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首页> 外文会议>IEEE Joint International Information Technology and Artificial Intelligence Conference >A Technique of Clock Difference Prediction and Interpolation Based on Dynamic Grey Model and Power Function Transformation for Pseudo-satellite Clock Systems
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A Technique of Clock Difference Prediction and Interpolation Based on Dynamic Grey Model and Power Function Transformation for Pseudo-satellite Clock Systems

机译：一种基于动态灰色模型和伪卫星时钟系统功率函数变换的时钟差预测和插值技术

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摘要

In order to meet the need of clock synchronization of the pseudo-satellite system, a technique of high precision pseudo-satellite clock difference prediction and interpolation is proposed to realize real-time tracking and adjustment of the system clock in this paper. At first, based on the conventional gray prediction Model GM (1, 1), by combined with the characteristics of the Gray Dynamic prediction Model(DGM) and Power Function Transformation (PFT), a novel pseudo-satellite clock difference prediction model(PFT-DGM) is established. The power function transformation method is used to transform and preprocess the initial observation data to improve the smoothness of the observation data, while the dynamic gray model is to constantly remove the early information and add new information, so as to improve the whiteness of the prediction interval and improve the prediction accuracy significantly. Then the piecewise linear interpolation for the predicted clock difference is carried out, and the clock difference values at other times are obtained by interpolation. The research results show that this technique has a significant improvement in the accuracy of clock difference prediction, which compared with the other similar methods, and can meet the demand of real-time tracking and adjustment of the system clock. So it has practical reference value for clock synchronization of the pseudo-satellite systems.
机译：为了满足伪卫星系统的时钟同步的需要，提出了一种高精度伪卫星时钟差预测和插值的技术，以实现本文的实时跟踪和调整系统时钟。首先，基于传统的灰色预测模型GM（1,1），通过结合灰度动态预测模型（DGM）和功率函数变换（PFT）的特性，是一种新型伪卫星时钟差预测模型（PFT -DGM）成立。功率函数转换方法用于转换和预处理初始观测数据以提高观察数据的平滑度，而动态灰色模型是不断地删除早期信息并添加新信息，以提高预测的白度间隔并显着提高预测精度。然后执行预测时钟差的分段线性插值，并且通过插值获得其他时间的时钟差值。研究结果表明，该技术对时钟差预测的精度具有显着提高，与其他类似方法相比，可以满足系统时钟的实时跟踪和调整的需求。因此，它具有伪卫星系统时钟同步的实用参考值。

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