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Method for determining Kalman filtering state error covariance matrix in ionospheric modeling

A technology of error covariance and determination method, applied in electrical digital data processing, special data processing applications, instruments, etc., can solve the problems of filtering divergence, filtering can not obtain high precision

Active Publication Date: 2019-12-06
XIAN UNIV OF SCI & TECH
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Problems solved by technology

The accurate determination of Q is the key to obtaining accurate results by filtering. If it cannot be given accurately, the filtering cannot obtain high-precision results, and even filtering divergence may occur.

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  • Method for determining Kalman filtering state error covariance matrix in ionospheric modeling
  • Method for determining Kalman filtering state error covariance matrix in ionospheric modeling
  • Method for determining Kalman filtering state error covariance matrix in ionospheric modeling

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Embodiment Construction

[0037] Taking the ionospheric spherical harmonic coefficients at 1-hour intervals in 2018 as an example, the calculation process of the Kalman filter state error covariance matrix in ionospheric modeling is illustrated in the following with a detailed description.

[0038] like Figure 5 As shown, a method for determining the Kalman filter state error covariance matrix in ionospheric modeling includes the following steps:

[0039] (1) For each ionospheric spherical harmonic coefficient C i Perform an inter-epoch difference, i.e. dC i (k)=C i (k+1)-C i (k), i is the serial number of the ionospheric spherical harmonic coefficient (i=1,2,...,256), dC i (k) represents the difference between epochs, and k represents the epoch. like figure 1 As shown, the first ionospheric spherical harmonic coefficient C in 2018 is given 00 time series, it can be seen that C 00 There are obvious cyclical changes within a year.

[0040] (2) Assuming that the ionospheric spherical harmonic c...

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Abstract

The invention discloses a method for determining a Kalman filtering state error covariance matrix in ionospheric modeling. The method comprises the following steps: performing epoch difference on eachionospheric spherical harmonic coefficient Ci; calculating the change rate of the spherical harmonic coefficient of the ionized layer in the Kalman filtering epoch interval; calculating the standarddeviation of the ionized layer spherical harmonic coefficient change rate vCi (k) sequence; and obtaining a Kalman filtering state error covariance matrix Q in ionospheric modeling, wherein Q is a diagonal matrix, and diagonal elements are squares of three times of the standard deviation of the spherical harmonic coefficient change rate vCi (k) of each ionospheric modeling. The method provided bythe invention is different from an existing pure experience determination method, calculates Q according to the spherical harmonic coefficient of the ionized layer, and can accurately give the variance of each element in the spherical harmonic coefficient of the ionized layer.

Description

technical field [0001] The invention belongs to the field of ionospheric modeling, and relates to a method for determining a state error covariance matrix, in particular to a method for determining a Kalman filter state error covariance matrix Q in ionospheric modeling. Background technique [0002] Real-time ionospheric modeling is a hot spot in the current international ionospheric research field. It not only plays a major role in navigation and positioning, but can significantly improve the positioning accuracy of single-frequency real-time single-point positioning users. It is also of great significance in the field of scientific research. Real-time access to global ionospheric Layer information, and then real-time monitoring and research of abnormal changes in the ionosphere, can make predictions and early warnings of major natural disasters such as tsunamis and earthquakes. [0003] At present, the assumption of a single-layer ionosphere is widely used in global ionosp...

Claims

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Application Information

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IPC IPC(8): G06F17/50
CPCY02A90/10
Inventor 陈鹏李政刘航马永超郑乃铨刘丽霞
Owner XIAN UNIV OF SCI & TECH