A method for tide measurement using a floating platform based on offshore GNSS data

Abstract

This invention relates to the field of line-of-sight measurement technology and discloses a method for tide gauge observation using a floating platform based on offshore GNSS data. The method includes a GNSS device and a communication device, comprising the following steps: S01, deploying at least one GNSS device sufficient to cover the detection area, and establishing a connection between the GNSS device and a user terminal via the communication device; S02, the user terminal's data center receiving and storing the real-time GNSS data transmitted by the GNSS device to obtain a GNSS dataset; S03, correcting the received GNSS dataset by deleting outliers and performing data filtering to obtain tide gauge data for offshore points. This invention solves the problem of low accuracy in tide gauge data due to displacement of submerged tide gauges in areas such as long-distance offshore operation areas where shore-based tide gauge stations cannot be deployed, or in areas with strong tides, estuaries, and soft bottoms, where submerged tide gauges are prone to displacement.

Description

Technical Field

[0001] This invention relates to line-of-sight measurement, and more specifically to a method for tide reading on a floating platform based on offshore GNSS data. Background Technology

[0002] The so-called tide gauge is the observation of water level. By observing water level, one can intuitively understand the tidal characteristics of the local area. By obtaining data from the observation, one can calculate the tidal harmonic parameters, mean sea level, depth datum, tidal forecast, and provide water level corrections for different times.

[0003] Existing tide gauge methods include two types: shore-based and offshore.

[0004] Shore-based tide gauges are further subdivided into several types, including water gauge tide gauges, float-type tide gauges, pressure-type water level gauges, and radar-type water level gauges. This primarily involves constructing corresponding observation stations. However, in strong tidal estuaries or silted coastal areas, this not only requires substantial investment but also presents significant challenges in site selection. Furthermore, siltation at these stations can severely impact the accuracy and precision of the observations.

[0005] Compared to the disadvantages of shore-based systems, offshore systems are more flexible, but they are subject to vertical displacement due to water flow and their own weight after deployment. This change is generally difficult to measure and has a significant impact on data accuracy.

[0006] Therefore, there is a need for a method that is as flexible as an offshore tide gauge while avoiding the problem of being greatly affected by external interference in a shore-based tide gauge. It is hoped that a good solution can be found. Summary of the Invention

[0007] The purpose of this invention is to provide a method for tide measurement on a floating platform based on offshore GNSS data, in order to solve the above-mentioned problems.

[0008] To achieve the above objectives, the present invention provides the following technical solution: a method for tide measurement on a floating platform based on offshore GNSS data, comprising GNSS equipment and communication equipment, and including the following steps:

[0009] S01. Deploy at least one GNSS device sufficient to cover the detection area, and establish a connection between the GNSS device and the user terminal through the communication device;

[0010] S02. The data center at the user end receives and stores the real-time GNSS data transmitted by the GNSS device to obtain a GNSS dataset.

[0011] S03. The received GNSS dataset is processed by deleting outliers and correcting data filtering to obtain the tide data of the offshore point.

[0012] S04. The user terminal feeds back the tide height data of the offshore point to the user.

[0013] Preferably, the GNSS data includes time, east, north, and altitude directions.

[0014] Preferably, the observation frequency of the GNSS device is 10Hz.

[0015] Preferably, step S03, which involves deleting outliers and correcting data filtering in the received GNSS dataset, includes:

[0016] S31. Based on the GNSS dataset obtained from one of the GNSS devices, H is processed sequentially. 秒平均 H 分钟平均 and H 小时平均 Anomaly filtering is constructed from top to bottom using hourly averages. Points exceeding the threshold are deleted as anomalies, resulting in anomaly data set and normal data set. Then, a polynomial is used to fit them to obtain a fitting curve.

[0017] S32. After smoothing the obtained fitted curve, perform interpolation and then use polynomial interpolation to solve for the tidal level at that point.

[0018] Preferably, step S31 includes the following steps:

[0019] S311. Calculate the average height of the GNSS dataset for 1 second, 1 minute, and 60 minutes sequentially, where:

[0020] The method for calculating the average value over one second is as follows:

[0021] (1);

[0022] Where H represents the high-frequency data within the GNSS data, and i represents 10 GNSS data points obtained by deploying at least one GNSS device sufficient to cover the detection area and performing 10Hz observations within 1 second.

