Precise point positioning method, system and equipment in ocean scene and medium

Abstract

The invention provides a precise point positioning method, system, equipment and medium in an ocean scene, and belongs to the field of satellite navigation positioning, and the method comprises the steps: obtaining IGS-ZTD data and GGOS-ZTD data of different observation stations on the land, obtaining time sequence daily average deviation value data through calculation, inputting the data into a fitting model, carrying out the spherical harmonic expansion after fitting, and carrying out the precise point positioning. And obtaining a spherical harmonic function deviation model of the land area. Acquiring longitude and latitude of the ocean observation station, performing fitting calculation by using a spherical harmonic function deviation model, and introducing a dynamic order screening mechanism of a monthly scale to obtain a correction deviation value of the ocean observation station in the current month; and fitting ZTD data is obtained according to the correction deviation value. The regional limitation of a GNSS observation station is broken through, and the positioning precision of GGOS-ZTD data in an ocean region is improved by constructing a collaborative correction framework. And applying the fitted ZTD data to precise single-point positioning of an ocean scene to realize high-precision positioning of the measuring points in the ocean area.

Description

Technical Field

[0001] The present invention belongs to the field of satellite navigation and positioning, and specifically relates to a precise single-point positioning method, system, equipment and medium in an ocean scene. Background Art

[0002] Tropospheric delay refers to the refraction and path bending of GNSS signals as they pass through the troposphere due to atmospheric effects. The projection of this delay at the station's zenith is known as the Zenith Tropospheric Delay (ZTD). ZTD exhibits significant spatial inhomogeneity and temporal variability, and is a major source of error in GNSS positioning applications.

[0003] Spherical harmonics, orthogonal basis functions defined in a spherical coordinate system, construct spatially continuous fields through multi-order mathematical expansions, providing a core mathematical tool for modeling surface atmospheric parameters. Their spatial decomposition characteristics are reflected in the following: the spherical harmonic function system constructed based on Legendre polynomials is completely orthogonal, and by adjusting the order parameters, a multi-scale representation of the ZTD spatial distribution can be achieved: low-order components depict large-scale geographic trends, while high-order components finely analyze local features. This multi-resolution fusion feature enables the reconstruction of ZTD observations from discretely distributed land and sea stations into continuous spatial functions. While maintaining the continuity and smoothness of the global field, adaptive expression of spatial resolution is achieved through order control, laying the mathematical foundation for establishing a globally unified spatial tropospheric delay correction model.

[0004] In traditional ZTD modeling technology, the defects of the spherical harmonic function model restrict the improvement of the positioning accuracy of ocean scenes. The existing spherical harmonic function model usually adopts a global fixed-order expansion strategy, which leads to insufficient model adaptability in areas with drastic water vapor changes. In addition, real-time dynamic modeling is highly dependent on computing resources, which makes it difficult to meet the timeliness requirements of ocean positioning, resulting in large ZTD errors in ocean scenes. Summary of the Invention

[0005] In order to address the shortcomings of the existing spherical harmonic function model in applying ZTD estimation in ocean scenes, the present invention provides a precise single-point positioning method, system, device and medium in ocean scenes.

[0006] In order to achieve the above object, the present invention provides the following technical solutions: A precise point positioning method in an ocean scenario includes the following steps: Obtaining IGS-ZTD data and GGOS-ZTD data from different land stations; using the IGS-ZTD data and GGOS-ZTD data to calculate the time series daily average deviation value data; wherein the IGS-ZTD data is the zenith total delay data measured by the International Global Navigation Satellite Service Organization based on GNSS stations; the GGOS-ZTD data is the zenith tropospheric delay grid data provided by the Global Geodetic Observation System; Inputting the time series daily average deviation value data into the station data fitting model for fitting, and expanding multiple deviation change values ​​in the station data fitting model using spherical harmonics to obtain a spherical harmonics deviation model for the land area; The longitude and latitude of the ocean station are obtained; the longitude and latitude of the ocean station are input into the spherical harmonic function deviation model of the land area for fitting calculation, and a dynamic order screening mechanism at the monthly scale is introduced to obtain the corrected deviation value of the ocean station for the current month; the corrected deviation value for the current month is superimposed on the ZTD data of the ocean station to obtain fitted ZTD data; the fitted ZTD data is applied to precise point positioning (PPP) to obtain positioning accuracy and convergence time, thereby realizing positioning of the measuring point in the ocean area.

