Depth reference epoch reduction method based on GNSS and satellite height measurement

Abstract

The invention discloses a depth reference epoch reduction method based on GNSS (Global Navigation Satellite System) and satellite height measurement, which belongs to the technical field of marine surveying and mapping, is used for calculating a depth reference, and comprises the following steps of: performing data processing on an earth crust vertical deformation time sequence, calculating an earth crust vertical deformation linear rate and performing data processing on an absolute sea surface height time sequence. Acquiring an absolute sea surface height change rate; and according to the tide station data, calculating a depth reference value, performing epoch reduction on the depth reference value, and verifying an epoch reduction result. According to the invention, dynamic characteristics of earth crust vertical deformation and absolute sea surface height change are captured more comprehensively; on the long-term time scale, the change trend of the sea surface height can be reflected more accurately; a new theoretical basis is provided for epoch reduction of the depth reference, the depth reference value is dynamically adjusted, and the problem of reference surface drift caused by sea surface height change and earth crust movement is avoided, so that the long-term stability and scientificity of the depth reference are ensured.

Description

Technical Field

[0001] The invention discloses a depth reference epoch reduction method based on GNSS and satellite altimetry, belonging to the technical field of marine surveying and mapping. Background Art

[0002] Due to the complexity of tidal waves and the asynchrony of observations, the depth datum cannot be defined by a point like the elevation datum and transferred by the equipotential surface of the conservative force field or its approximate surface, but is realized by the calculation of tidal harmonic constants. If the harmonic constant has a certain trend change law, the depth datum determined by it will inevitably show a certain regular change. The traditional depth datum is represented by the depth datum value determined by the tide gauge station at discrete sites. In the calculation of the depth datum value, the datum value determined by the same location and the same calculation method has a certain time-varying property, that is, the depth datum value varies greatly with the time of tidal observation data, the length of the sequence, etc. Therefore, the depth datum is often specified as a clear epoch, that is, the depth datum epoch. Moreover, this epoch is usually specified as a specific period. According to the 18.61-year cycle of the lunar ascending node, the length of this period is usually taken as 19 years.

[0003] With the accumulation of tidal data and global sea level changes, the traditional depth datum determination method has shown obvious deficiencies and defects in practical applications. The time scales of tidal observation data used by the depth datum values ​​determined by various tide gauges at different times and locations are inconsistent, which puts the sea area depth datum in different time bases. Moreover, the depth datum values ​​currently used by long-term tide gauges were determined at an early time, and the algorithms used in different periods are not unified and have not been revised, so the timeliness needs to be improved. In addition, the depth datum does not have a clear definition of the depth datum epoch, and the depth datum determined by tidal data in different periods and time periods has a strong time-varying property.

[0004] In order to realize the construction of a unified depth datum in the sea area and avoid the time-variability caused by the depth datum determined by observation data in different periods and time periods, epoch conversion must be performed in the determination of the depth datum for tide gauge station data that do not have a specific 19-year tidal level time scale. At present, the method of implementing epoch conversion of depth datum is mainly based on the distance weighted interpolation method, the ratio method of the slightly lowest low tide level, the tidal range ratio method, the least squares fitting method and the difference correction method based on the synchronous observation data of nearby long-term tide gauge stations. However, the accuracy of the depth datum value determined by this series of methods mainly depends on the quality of the synchronous observation data. Factors such as tidal properties, transmission distance, synchronization duration and terrain environment will also affect the transmission accuracy. It cannot cope with the influence of time variability and has certain limitations.

[0005] The tidal data observed by the tide gauge station reflects a relative change in sea level height, and its rate of change is the difference between the absolute sea level change rate and the vertical deformation rate of the crust. For tide gauge stations where the absolute sea level rise rate is large and the crust rise rate is small or where subsidence occurs, the observed relative sea level height appears to rise, and vice versa. For stations where the time scale of long-term tide gauge data does not meet 19 years, the relative sea level change determined by the absolute sea level change rate and the vertical deformation rate of the crust provides a methodological basis for the innovative implementation of the depth benchmark epoch reduction. With the continuous accumulation of satellite altimetry data and the continuous improvement of GNSS technology, a practical data basis and theoretical basis have been provided for the depth benchmark epoch reduction. Summary of the invention

[0006] The purpose of the present invention is to provide a depth reference epoch reduction method based on GNSS and satellite altimetry to solve the problem in the prior art that the accuracy of the depth reference value decreases over time.

