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Aiming at the problems of traditional model navigation method, such as difficulty in establishing model and large data dimension, a method of nonlinear prediction based on wavelet neural network and directly solving the position and velocity error information after solving is proposed. The shackles prevent new errors from being introduced in the model establishment, and use multiple parallel networks to reduce the dimensionality of the data, greatly reducing the amount of calculation. The Kalman filter is used as a reference for simulation experiments. The results show that the proposed method can effectively improve the accuracy and real-time performance of the integrated navigation system, and provides a new feasible path for combined navigation filtering.