[0007] Preferably, the station data fitting model is specifically: ; in, is the daily average deviation value of the i-th time series data of the current station; multiple deviation change values ​​specifically include 、 、 、 、 ; 、 、 They are the annual mean of deviation, the annual cycle variation amplitude and the semiannual cycle variation amplitude; 、 The phases of annual cycle changes and semi-annual cycle changes; The number of days in a year corresponding to the i-th time series data.

[0008] Preferably, the spherical harmonics deviation model of the land area is specifically: ; Where i represents the parameter of the current spherical harmonic expansion, i=0, 1,…, 4; is the annual mean deviation, is the annual cycle variation amplitude, The annual cycle changes phase, is the amplitude of the half-year cycle change, is the phase of the semi-annual variation; K represents the order of the spherical harmonic function, k=1, 2,…, 15; is the Legendre polynomial; and is the longitude and latitude of the current land station; and are the spherical harmonic coefficients.

[0009] Preferably, the fitted ZTD data is applied to precise point positioning (PPP) to obtain positioning accuracy and convergence time, thereby realizing positioning of measurement points in the ocean area. Specifically, the fitted ZTD data is embedded in a real-time PPP solution engine for positioning solution, and positioning is performed according to the solution results.

[0010] Preferably, the dynamic order screening mechanism at the monthly scale is specifically: calculating the monthly average accuracy at different orders during the fitting process, and taking the order corresponding to the highest monthly average accuracy as the best fitting order corresponding to the current month.

[0011] Preferably, after obtaining the IGS-ZTD data and the GGOS-ZTD data, the method further comprises preprocessing the IGS-ZTD data and the GGOS-ZTD data respectively, specifically: Setting screening criteria for the IGS-ZTD data and eliminating data that do not meet the criteria; The GGOS-ZTD data are preprocessed by height reduction and bilinear interpolation. The height reduction is specifically performed by the following formula: ; ; in, represents the daily mean value of the GGOS-ZTD grid; is the height reduction coefficient, which is -1.3737×10 -4 ; Represents the height of the grid point on the MSL; H1 and H2 are the difference between the grid point orthometric height and MSL, and the difference between the IGS station height and MSL, respectively; Will get After bilinear interpolation to the position of the IGS station, calculate And calculated to the height of the IGS station; The time series daily average deviation data are calculated using the preprocessed IGS-ZTD data and GGOS-ZTD data.

[0012] The present invention also provides a precise single-point positioning system for ocean scenarios, specifically comprising: The data acquisition module is used to obtain IGS-ZTD data and GGOS-ZTD data from different land stations; and calculate the time series daily average deviation value data using the IGS-ZTD data and GGOS-ZTD data. The IGS-ZTD data is the zenith total delay data measured by the International Global Navigation Satellite Service Organization at the GNSS station; and the GGOS-ZTD data is the zenith tropospheric delay grid data provided by the Global Geodetic Observation System.

[0013] The model construction module is used to input the time series daily average deviation value data into the station data fitting model for fitting, and expand the multiple deviation change values ​​in the station data fitting model using spherical harmonic functions to obtain a spherical harmonic function deviation model of the land area.

[0014] The positioning module is used to obtain the longitude and latitude of the ocean station; input the longitude and latitude of the ocean station into the spherical harmonic function deviation model of the land area for fitting calculation, and introduce a dynamic order screening mechanism on a monthly scale to obtain the corrected deviation value of the ocean station for the current month; superimpose the corrected deviation value for the current month on the ZTD data of the ocean station to obtain fitted ZTD data; apply the fitted ZTD data to precise point positioning (PPP) to obtain positioning accuracy and convergence time, thereby realizing the positioning of the measurement point in the ocean area.

