电光与控制, 2018, 25 (6): 110, 网络出版: 2018-08-21
PCA和GA-BP结合的地磁导航适配区选择方法
Geomagnetic Navigation Matching Area Selection Based on PCA and GA-BP Neural Network
地磁导航 特征参数 主成分分析 GA-BP神经网络 适配区选择 geomagnetic navigation characteristic parameter principal component analysis GA-BP neural network matching area selection
摘要
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。
Abstract
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 componentsPCA is used to analyze the geomagnetic characteristic parameters.Thenthe GA-BP neural network model is constructedand the correspondence between the geomagnetic characteristic parameters and matching performance is establishedso 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 areaand improve the positioning accuracy of geomagnetic navigation.
王晨阳. PCA和GA-BP结合的地磁导航适配区选择方法[J]. 电光与控制, 2018, 25(6): 110. WANG Chen-yang. Geomagnetic Navigation Matching Area Selection Based on PCA and GA-BP Neural Network[J]. Electronics Optics & Control, 2018, 25(6): 110.