[0023] The method for calculating the 1-minute average is as follows:

[0024] (2);

[0025] Among them, H 分钟平均 For H within 60 seconds 秒平均 Calculate the average value of the results;

[0026] The method for calculating the 1-hour average is as follows:

[0027] (3);

[0028] Among them, H 小时平均 For 60 minutes of H 分钟平均 Calculate the average value of the results;

[0029] S312, the resulting multiple H 小时平均 By fitting it with a polynomial, L is obtained. 小时 Fit a curve, and denote the data of the fitted curve as H. 小时拟合 Calculate the difference between the data before and after fitting:

[0030] (4);

[0031] Double The size is used as a threshold to filter out values ​​that exceed the fitted curve. range of H 分钟平均 The data points are treated as gross errors and removed from the GNSS dataset. The H value for removing these gross errors is denoted as H. 分钟平均 For H 分钟剔除 ;

[0032] S313. Fit it again using a polynomial to obtain L. 分钟 Fit a curve, and denote the data of the fitted curve as H. 分钟拟合 Calculate the difference between the data before and after fitting:

[0033] (5);

[0034] Double The size is used as a threshold to filter out values ​​that exceed the fitted curve. The data of H observations within the range are treated as gross errors and removed from the GNSS dataset. The H observations with gross errors removed are denoted as H-second removals.

[0035] Preferably, step S32 includes the following steps:

[0036] S321. Use the moving average method to smooth the GNSS dataset after deleting outliers.

[0037] (6);

[0038] S322. Calculate the GNSS dataset for deleting outliers using an interpolation method.

[0039] (7).

[0040] In the above technical solution, the floating platform tide gauge method based on offshore GNSS data provided by the present invention has the following beneficial effects:

[0041] Data can be collected directly using a floating platform, which is convenient for site deployment and can be measured without the need to build stations. At the same time, by combining high-frequency GNSS observation with data processing, the problem of traditional bottom-mounted tide gauges being unable to obtain accurate tide data due to settlement or other displacements is avoided.

[0042] 2. By processing high-frequency GNSS observation data, the mean values ​​were calculated from seconds to minutes to hours. Then, outlier filtering and interpolation were performed by constructing hourly and minute fitting curves. The tidal data was calculated using a simple and easy-to-implement algorithm. Attached Figure Description

[0043] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments recorded in this invention. For those skilled in the art, other drawings can be obtained based on these drawings.

[0044] Figure 1 A flowchart provided for an embodiment of the present invention. Detailed Implementation

[0045] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. All other embodiments obtained by ordinary technicians in this field based on the embodiments of the present invention without making any creative efforts shall fall within the scope of protection of the present invention.

[0046] like Figure 1 As shown, a method for tide measurement using a floating platform based on offshore GNSS data includes the following steps:

[0047] S01. Deploy at least one GNSS device sufficient to cover the detection area, and establish contact between the GNSS device and the user terminal through communication equipment;

[0048] S02. The user's data center receives and stores the real-time GNSS data transmitted by the GNSS equipment to obtain a GNSS dataset.

[0049] S03. Delete outliers and correct data filtering in the received GNSS dataset to obtain tide data for offshore points.

[0050] S04. The user terminal feeds back the tide level data of the offshore point to the user.

[0051] Specifically, in the above embodiments, deploying at least one GNSS device sufficient to cover the detection area means pre-building a floating platform according to the detection area, fixing the floating platform with an anchor bolt system, and then fixing the GNSS device, power supply equipment, and communication equipment on the floating platform.

[0052] The observation frequency of GNSS equipment is 10Hz.

[0053] Furthermore, the GNSS data in the above embodiments includes time, east, north, and altitude. Step S03 involves deleting outliers and correcting data filtering in the received GNSS dataset, primarily targeting the altitude within the GNSS data. Detailed processing steps include:

[0054] Based on the GNSS dataset obtained from a GNSS device, H was successively... 秒平均 H 分钟平均 and H 小时平均 An outlier filtering is constructed from top to bottom using hourly averages. Points exceeding a threshold are deleted as outliers, resulting in an outlier dataset and a normal dataset. A polynomial is then used to fit these datasets to obtain a fitted curve.