[0015] The present invention also provides a computer device, comprising a memory, a processor, and a computer program stored in the memory, wherein the processor executes the computer program to implement the steps described in the method for precise point positioning in an ocean scenario.

[0016] The present invention also provides a computer-readable storage medium, on which a computer program is stored. When the computer program is loaded by a processor, it can execute the steps described in the precise single-point positioning method in an ocean scenario.

[0017] The present invention provides a precise single-point positioning method for ocean scenarios, which has the following beneficial effects: The present invention obtains IGS-ZTD data and GGOS-ZTD data from different land stations, performs deviation calculation and fitting processing, and obtains a spherical harmonics deviation model for the land area. Dynamically correct the zenith direction delay on the signal propagation path, and correct the ZTD data according to the model output. Based on the spherical harmonics deviation model of the land area, a monthly scale dynamic screening mechanism is introduced to solve the problem of regional differences in marine atmospheric activity, improve the problem of accumulated delay compensation errors caused by the fixed troposphere model in the traditional PPP algorithm in the ocean scene, and realize automatic matching of the optimal ZTD parameters according to longitude and latitude and month, thereby enhancing the adaptability of the model to different sea areas. Precise single-point positioning settlement is performed based on the fitted ZTD data as input to realize the positioning of the measuring points in the ocean area, without equipment dependence and with low real-time computing burden. Reduce the computing impact when the computing resources of the ocean platform are limited, and enhance the timeliness of positioning. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] To more clearly illustrate the embodiments of the present invention and its design, the following briefly introduces the drawings required for this embodiment. The drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be derived from these drawings without inventive effort.

[0019] Figure 1 This is a flow chart of a precise point positioning method in an ocean scenario according to an embodiment of the present invention.

[0020] Figure 2 This is a frequency statistics chart of the best-fit order of global IGS ocean stations in an embodiment of the present invention.

[0021] Figure 3 This is a diagram showing the time distribution verification results of the global IGS ocean stations in an embodiment of the present invention.

[0022] Figure 4 This is a diagram showing the spatial distribution verification results of global IGS ocean stations in an embodiment of the present invention.

[0023] Figure 5 This is a comparison chart of the annual average accuracy of IGS ocean stations in the East, North, and Up directions under the two strategies of enhanced PPP and estimated PPP in an embodiment of the present invention.

[0024] Figure 6 Graph showing the relationship between the annual average Up direction accuracy improvement rate and latitude for ocean stations in the southern and northern hemispheres in an embodiment of the present invention.

[0025] Figure 7 This is a comparison chart of the convergence time of IGS ocean stations in the East, North, and Up directions under the enhanced PPP and estimated PPP strategies in an embodiment of the present invention.

[0026] Figure 8 The convergence of the ASCG, KOKB, SEY2, and THTG stations in the first hour under the two strategies of enhanced PPP and estimated PPP in the embodiment of the present invention is shown in Figure 2. Figure 8 (a) shows the convergence of ASCG at the ocean station in the first hour under the two strategies; Figure 8 (b) shows the convergence of ocean station KOKB in the first hour under the two strategies; Figure 8 (c) shows the convergence of the ocean station SEY2 under the two strategies in the first hour; Figure 8 (d) shows the convergence of THTG at the ocean station in the first hour under the two strategies. DETAILED DESCRIPTION

[0027] In order to enable those skilled in the art to better understand the technical solution of the present invention and to be able to implement it, the present invention is described in detail below with reference to the accompanying drawings and specific embodiments. The following embodiments are only used to more clearly illustrate the technical solution of the present invention and are not intended to limit the scope of protection of the present invention.

[0028] Example The present invention provides a precise single-point positioning method in an ocean scenario, such as Figure 1 As shown, the specific steps include: Step 1: Obtain IGS-ZTD and GGOS-ZTD data from different land stations, preprocess the data, and use them to calculate the daily average time series deviation data. IGS-ZTD data are zenith total delay (ZTD) data measured at GNSS stations using the International GNSS Service (IGS). GGOS-ZTD data are zenith ZTD global grid data provided by the Global Geodetic Observing System (GGOS).

