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摘要
In this work, an adaptive neural-fuzzy-based multi-sensor data fusion (ANF-MDF) architecture for target tracking systems is presented. In this architecture, neural networks are employed to detect and estimate target manoeuvres, and adaptive-network-based fuzzy inference systems (ANFIS) are used to adjust the measurement noise covariance matrices. They are combined as an adaptive mechanism to cooperate with Kalman filters to process measurements from multiple sensors, whose outputs are fused by a specific neural network to obtain optimal results. The results of simulations demonstrate this architecture can adjust system parameters and respond quickly to avoid mistracking effectively.
