An improved target tracking information differentiating system using the neural network to substitute for fuzzy rules is presented for the infrared-radar dual-mode guidance system. Since the neural network training based on the expert knowledge database is conducted off-line, the benefits for developing real-time tracking capabilities can be obtained. The network outputs the confidence degree denoted by the weight value of target information in the data fusion center according to two input variables of the measurement noise covariance and the tracking filter covariance. Simulation results show that the improved system can differentiate the target tracking information from the seeker fast and accurately.
