利用BP神经网络的动态精密单点定位故障诊断算法

Detection and Diagnosis of Failures with BP Neural Network in Dynamic Precise Point Positioning

  • 摘要: 针对动态精密单点定位中可能出现的观测信息故障,提出了基于两级神经网络的故障诊断算法。该算法首先采用一级神经网络在线修正Kalman滤波的动力学模型信息,然后基于二级神经网络自动对观测信息进行故障检测、定位和剔除。利用机载实测数据进行了实验,结果表明该方法能够正确地诊断观测信息中存在的故障,提高了诊断正确率。

     

    Abstract: We present an algorithm to detect and diagnose the fault with two classes neural networks for the fault in observations of dynamic precise point positioning occurs.At first,the first neural network training samples online is used to improve the reliability of dynamic model.The second neural network can automatically detect failures,position and delete the fault of observations,and the observations processed can further improve the contribution of dynamic model to the result of navigation.In the data of aircraft,the algorithm can detect the fault of observations,improve the percent of diagnosis and control the influences of the fault to the result of navigation.

     

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