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Geomagnetic matching algorithm based on support vector machine

机译:基于支持向量机的地磁匹配算法

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In order to realize geomagnetism aided navigation (GAN) in the regions with insignificant geomagnetic characteristic, inspired by the pattern recognition idea, the geomagnetic matching (GM) problem was transformed into statistical pattern recognition and was analyzed from the aspect of pattern recognition. A matching algorithm based on support vector machine (SVM) was proposed. The selection of training sample for SVM, the relation between the parameter of the SVM and the geomagnetic roughness were studied. Then a SVM was constructed for GM. Simulation results show that the proposed method can greatly improve the efficiency and achieve better performance than ordinary correlative matching algorithm. The accuracy of matching method is less than the unit cell size of the geomagnetic map.
机译:为了在地磁特征不明显的地区实现地磁辅助导航,在模式识别思想的启发下,将地磁匹配问题转化为统计模式识别,并从模式识别的角度进行了分析。提出了一种基于支持向量机的匹配算法。研究了支持向量机训练样本的选择,支持向量机参数与地磁粗糙度之间的关系。然后为GM构建了一个SVM。仿真结果表明,与普通的相关匹配算法相比,该方法可以大大提高效率,并获得更好的性能。匹配方法的精度小于地磁图的像元大小。

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