[0029] S11: In terms of IGS-ZTD data processing, first, statistics are performed at each measuring station. For the 288 ZTD data generated every 5 minutes in a day, their average value is calculated as the daily average value of the corresponding measuring station.

[0030] At the same time, to ensure the credibility of the data, the daily ZTD data needs to be screened for gross errors. The standard is: if the daily mean ZTD value is greater than 3m or the standard deviation is greater than 3.5mm, the data will be eliminated.

[0031] S12: In terms of GGOS-ZTD data processing: First, calculate the daily average of the data generated daily at 0:00, 6:00, 12:00, and 18:00 by the global grid points.

[0032] In order to unify the positions of the two ZTDs in space, the daily mean values ​​of the GGOS-ZTD grid points are subjected to height conversion and bilinear interpolation. The specific height conversion calculation formula is as follows: (1) (2) The GGOS-ZTD grid data is uniformly converted to the mean sea level (MSL) using formula (1). represents the daily mean value of the GGOS-ZTD grid; is the height reduction coefficient, which is -1.3737×10 -4 ; H1 is the difference between the grid point height and MSL. The result obtained by formula (1) is bilinearly interpolated to the position of the IGS station, and then the data is converted to the height of the IGS station using formula (2). Represents the height of the grid point on MSL; H2 is the difference between the IGS station height and MSL.

[0033] S13: After time-space matching, the daily average deviation value of the annual time series is calculated based on the difference between the daily average values ​​of IGS-ZTD and GGOS-ZTD after time-space matching. The ZTD accuracy data of each IGS station is compared with the ZTD accuracy after subsequent spherical harmonic fitting, and the accuracy improvement rate is calculated to quantify the model correction effect, such as Figure 3 and Figure 4 shown.

[0034] Step 2: For the annual time series daily average deviation value data series obtained from the land observation station, fit it using the station data fitting model. The specific station data fitting model is: ; in, is the daily average deviation value of the i-th time series data of the current station; multiple deviation change values ​​specifically include 、 、 、 、 ; 、 、 They are the annual mean of deviation, the annual cycle variation amplitude and the semiannual cycle variation amplitude; 、 The phases of annual cycle changes and semi-annual cycle changes; The number of days in a year corresponding to the i-th time series data.

[0035] Based on 5 deviation change values ​​for each land station 、 、 、 、 , spherical harmonic expansion is performed using spherical harmonic functions of order 1 to 15 to establish the MBE spherical harmonic function model, which is the spherical harmonic function deviation model for the land area. Specifically: ; Where i represents the parameter of the current spherical harmonic expansion, i=0, 1,…, 4; K represents the order of the spherical harmonic function, k=1, 2,…, 15; is the Legendre polynomial; and is the longitude and latitude of the current land station; and are the spherical harmonic coefficients.

[0036] Step 3: Obtain data from 59 IGS ocean stations to form an independent validation set. Based on the spherical harmonic deviation model for land areas, the latitude and longitude of the ocean station and the annual cumulative date are input to perform a spherical harmonic fitting ZTD at sea. The output is the corrected MBE for the corresponding annual cumulative date at the station, enabling the model to be extended to the ocean.

[0037] The ZTD calculation process for offshore spherical harmonic fitting incorporates dynamic monthly order selection. The rule is: if a spherical harmonic function order has the highest monthly average accuracy, it is considered the best fitting order for that month at the current station. Corrected bias values ​​for each month at each station are obtained using the best fitting order and added to the original GGOS-ZTD data to produce the fitted ZTD data.

[0038] Step 4: Apply the fitted ZTD data to precise point positioning (PPP) to obtain the positioning accuracy and convergence time, and verify the actual positioning effect.

[0039] Two PPP experiments were designed: the first used the best-fit order spherical harmonics as a priori constraints to enhance PPP; the second relied on each station's own observational data to estimate PPP. The two processing methods were compared and analyzed in terms of positioning accuracy and convergence time to evaluate the effectiveness of GGOS-ZTD spherical harmonic corrections in improving PPP performance.

