Wavelet neural network (WNN) is such a network that combines wavelet transform with conventional neural networks. It takes nonlinear wavelet bases as hidden nodes activation to replace nonlinear activation function in neural networks. A new maneuvering target tracking method based on WNN is proposed. The structure of multi-resolution WNN fitting for maneuvering target tracking is constructed. It does not need modeling and computing quantity doesn't increase with the number of target models. Simulation results show that the algorithm can track maneuvering target exactly, meanwhile, it has better tracking performance than BP neural networks.