[0055] S311. Calculate the average height of the GNSS dataset for 1 second, 1 minute, and 60 minutes sequentially, where:

[0056] The method for calculating the average value over one second is as follows:

[0057] (1);

[0058] Where H represents the high-frequency data within the GNSS data, and i represents 10 GNSS data points obtained by deploying at least one GNSS device sufficient to cover the detection area and performing 10Hz observations within 1 second.

[0059] The method for calculating the 1-minute average is as follows:

[0060] (2);

[0061] Among them, H 分钟平均 For H within 60 seconds 秒平均 Calculate the average value of the results;

[0062] The method for calculating the 1-hour average is as follows:

[0063] (3);

[0064] Among them, H 小时平均 For 60 minutes of H 分钟平均 Calculate the average value of the results;

[0065] S312, the resulting multiple H 小时平均 By fitting it with a polynomial, L is obtained. 小时 Fit a curve, and denote the data of the fitted curve as H. 小时拟合 Calculate the difference between the data before and after fitting:

[0066] (4);

[0067] Double The size is used as a threshold to filter out values ​​that exceed the fitted curve. range of H 分钟平均 The data points are treated as gross errors and removed from the GNSS dataset. The H value for removing these gross errors is denoted as H. 分钟平均 For H 分钟剔除 ;

[0068] S313. Fit it again using a polynomial to obtain L. 分钟 Fit a curve, and denote the data of the fitted curve as H. 分钟拟合 Calculate the difference between the data before and after fitting:

[0069] (5);

[0070] Double The size is used as a threshold to filter out values ​​that exceed the fitted curve. The data of H observations within the range are treated as gross errors and removed from the GNSS dataset. The H observations with gross errors removed are denoted as H-second removals.

[0071] The purpose of smoothing the obtained fitted curve is that, since the GNSS platform is directly deployed on the water surface, it is affected not only by the tide level but also by various factors such as tidal currents, ship waves, and wind. Occasionally, outliers may appear during the observation. These influences are short-period data relative to the tide level change, while the tide level change is a long-period change. Therefore, by using high-frequency observations to calculate the average values ​​for seconds, minutes, and hours, the data can be smoothed, eliminating the influence of short-period data on the outlier data of the tide level observation.

[0072] Interpolation is performed after smoothing because tidal level changes are a continuous process without abrupt changes. Therefore, given sufficient observational data, interpolation can be used to fill in missing data. When the data observation density is high enough, data within short periods (e.g., 1 minute) can even be considered linearly correlated. This is done to better fit tidal level observations.

[0073] Finally, polynomial interpolation was used to determine the tide level at that point.

[0074] The detailed steps of the above embodiments are as follows:

[0075] S321. Use the moving average method to smooth the GNSS dataset after deleting outliers.

[0076] (6);

[0077] S322. Calculate the GNSS dataset for deleting outliers using an interpolation method.

[0078] (7).

[0079] It should be noted that the polynomial fitting in the above embodiments is performed by determining the order of the fitting polynomial. Due to the large amount of collected data, the six nearest known data points to the point to be interpolated (this is divided into three cases: three data points before and after the point to be interpolated, or more than three data points before or after the point to be interpolated, which does not affect the operation of the algorithm) are used for a total of six points, and cubic spline interpolation is performed. The process is as follows:

[0080] 1) Read known data, i.e., nodes The value of i ranges from 0 to 5, and the insertion point is marked as...

[0081] 2) For i = 0, 1, ..., 5, calculate

[0082] 3) Calculation and (i=0,1,…,5)

[0083]

[0084]

[0085] For i=1,…,4, calculate:

[0086]

[0087] 4) Calculation and (i=0,1,…,5)

[0088]

[0089] For i=1,…,5, calculate:

[0090]

[0091] 5) Calculation (i=0,1,…,5)

[0092]

[0093]

[0094] 6) Determine the insertion point The interval Then calculate the corresponding value and output it:

[0095] + .

