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In this work, a new multisensor data fusion architecture integrating neural network and fuzzy logic techniques is introduced, which has the ability of fast adjusting acceleration parameter and covariance of measurement noise of sensors. In this architecture, the neural network estimates acceleration and fuzzy logic adapts the covariance of measurement noise on-line and also offers degree of confidence of sensors for fusion. The results of simulation show that this new architecture can adjust maneuver parameter in nearly one sample time and change the covariance of measurement noise effectively.

A hybrid neural network-fuzzy logic architecture for multisensor data fusion in target tracking system