Abstract: Based on the analysis of the echo from buried objects, a novel method of locating buried mines using pattern recognition is recommended. The process comprises pre-processing stage, feature-extraction stage, feature reduction and a neural network classification stage. A PNN neural network is employed to identify the objects by training it to recognize the features extracted from time domain and frequency domain, wavelet domain as well as Welch power spectral density estimation of signal segments reflected from various types of buried targets. The data concerning mines and some other objects which are like mines in shape and size are compared and tested with the network, and the results indicate that the neural network using multi-feature can improve mine detection greatly.

Key words: neural network, pattern recognition, ground penetrating radar, mine detection