[0007] The depth reference epoch reduction method based on GNSS and satellite altimetry includes:

[0008] S1. Collect and process GNSS data, tide station data and satellite altimetry data to obtain the time series of crustal vertical deformation and absolute sea level height;

[0009] S2, processing the time series of vertical deformation of the crust and calculating the linear rate of vertical deformation of the crust;

[0010] S3, processing the absolute sea level time series to obtain the absolute sea level change rate;

[0011] S4. Calculate the depth reference value based on the tide gauge station data;

[0012] S5. Perform epoch reduction calculation on the depth reference value and verify the epoch reduction calculation result.

[0013] S1 includes site selection, which requires synchronous observation data with a time scale of more than one year, data efficiency of more than 80%, and the existence of GNSS stations and long-term tide gauge stations within 50km.

[0014] The collection and processing includes using a method of continuous iteration of harmonic analysis to process missing values ​​and zero drift of tide station data, wherein the tide station data is tide level data;

[0015] The mean of the effective along-track points within a 1° range around the tide gauge station is selected as the absolute sea level height time series.

[0016] The cubic spline interpolation method and the three-fold mean error are used as the threshold to process the missing values ​​and abnormal values ​​of the GNSS data and the satellite altimetry data, respectively. The satellite altimetry data is a tidal height sequence inverted from the satellite altimetry.

[0017] The short-term data drift caused by GNSS antenna movement and earthquake factors is unified to obtain the time series of vertical crustal deformation.

[0018] S2 includes using a linear regression model to calculate the linear rate of vertical crust deformation of the time series of vertical crust deformation.

[0019] S3 includes using singular spectrum analysis to perform principal component analysis on the absolute sea level time series, removing seasonal periodic signals, and using a linear regression model to obtain the absolute sea level change rate. .

[0020] S5 includes the linear rate of vertical deformation of the crust between the observation epoch and the target epoch based on the tide observation data and the absolute sea level change rate , construct the mathematical model of depth benchmark epoch reduction:

[0021] ;

[0022] In the formula, , denote the observation epoch and the target epoch respectively, epoch normalization for the depth reference value.

[0023] The epoch-corrected depth reference value is added to the depth reference value of S4 to obtain the depth reference value after epoch-corrected correction.

[0024] Compared with the prior art, the present invention has the following beneficial effects: the present invention combines the use of multi-source data such as GNSS, tide gauges and satellite altimetry to more comprehensively capture the dynamic characteristics of vertical crust deformation and absolute sea level changes; the traditional method mainly relies on tide gauge data, which is limited by the quality of synchronous observation data and transmission distance, and has limited accuracy. The fusion of multi-source data not only makes up for the shortcomings of a single data source, but also improves the accuracy of depth benchmark epoch reduction through cross-validation, especially on a long-term time scale, and can more accurately reflect the trend of sea level changes. The traditional depth benchmark determination method is difficult to effectively deal with the influence of time variability, and the present invention provides a new theoretical basis for depth benchmark epoch reduction by introducing the calculation of absolute sea level change rate and vertical crust deformation rate. This method can dynamically adjust the depth benchmark value to avoid the problem of benchmark drift caused by sea level changes and crustal movement, thereby ensuring the long-term stability and scientificity of the depth benchmark. BRIEF DESCRIPTION OF THE DRAWINGS

[0025] Figure 1 It is a flow chart of the present invention. DETAILED DESCRIPTION

[0026] In order to make the purpose, technical solution and advantages of the present invention clearer, the technical solution of the present invention is described clearly and completely below. Obviously, the described embodiments are part of the embodiments of the present invention, but not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0027] The depth reference epoch reduction method based on GNSS and satellite altimetry includes:

