Vehicle identification based on self-organizing artificial neural network

UGS (Unattended Ground System) has been proved to be effective in target real-defection, identification. This paper discusses data acquisition by seismic sensors and how to extract features from the seismic signal produced by a vehicle. ANN (artificial neural network) is a robust classifier in pattern recognition, especially the property of ART ANN self-learning is very suitable to target emergence in the battlefield, therefore this paper presents a method of target identification by ART ANN. A satisfactory experiment result is obtained after simulation.