Matching suitability analysis for geomagnetic aided navigation based on an intelligent classification method

The problem of matching suitability for geomagnetic aided navigation is investigated from the viewpoint of pattern recognition in this article. In order to improve the classification accuracy of candidate matching areas, an intelligent classification method based on genetic algorithm and support vector machine is proposed. Firstly, the geomagnetic datasets and the factors influencing the classification performance of support vector machine are studied. Then support vector machine is employed as the classifier, and genetic algorithm is utilized for feature selection and support vector machine parameters optimization to improve the classification performance. Afterwards the multi-class support vector machine classifiers based on the one-against-one strategy are constructed for analyzing matching suitability. Experimental results show that the proposed method can greatly improve the classification accuracy of candidate matching areas, and moreover, the conclusions of this article can provide beneficial guidance for geomagnetic matching and route planning.