[0028] S1. Collect and process GNSS data, tide station data and satellite altimetry data to obtain the time series of crustal vertical deformation and absolute sea level height;

[0029] S2, processing the time series of vertical deformation of the crust and calculating the linear rate of vertical deformation of the crust;

[0030] S3, processing the absolute sea level time series to obtain the absolute sea level change rate;

[0031] S4. Calculate the depth reference value based on the tide gauge station data;

[0032] S5. Perform epoch reduction calculation on the depth reference value and verify the epoch reduction calculation result.

[0033] S1 includes site selection, which requires synchronous observation data with a time scale of more than one year, data efficiency of more than 80%, and the existence of GNSS stations and long-term tide gauge stations within 50km.

[0034] The collection and processing includes using a method of continuous iteration of harmonic analysis to process missing values ​​and zero drift of tide station data, wherein the tide station data is tide level data;

[0035] The mean of the effective along-track points within a 1° range around the tide gauge station is selected as the absolute sea level height time series.

[0036] The cubic spline interpolation method and the three-fold mean error are used as the threshold to process the missing values ​​and abnormal values ​​of the GNSS data and the satellite altimetry data, respectively. The satellite altimetry data is a tidal height sequence inverted from the satellite altimetry.

[0037] The short-term data drift caused by GNSS antenna movement and earthquake factors is unified to obtain the time series of vertical crustal deformation.

[0038] S2 includes using a linear regression model to calculate the linear rate of vertical crust deformation of the time series of vertical crust deformation.

[0039] S3 includes using singular spectrum analysis to perform principal component analysis on the absolute sea level time series, removing seasonal periodic signals, and using a linear regression model to obtain the absolute sea level change rate. .

[0040] S5 includes the linear rate of vertical deformation of the crust between the observation epoch and the target epoch based on the tide observation data and the absolute sea level change rate , construct the mathematical model of depth benchmark epoch reduction:

[0041] ;

[0042] In the formula, , denote the observation epoch and the target epoch respectively, epoch normalization for the depth reference value.

[0043] The epoch-corrected depth reference value is added to the depth reference value of S4 to obtain the depth reference value after epoch-corrected correction.

[0044] The present invention innovatively proposes a depth benchmark epoch reduction model based on the absolute sea level change rate and the crust vertical deformation rate. Traditional methods mainly rely on statistical analysis of tide gauge station data, while this model can more accurately quantify the change rate of relative sea level by combining satellite altimetry and GNSS data, thereby providing a more scientific mathematical basis for the epoch reduction of the depth benchmark. This innovation not only solves the problem that traditional methods cannot cope with time variability, but also provides a new technical means for the long-term maintenance of the depth benchmark. The present invention proposes an innovative mechanism for collaborative processing and verification of multi-source data. Through the joint processing of GNSS, satellite altimetry and tide gauge station data, not only can more accurate crust deformation and absolute sea level change information be obtained, but also the reliability and consistency of the data can be ensured through cross-validation. This collaborative processing mechanism not only improves the accuracy of depth benchmark epoch reduction, but also provides an operational technical framework for subsequent datum surface updates and maintenance, and has important practical value.

[0045] The technical process of the present invention is as follows Figure 1As shown, it includes processing GNSS observation data, extracting crustal deformation sequence, obtaining crustal vertical deformation rate and uncertainty, processing satellite altimetry data, extracting sea surface height time series, obtaining absolute sea surface height rate, obtaining long-term tide gauge station data, processing tide level data in combination with crustal deformation sequence, correcting relative sea surface height by combining crustal vertical deformation rate, uncertainty, and tide level data with absolute sea surface height rate, obtaining depth reference epoch reduction result and verifying it. The present invention extracts absolute sea surface height change rate of 16 long-term tide gauge stations in the experimental sea area, and performs statistics on sea surface height change rate of 16 long-term tide gauge stations as shown in Table 1.

