Abstract: A new terrain matching neural network algorithm mode is constructed by means of multi-features fusion, which includes different statistical and geometrical features. By analyzing of the real terrain and the reference terrain, the connective weight function between different nodes is deduced, and the energy formula of the network system is structured. The matching position can be acquired by seeking the least system energy. As the algorithm can utilize different features sufficiently, it has higher matching precision, and also better robustness to noise and geometric distortion. The experimental results reveal that its performance is better than that of the conventional.

Key words: terrain matching, neural network, multitudinous features syncretize, the least energy