[0040] The experimental treatment effects are as follows: 1: GGOS-ZTD accuracy verification.

[0041] (1) Compliance inspection within land areas.

[0042] This section will use the established 1st to 15th-order spherical harmonics models to fit time series data from 396 land stations in 2023 and determine accuracy. To evaluate the effectiveness of the spherical harmonics model, this paper introduces the accuracy improvement rate as an evaluation metric. This rate measures the improvement in accuracy of the original GGOS-ZTD data compared to the unprocessed data.

[0043] Table 1. Annual average ZTD accuracy of spherical harmonic fitting at land stations (unit: mm) and its improvement rate

[0044] Table 1 shows the accuracy of the spherical harmonic fitting data and the improvement compared to the original data. Overall, the data accuracy improved to varying degrees for 1st to 15th-order spherical harmonic fitting. The IGS Land Station achieved the best overall fit using the 12th-order spherical harmonic model. This spherical harmonic model reduced the MAE and RMS of the GGOS-ZTD by 10.1% and 8.9%, respectively.

[0045] (2) Compliance inspection outside the marine area.

[0046] like Figure 2 The chart shows the frequency of the best-fit order used by each IGS ocean station each month. It can be seen that the frequency decreases with increasing order. The frequency of best-fit orders between 1 and 6 accounts for 79.5% of the total.

[0047] The annual average accuracy of the spherical harmonic fitting data was statistically analyzed, and its average, maximum, and minimum values ​​were calculated. The accuracy improvement rate compared with the original data was analyzed. After the model fitting, the overall systematic deviation of the IGS ocean station was corrected to a certain extent, from -6.79mm to -1.98mm. The RMS indicator shows that the overall ZTD of the ocean area has improved by 10.3%. Figure 3 and Figure 4 As shown, the time distribution verification result diagram of the global IGS ocean stations and the spatial distribution verification result diagram of the global IGS ocean stations.

[0048] Table 2 Annual average accuracy of spherical harmonic fitting data at ocean stations (unit: mm) and improvement rate

[0049] 2: Application of PPP in marine scenarios.

[0050] (1) Positioning accuracy. First, based on the spatial perspective, the annual average RMS of each ocean station in the first 5 minutes in the East, North, and Up directions using the enhanced PPP and estimated PPP strategies is calculated.

[0051] like Figure 5 As shown in Figure 1, when evaluating the PPP effect, the accuracy improvement rate refers to the improvement ratio of the enhanced mode in fitting accuracy compared with the traditional estimation mode, which is mainly reflected in the Up direction. Therefore, only the accuracy improvement rate in this direction is calculated. Figure 6 The monthly average accuracy of all ocean stations in the first five minutes of the East, North, and Up directions was calculated. Among all stations, only one showed a slight decrease in ZTD accuracy (-0.9%) after spherical harmonic fitting. The accuracy of the remaining 47 stations improved to varying degrees, ranging from 1.4% to 51.1%. The average positioning accuracy of all ocean stations increased by 19.9%.

[0052] Figure 6 The relationship between the annual average up-direction accuracy improvement and latitude was calculated for ocean stations in the northern and southern hemispheres. In the northern hemisphere, the correlation coefficient between the accuracy improvement of enhanced PPP in the first five minutes and latitude was 0.73, while in the southern hemisphere it was 0.68.

[0053] Table 3 Monthly average change statistics of the improvement rate of PPP positioning accuracy in the northern and southern hemispheres (unit: %)

[0054] Table 3 compares the monthly average accuracy improvement of enhanced PPP in the first five minutes for the Northern and Southern Hemispheres. The Northern Hemisphere outperforms the Southern Hemisphere in improving ZTD fitting accuracy, while the Southern Hemisphere performs better in terms of enhanced PPP accuracy. PPP positioning accuracy is constrained by factors such as satellite geometry, surface conditions, and atmospheric circulation. Therefore, although ZTD corrections can systematically improve positioning accuracy, the interaction of these dynamic interference factors leads to irregular fluctuations in actual positioning results.

