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Satellite clock error prediction method based on empirical mode decomposition (EMD) model and generalized autoregressive conditional heteroskedasticity (GARCH) model

A satellite clock error and clock error technology, applied in character and pattern recognition, instruments, computer parts, etc., can solve problems such as difficulty in improving forecast accuracy, and achieve improved clock error forecast accuracy, prediction accuracy, and pattern recognition difficulties. Effect

Inactive Publication Date: 2012-01-04
HARBIN INST OF TECH
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Problems solved by technology

[0005] The purpose of the present invention is to solve the problem that the existing satellite clock error prediction method is difficult to improve due to the lack of prediction of non-stationary random items, and to provide a satellite clock error prediction method based on EMD and GARCH model

Method used

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  • Satellite clock error prediction method based on empirical mode decomposition (EMD) model and generalized autoregressive conditional heteroskedasticity (GARCH) model
  • Satellite clock error prediction method based on empirical mode decomposition (EMD) model and generalized autoregressive conditional heteroskedasticity (GARCH) model
  • Satellite clock error prediction method based on empirical mode decomposition (EMD) model and generalized autoregressive conditional heteroskedasticity (GARCH) model

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specific Embodiment approach 1

[0017] Specific implementation mode 1: Combination figure 1 To describe this embodiment, this embodiment includes the following specific steps:

[0018] Step 1: Obtain historical clock error data, and perform data correction preprocessing to obtain satellite clock error data;

[0019] Step 2: Decompose the empirical mode of the satellite clock error data; use EMD to decompose the satellite clock error data into a series of eigenmode function and residual function components with different frequency components; the frequency of the eigenmode function has From high to low, after removing the high frequency part, the eigenmode function is summed to obtain the random term part of the satellite clock error data, and the trend term of the satellite clock error data is obtained through the residual function, and the residual function reflects the satellite The trend item part of the clock error data;

[0020] Step 3: Predict the trend item of the satellite clock error data. The trend of t...

specific Embodiment approach 2

[0022] Embodiment 2: If there are abnormal points, no data segments, or data abnormalities in the clock error history data acquired in step one of specific embodiment 1, the abnormalities are corrected, and for abnormal points, the abnormalities are deleted. Point, and then merge into no data section; for no data section, use polynomial interpolation method to get the data of no data section; for data jump, use sliding window to detect jump, for jump data, take the front-end data and use it Segment data is used to predict the clock error. The other composition and connection relationship are the same as in the first embodiment.

[0023] Step 2: Before the EMD analysis of the satellite clock error data, determine whether the following conditions are met at the same time: a. The analyzed data contains at least two extreme points, a maximum value and a minimum value; b. According to the two adjacent extreme points The time distance can define the characteristic time scale; c. If th...

specific Embodiment approach 3

[0025] Specific embodiment three: the sub-steps included in step two in specific embodiment one are as follows:

[0026] Substep 1. Obtain the maximum value y(t) from the satellite clock error data y(t) u ) And the minimum value y(t v ), where u = 1, 2,..., N u , V=1, 2,..., N v , N u Is the number of maxima, N v Is the number of minimum values; the upper and lower envelopes y of the maximum point and the minimum point are constructed using cubic spline function respectively u (t) and y v (t), calculate the mean of the two envelopes

[0027] m 1 = 1 2 ( y u ( t ) + y v ( t ) ) ; - - - ( 1 )

[0028] Sub-step 2, judge h 1 =y(t)-m 1 Whether the following two conditions are met at the same time as the IMF:

[0029] a. The number of data extreme points is equal to or one difference from the number of zero points;

[0030] b. The local mean of the upper envelope defined by the maximum value and the lower envelope defined b...

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Abstract

The invention provides a satellite clock error prediction method based on an empirical mode decomposition (EMD) model and a generalized autoregressive conditional heteroskedasticity (GARCH) model, relates to the field of clock error prediction of satellite clock, and solves the problem of difficulty in improving prediction precision because the traditional satellite clock error prediction method lacks prediction of an unstable random term. The method comprises the following steps of: 1, acquiring historical data of clock error, and correcting and pre-processing the data to obtain satellite clock error data; 2, decomposing an empirical mode of the satellite clock error data to obtain a random term part of the satellite clock error data; 3, predicting a trend term of the satellite clock error data, and building a Kalman prediction model to predict the trend term of the satellite clock error data; and 4, predicting a random term of the satellite clock error data, namely, removing the trend term to obtain the random term, predicting the random term by using an auto-regressive and moving average (ARMA) model and the GARCH model, and improving the precision of satellite clock error prediction. The method is used for high-precision time synchronization of a satellite navigation system.

Description

Technical field [0001] The invention relates to the field of satellite clock clock error prediction. Background technique [0002] Time synchronization is the foundation and key of a satellite navigation system. The final accuracy of time synchronization depends on the accuracy of satellite clock error prediction. That is, satellite clock error prediction is one of the largest sources of error. Therefore, satellite clock error prediction is the key to satellite navigation systems. One of the technologies. [0003] Clock error prediction is to use the current existing clock error observation data to obtain the clock error forecast value at a certain time in the future through a certain algorithm. The satellite clock error prediction method based on empirical mode decomposition (EMD) and generalized autoregressive conditional heteroscedasticity (GARCH) model is a high-precision and fast clock error prediction technology. This method uses EMD to decompose satellite clock error data i...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/62
Inventor 姜宇金晶张迎春
Owner HARBIN INST OF TECH
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