The selection of suitable matching area of geomagnetic map is important for ensuring the positioning accuracy of geomagnetic navigation.This paper puts forward a method for the automatic recognition and classification of the suitable and unsuitable matching areas of geomagnetic background field based on Principal Component Analysis (PCA) and GA-BP neural network.To select independent characteristic parameters containing the main componentsPCA is used to analyze the geomagnetic characteristic parameters.Thenthe GA-BP neural network model is constructedand the correspondence between the geomagnetic characteristic parameters and matching performance is establishedso as to realize the recognition and classification of suitable and unsuitable matching areas.Simulation results show that this method can efficiently find out a more effective matching areaand improve the positioning accuracy of geomagnetic navigation.