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Geomagnetic matching algorithm based on the probabilistic neural network

机译:基于概率神经网络的地磁匹配算法

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摘要

In order to realize geomagnetism-aided navigation in the regions with insignificant geomagnetic characteristic, inspired by the pattern recognition idea, the geomagnetic matching problem was transformed into statistical pattern recognition and was analysed from the aspect of pattern recognition. A matching algorithm based on the probabilistic neural network (PNN) was proposed. The selection of training sample for the PNN, the relation between the parameter of the PNN, and the geomagnetic roughness were studied. Then a PNN was constructed for geomagnetic matching. Simulation results show that the proposed method can greatly improve the efficiency and achieve better performance than ordinary correlative matching algorithm. The accuracy of the 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,受模式识别思想的启发,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。提出了一种基于概率神经网络的匹配算法。研究了神经网络训练样本的选择,神经网络参数与地磁粗糙度之间的关系。然后构造了用于地磁匹配的PNN。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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