As one of the key techniques for high-resolution remote sensing target recognition

feature selection focused on how to find the critical features in the feature set to represent the target. Generally

the classical methods for feature selection were as follows

principal component analysis

empirical method

etc. When using these classical methods

recognition accuracy was not guaranteed. In this paper

a new method was proposed

the main idea of which was to couple GA （Genetic Algorithm） and SVM （Support Vector Machine） for feature selection

and using recognition results to guide the revolution direction of GA. Meanwhile

to reduce the risk of premature convergence of the traditional GA

some modification had been made. The experi-ment demonstrated the effectiveness of the proposed method.