由于地磁图适配区的选择是影响地磁导航定位精度的重要因素，因此提出一种基于主成分分析法（PCA）和GA-BP神经网络相结合的地磁背景场适配/非适配区自动识别和分类的方法。首先利用PCA对地磁特征参数进行分析，选择出独立的、并且包含主成分的特征参量，其次构建GA-BP神经网络模型，建立地磁特征参数和匹配性能的对应关系，从而实现适配/非适配区的划分。通过多次仿真试验，证明了采用该方法能够选择出较好的适配区域，提高地磁导航定位精度。

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.