[0055] (2) Convergence time. Figure 7 A statistical analysis of the daily convergence times for all ocean stations was performed. On average, the convergence times for IGS ocean stations worldwide were shortened by 0.63 seconds in the East, 2.50 seconds in the North, and 49.38 seconds in the Up directions. Overall, using the enhanced PPP mode, the convergence times of 28 stations (47%) were shortened, 2 stations remained unchanged, and 18 stations increased. Subsequently, a number of stations were selected from each of the three scenarios, and the results were calculated using the 68th percentile to demonstrate the convergence process under the enhanced and traditional estimation PPP modes. The rule of this statistical method is: at each epoch, the absolute values ​​of the PPP solutions for the current station throughout the year are sorted, and the 68th percentile value after sorting is taken to represent the positioning error of the station at that epoch.

[0056] Figure 8The convergence of the two PPP modes in the UP direction of the ASCG, KOKB, SEY2, and THTG stations in the first hour is shown. Figure 8 (a) is the convergence of ASCG at the ocean station; Figure 8 (b) is the convergence of ocean station KOKB; Figure 8 (c) shows the convergence of ocean station SEY2; Figure 8 (d) is the convergence status of the ocean station THTG. The selected ASCG and SEY2 stations represent the situation where the enhanced mode converges faster, the KOKB station represents the situation where the convergence time of the two modes is equivalent, and the THTG represents the situation where the estimated mode converges faster. Compared with the stations with faster convergence speed in the enhanced mode, the KOKB and THTG stations reflect a common problem: the early enhanced PPP convergence effect is better than the estimated PPP. When the convergence reaches a certain extent, the convergence of the two modes is basically the same or the estimated PPP convergence effect is better. This phenomenon is related to the update frequency of ZTD data, and its time resolution has a significant impact on the convergence speed and positioning accuracy of PPP. In the present invention, the time resolution of the GGOS-ZTD data after preprocessing is 24h, and the spherical harmonic fitting prior value is provided at 00:00 for enhanced PPP solution. Since ZTD data cannot be updated at high frequency, it is difficult to accurately reflect the actual atmospheric delay in other time periods, which in turn affects the accuracy of the later PPP solution.

[0057] The proposed method achieves a ZTD accuracy of 1.72cm in ocean scenarios, a 52% to 66% improvement compared to mainstream models (UNB3m, GPT2w-5, GPT2w-1, and GGZTD, which have ZTD accuracies of 5.15cm, 3.75cm, 3.69cm, and 3.62cm, respectively), demonstrating its superior marine adaptability. Using the proposed ZTD correction value as prior information, PPP positioning accuracy in the up direction improves by 19.9% ​​and convergence time is shortened by 49.38 seconds. This innovative method is expected to provide more reliable positioning services for offshore operations in the absence of field data.

[0058] The present invention also provides a precise single-point positioning system for ocean scenarios, specifically comprising: The data acquisition module is used to obtain IGS-ZTD data and GGOS-ZTD data from different land stations; the time series daily average deviation value data is calculated using IGS-ZTD data and GGOS-ZTD data; among them, the IGS-ZTD data is the zenith total delay data measured by the International Global Navigation Satellite Service Organization based on GNSS stations; the GGOS-ZTD data is the zenith tropospheric delay grid data provided by the Global Geodetic Observation System.

[0059] The model construction module is used to input the time series daily average deviation value data into the station data fitting model for fitting, and use spherical harmonic functions to expand the multiple deviation change values ​​in the station data fitting model to obtain the spherical harmonic function deviation model of the land area.

[0060] The positioning module is used to obtain the longitude and latitude of the ocean station; the longitude and latitude of the ocean station are input into the spherical harmonic function deviation model of the land area for fitting calculation, and a dynamic order screening mechanism on a monthly scale is introduced to obtain the corrected deviation value of the ocean station for the current month; the corrected deviation value of the current month is superimposed on the ZTD data of the ocean station to obtain the fitted ZTD data; the fitted ZTD data is applied to the precise single point positioning (PPP) to obtain the positioning accuracy and convergence time, thereby realizing the positioning of the measurement points in the ocean area.