[0046] Table 1. Sea surface height change rate at 16 long-term tide gauge stations (unit: mm)

[0047] ;

[0048] according to conduct Calculate and obtain the depth reference plane as shown in Table 2.

[0049] Table 2. Epoch reduction verification results (unit: cm)

[0050] ;

[0051] Table 2 shows the results of the long-term tide station data after the depth benchmark epoch conversion. Taking the tide data from 2000 to 2011 as the benchmark, after calculating the benchmark value, the data from 2011 to 2018 were further corrected for deformation (2011-2018 deformation = , the table is approximated to two decimal places in cm), and finally the benchmark value after epoch correction is obtained. The benchmark values ​​from 2000 to 2018 are used as the "true value" for comparative analysis. The results show that the average value of the benchmark value after epoch conversion is reduced from 7.03 cm to 3.95 cm. Although the correction effect of some stations is not ideal due to changes in the coastline and environmental factors, overall, epoch conversion has significantly improved the accuracy of the benchmark value.

[0052] The above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit the same. Although the present invention has been described in detail with reference to the aforementioned embodiments, a person skilled in the art should understand that the technical solutions described in the aforementioned embodiments may still be modified, or some or all of the technical features may be replaced by equivalents, and these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for calculating depth reference epochs based on GNSS and satellite altimetry, characterized in that: include: S1. Collect and process GNSS data, tide station data and satellite altimetry data to obtain the time series of crustal vertical deformation and absolute sea level height; S2, processing the time series of vertical deformation of the earth's crust and calculating the linear rate of vertical deformation of the earth's crust; S3, processing the absolute sea level time series to obtain the absolute sea level change rate; S4. Calculate the depth reference value based on the tide gauge station data; S5. Perform epoch reduction calculation on the depth reference value and verify the epoch reduction calculation result.

2. The method for calculating depth reference epochs based on GNSS and satellite altimetry according to claim 1, characterized in that: S1 includes site selection, which requires synchronous observation data with a time scale of more than one year, data efficiency of more than 80%, and the existence of GNSS stations and long-term tide gauge stations within 50km.

3. The method for calculating depth reference epochs based on GNSS and satellite altimetry according to claim 1, characterized in that: The collection and processing includes using a method of continuous iteration of harmonic analysis to process missing values ​​and zero drift of tide station data, wherein the tide station data is tide level data; The mean of the effective along-track points within a 1° range around the tide gauge station is selected as the absolute sea level height time series.

4. The method for calculating depth reference epochs based on GNSS and satellite altimetry according to claim 3, characterized in that: The cubic spline interpolation method and the three-fold mean error are used as the threshold to process the missing values ​​and abnormal values ​​of the GNSS data and the satellite altimetry data, respectively. The satellite altimetry data is a tidal height sequence inverted from the satellite altimetry. The short-term data drift caused by GNSS antenna movement and earthquake factors is unified to obtain the time series of vertical crustal deformation.

5. The method for calculating depth reference epochs based on GNSS and satellite altimetry according to claim 4, characterized in that: S2 includes using a linear regression model to calculate the linear rate of vertical crust deformation of the time series of vertical crust deformation.

6. The method for calculating depth reference epochs based on GNSS and satellite altimetry according to claim 5, characterized in that: S3 includes using singular spectrum analysis to perform principal component analysis on the absolute sea level time series, eliminating seasonal periodic signals, and using a linear regression model to obtain the absolute sea level change rate. .

7. The method for calculating depth reference epochs based on GNSS and satellite altimetry according to claim 6, characterized in that: S5 includes the linear rate of vertical crustal deformation between the epoch observed and the target epoch based on tidal observation data with a 19-year epoch period. and the absolute sea level change rate , construct the mathematical model of depth benchmark epoch reduction: ； In the formula, , denote the observation epoch and the target epoch respectively, The epoch return value for the depth reference value.

8. The method for calculating depth reference epochs based on GNSS and satellite altimetry according to claim 7, characterized in that: The epoch-corrected depth reference value is added to the depth reference value of S4 to obtain the depth reference value after epoch-corrected correction.

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