According to the characteristics of gas signals

the effectiveness of battlefield targets classification and identification used by neural network is explored. A system of gas test and analysis for typical battlefield targets is set up. BP algorithm is adopted to deal with the on base of the characteristic regulation of targets and the analysis of BP algorithm target recognition under undefined background in battlefield. The ability of detecting signal will be improved effectively. It is demonstrated that the modified BP algorithm has higher correct identification rates for gas signals of battlefield targets according to signal sample experiments of typical targets

and the neural network classifier is suitable for the classification of battlefield targets.