[0061] Each module in the precise point positioning system for the aforementioned ocean scenario can be implemented in whole or in part through software, hardware, or a combination thereof. Each module can be embedded in or independent of a processor in a computer device in hardware form, or can be stored in a computer device memory in software form, so that the processor can call and execute the corresponding operations of each module.

[0062] The present invention also provides a computer device comprising a memory, a processor, and a computer program stored in the memory. The processor executes the computer program to implement the steps of an embodiment of a method for precise point positioning in an ocean scenario. The specific implementation method can be found in the method embodiment and will not be repeated here.

[0063] Furthermore, the present invention provides a non-transitory computer-readable storage medium containing instructions, wherein the storage medium stores a computer program. For example, the storage medium may be a memory containing instructions, wherein the instructions are executable by a processor of a computer device to perform the above-described method. For example, the non-transitory computer-readable storage medium may be a ROM, random access memory (RAM), CD-ROM, magnetic tape, floppy disk, or optical data storage device. When executed by the processor, the computer program is capable of implementing the steps of an embodiment of a method for precise point positioning in an ocean scenario. The specific implementation method can be found in the method embodiments and will not be further described here.

[0064] Those skilled in the art will appreciate that embodiments of the present invention may provide methods, systems, or computer program products. Accordingly, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to magnetic disk storage, CD-ROMs, optical storage, etc.) containing computer-usable program code.

[0065] The present invention is described with reference to flowcharts and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowcharts and / or block diagrams, as well as combinations of processes and / or blocks in the flowcharts and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowcharts and / or block diagrams. Figure 1 a process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0066] These computer program instructions may also be stored in a computer readable memory that can direct a computer or other programmable data processing device to work in a specific manner, so that the instructions stored in the computer readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 a process or multiple processes and / or boxes Figure 1 The function specified in one or more boxes.

[0067] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operational steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing the instructions executed on the computer or other programmable device for implementing the process. Figure 1 a process or multiple processes and / or boxes Figure 1 A step that specifies a function in one or more boxes.

[0068] It should be pointed out that the specific implementation methods described above can enable those skilled in the art to understand the invention more comprehensively, but do not limit the invention in any way. Therefore, although the present specification and examples have described the invention in detail, those skilled in the art should understand that the invention can still be modified or replaced by equivalents; and all technical solutions and improvements that do not deviate from the spirit and scope of the invention are included in the scope of protection of the patent for the invention. Any figure mark in the claims should not be regarded as limiting the claims involved. Any simple change or equivalent replacement of the technical solution that can be obviously obtained by any person familiar with the art within the technical scope disclosed in the present invention falls within the scope of protection of the present invention.

Claims

1. A precise point positioning method in an ocean scenario, characterized by: The following steps are involved: Obtaining IGS-ZTD data and GGOS-ZTD data from different land stations; using the IGS-ZTD data and GGOS-ZTD data to calculate the time series daily average deviation value data; wherein the IGS-ZTD data is the zenith total delay data measured by the International Global Navigation Satellite Service Organization based on GNSS stations; the GGOS-ZTD data is the zenith tropospheric delay grid data provided by the Global Geodetic Observation System; Inputting the time series daily average deviation value data into the station data fitting model for fitting, and expanding multiple deviation change values ​​in the station data fitting model using spherical harmonics to obtain a spherical harmonics deviation model for the land area; The longitude and latitude of the ocean station are obtained; the longitude and latitude of the ocean station are input into the spherical harmonic function deviation model of the land area for fitting calculation, and a dynamic order screening mechanism at the monthly scale is introduced to obtain the corrected deviation value of the ocean station for the current month; the corrected deviation value for the current month is superimposed on the ZTD data of the ocean station to obtain fitted ZTD data; the fitted ZTD data is applied to precise point positioning (PPP) to obtain positioning accuracy and convergence time, thereby realizing positioning of the measuring point in the ocean area.

