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An Adaptive Difference Estimation Method for Geodetic Non-equidistant Time Series Noise

An adaptive difference and geodetic technology, which is applied in the field of adaptive difference estimation of distance time series noise, can solve the problems of time series random characteristics change, data loss, and destruction of original time series random characteristics, etc.

Active Publication Date: 2021-07-30
CHINA UNIV OF MINING & TECH
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

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Problems solved by technology

In the above research, due to the certain pollution in the observations, it is necessary to eliminate gross errors, resulting in missing data, and changing the time series of observations from equal interval time series to non-equal interval time series. Interpolation, which may cause changes in the random properties of the time series
[0004] In addition, the conventional difference method has the following shortcomings: 1. It cannot deal with non-equidistant time series, and it must be filled by interpolation method first, but the interpolation algorithm may destroy the random characteristics of the original time series; 2. The order of the time basis function and the difference operator The length is a fixed relationship, and the difference operator is not adaptive; 3. The determination of the difference operator does not use the optimal estimation criterion, and the optimality cannot be guaranteed

Method used

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  • An Adaptive Difference Estimation Method for Geodetic Non-equidistant Time Series Noise
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  • An Adaptive Difference Estimation Method for Geodetic Non-equidistant Time Series Noise

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Experimental program
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Embodiment 1

[0070] Embodiment 1: collect the observation value file (GPS satellite PRN number 1~31) of the GNSS certain station of 320 years in 2015, its time sampling rate is 10s, therefrom extract P1 code and P2 code observation value, according to the following method Obtain P1 and P2 coding error estimation results respectively. The noise estimation steps of GNSS observation time series are as follows:

[0071] (1) Download the observation value file (O file) from the CDDIS (ftp: / / cddis.gsfc.nasa.gov / ) data center, or the GNSS observation value file collected by the user, and read the pseudorange observation value in the observation value file P and phase observations L:

[0072]

[0073] Among them, ρ represents the geometric distance from the station to the satellite, c represents the speed of light, dt and dT represent the clock error of the receiver and the satellite clock respectively, and d ion 、d trop is the ionospheric delay and tropospheric delay error, λ is the wavelen...

Embodiment 2

[0089] Embodiment 2: collect the Jason-2 satellite DORIS observation value file from March 1st to 30th, 2015, its time sampling interval is non-equidistant (3s and 7s alternate sampling), extract L1 carrier observation value therefrom, according to the following The method obtains the L1 phase error estimation result. The noise estimation steps of DORIS observation time series are as follows:

[0090] (1) Download the observation value file from the IDS (ftp: / / ftp: / / ftp.cddis.eosdis.nasa.gov / pub / doris / ) data center, or the DORIS observation value file collected by the user, and read the carrier phase in the observation value file Observation value L D :

[0091] L D =R+c(dt-dT)+λN-d ion +d trop +ε D

[0092] Among them, R represents the geometric distance from the DORIS ground station to the satellite, c represents the speed of light, dt, dT represents the receiver clock error and satellite clock error, d ion is the ionospheric delay error, d trop is the tropospheric...

Embodiment 3

[0108]Embodiment 3: Collect the Jason-2 satellite SLR observation value file (CRD format) from January 1, 2014 to April 30, whose time sampling interval is non-equidistant (several seconds, tens of seconds, etc.), from which to extract laser light The ranging observation value is obtained according to the following method to obtain the estimation result of the laser ranging error. The noise estimation steps of the time series of SLR observations are as follows:

[0109] (1) Download the observation value file from the EDC (ftp: / / edc.dgfi.tum.de / ) data center, or the SLR observation value file collected by the user, and read the distance observation value S in the observation value file:

[0110]

[0111] Among them, c represents the speed of light, Δt represents the signal propagation time, Δs represents the error of troposphere, relativity, satellite centroid and station system, etc., ε S respectively represent the observation noise;

[0112] According to the two situati...

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Abstract

The present invention provides an adaptive differential estimation method for geodetic non-equidistant time series noise. The method of the present invention aims at the shortcomings of the conventional differential estimation method, which is only applicable to equidistant time series and the length of the differential operator is fixed. Based on the adaptive moving window and the minimum The square adjustment constructs a new difference operator estimation equation, which effectively solves the non-equidistant and non-stationary time series noise estimation problem of a single station or more in geodesy. Compared with the conventional difference estimation method, the method of the present invention has the following advantages: (1) The time basis functions based on general polynomials and Bernoulli polynomials are applicable to both non-equidistant and equidistant time series; The order is uniquely fixed, and this flexibility enables multi-node adaptability when the order of the difference remains unchanged; (3) The adaptive difference operator solved by the least squares criterion and the skewness and kurtosis test guarantee of the difference sequence The statistical optimality of the new difference operator is obtained.

Description

technical field [0001] The invention relates to a geodetic surveying technique, in particular to an adaptive difference estimation method of non-equidistant time series noise. Background technique [0002] Modern space earth observation technology represented by Global Navigation Satellite System (GNSS), Doppler Radio Positioning System (DORIS), Satellite Laser Ranging (SLR) and Satellite Altimetry (SA) are widely used in navigation and positioning, satellite Orbit determination, deformation monitoring, and reference frame maintenance. In the above application, determining the stochastic model by estimating the time series noise of the observation value can effectively improve the application accuracy. [0003] Conventional timing noise estimation or stochastic model estimation mostly focus on the GNSS field. For example, the Chinese patent No. CN201410751673.0 "A Noise Evaluation Method for Beidou Receiver Undifference Observation Value" uses the Beidou tri-frequency comb...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G01S19/37G01S19/41G06F17/16G06F17/15
CPCG01S19/37G01S19/41G06F17/15G06F17/16
Inventor 刘志平朱丹彤靳少飞张秋昭张克非
Owner CHINA UNIV OF MINING & TECH