP neural network based ESM/Radar track association is studied.As a result of greater sampling period difference between sensors in one fusion period,the generalization ability of the trained network becomes poor.The problem is solved by sampling again after the track curves are fit and the number of sample for training is increased.The association probability is reevaluated by calculating the Euclidean distance.The final association probability is obtained by calculating the weighted sum of the association probability from neural network and the reevaluated association probability.Simulations show that the modified algorithm can make a correct judgement for association problem.