2. The precise point positioning method in an ocean scenario according to claim 1, characterized in that: The station data fitting model is specifically: ； in, is the daily average deviation value of the i-th time series data of the current station; multiple deviation change values ​​specifically include Annual mean deviation, Annual cycle variation amplitude, Amplitude of half-year cycle changes, Annual cycle phase and Phase changes in the semiannual cycle; The number of days in a year corresponding to the i-th time series data.

3. The precise point positioning method in an ocean scenario according to claim 1, characterized in that: The spherical harmonic deviation model of the land area is specifically: ； in, are multiple deviation change values, i represents the parameter of the current spherical harmonic expansion, i=0, 1, ..., 4; K represents the order of the spherical harmonic function, k=1, 2, ..., 15; is the Legendre polynomial; and is the longitude and latitude of the current land station; and are the spherical harmonic coefficients.

4. The precise point positioning method in an ocean scenario according to claim 1, characterized in that: The fitted ZTD data is applied to precise point positioning (PPP) to obtain positioning accuracy and convergence time, thereby realizing positioning of measurement points in the ocean area. Specifically, the fitted ZTD data is embedded in a real-time PPP solution engine for positioning solution, and positioning is performed based on the solution results.

5. The precise point positioning method in an ocean scenario according to claim 1, characterized in that: The dynamic order screening mechanism of the monthly scale is specifically as follows: the monthly average accuracy under different orders is calculated during the fitting process, and the order corresponding to the highest monthly average accuracy is used as the best fitting order corresponding to the current month.

6. The precise point positioning method in an ocean scenario according to claim 1, characterized in that: The method further includes preprocessing the IGS-ZTD data and the GGOS-ZTD data respectively after acquiring the IGS-ZTD data and the GGOS-ZTD data, specifically: Setting screening criteria for the IGS-ZTD data and eliminating data that do not meet the criteria; The GGOS-ZTD data are preprocessed by height reduction and bilinear interpolation. The height reduction is specifically performed by the following formula: ； ； in, represents the daily mean value of the GGOS-ZTD grid; is the height reduction coefficient, which is -1.3737×10 -4 ; Represents the height of the grid point on the MSL; H1 and H2 are the difference between the grid point orthometric height and MSL, and the difference between the IGS station height and MSL, respectively; Will get After bilinear interpolation to the position of the IGS station, calculate And calculated to the height of the IGS station; The time series daily average deviation data are calculated using the preprocessed IGS-ZTD data and GGOS-ZTD data.

7. A precise point positioning system for ocean scenarios, characterized by: include: A data acquisition module is used to acquire IGS-ZTD data and GGOS-ZTD data from different land stations; and calculate the time series daily average deviation value data using the IGS-ZTD data and GGOS-ZTD data; wherein the IGS-ZTD data is the zenith total delay data measured by the International Global Navigation Satellite Service Organization based on GNSS stations; and the GGOS-ZTD data is the zenith tropospheric delay grid data provided by the Global Geodetic Observation System; a model building module, configured to input the time series daily average deviation value data into a station data fitting model for fitting, and expand multiple deviation change values ​​in the station data fitting model using spherical harmonic functions to obtain a spherical harmonic function deviation model for a land area; The positioning module is used to obtain the longitude and latitude of the ocean station; input the longitude and latitude of the ocean station into the spherical harmonic function deviation model of the land area for fitting calculation, and introduce a dynamic order screening mechanism on a monthly scale to obtain the corrected deviation value of the ocean station for the current month; superimpose the corrected deviation value for the current month on the ZTD data of the ocean station to obtain fitted ZTD data; apply the fitted ZTD data to precise point positioning (PPP) to obtain positioning accuracy and convergence time, thereby realizing the positioning of the measurement point in the ocean area.

8. A computer device comprising a memory, a processor, and a computer program stored in the memory, wherein: The processor executes the computer program to implement the steps of the method according to any one of claims 1 to 6.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is loaded into a processor, it can execute the steps of the method according to any one of claims 1 to 6.

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