[0096] In the above, x represents the observation time, y represents the tidal level at the observation time, and h is the step size. The correlation coefficient is the result of cubic spline interpolation.

[0097] Among the above technologies, data is collected directly using a floating platform, which is convenient for site deployment and can be measured without the need to build a station; at the same time, by combining high-frequency GNSS observation with data processing, the problem of traditional bottom-mounted tide gauges being unable to obtain accurate tide data due to settlement or other displacement is avoided.

[0098] By processing high-frequency GNSS observation data, the mean values ​​were calculated from seconds to minutes to hours. Then, outlier filtering and interpolation were performed by constructing hourly and minute fitting curves. The tidal level data was calculated using a simple and easy-to-implement algorithm.

[0099] Those skilled in the art will understand that embodiments of the present invention can be provided as methods, systems, or computer program products. Therefore, the present invention can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention can take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0100] This invention is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations 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, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart illustrations and / or block diagrams. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0101] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0102] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0103] Specific embodiments have been used to illustrate the principles and implementation methods of this invention. The descriptions of the embodiments above are only for the purpose of helping to understand the method and core ideas of this invention. At the same time, for those skilled in the art, there will be changes in the specific implementation methods and application scope based on the ideas of this invention. Therefore, the content of this specification should not be construed as a limitation of this invention.

[0104] The embodiments of this application also provide a specific implementation of an electronic device capable of implementing all the steps in the methods described above, wherein the electronic device specifically includes the following:

[0105] Processor, memory, communications interface, and bus;

[0106] The processor, memory, and communication interface communicate with each other through the bus.

[0107] The processor is used to invoke a computer program in the memory, and when the processor executes the computer program, it implements all the steps in the method described in the above embodiments.

[0108] Embodiments of this application also provide a computer-readable storage medium capable of implementing all the steps of the methods in the above embodiments, wherein the computer-readable storage medium stores a computer program that, when executed by a processor, implements all the steps of the methods in the above embodiments.

[0109] The various embodiments in this specification are described in a progressive manner. Similar or identical parts between embodiments can be referred to mutually. Each embodiment focuses on its differences from other embodiments. In particular, for hardware + program embodiments, since they are basically similar to method embodiments, the description is relatively simple; relevant parts can be referred to the descriptions in the method embodiments. Although the embodiments in this specification provide the method operation steps as shown in the embodiments or flowcharts, more or fewer operation steps may be included based on conventional or non-inventive means. The order of steps listed in the embodiments is merely one possible execution order among many steps and does not represent the only execution order. In actual device or terminal product execution, the methods can be executed in the order shown in the embodiments or drawings or in parallel (e.g., in a parallel processor or multi-threaded processing environment, or even a distributed data processing environment). The terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, product, or apparatus that includes a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, product, or apparatus. Without further limitations, the presence of other identical or equivalent elements in the process, method, product, or apparatus that includes said elements is not excluded. For ease of description, the above devices are described in terms of function, divided into various modules. Of course, in implementing the embodiments of this specification, the functions of each module can be implemented in one or more software and / or hardware, or the module implementing the same function can be implemented by a combination of multiple sub-modules or sub-units, etc. The device embodiments described above are merely illustrative. For example, the division of units is only a logical functional division; in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the displayed or discussed mutual couplings or direct couplings or communication connections may be through some interfaces; indirect couplings or communication connections between devices or units may be electrical, mechanical, or other forms. This invention is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It should be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations 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, special-purpose computer, embedded processor, or other programmable data processing device to produce a machine, such that the instructions, which are executable by the processor of the computer or other programmable data processing device, produce instructions for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0110] Those skilled in the art will understand that the embodiments of this specification can be provided as methods, systems, or computer program products. Therefore, the embodiments of this specification can take the form of entirely hardware embodiments, entirely software embodiments, or embodiments combining software and hardware aspects. Furthermore, the embodiments of this specification can take the form of computer program products implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code. The various embodiments in this specification are described in a progressive manner, and similar or identical parts between embodiments can be referred to mutually. Each embodiment focuses on describing the differences from other embodiments. In particular, for system embodiments, since they are basically similar to method embodiments, the description is relatively simple, and relevant parts can be referred to the description of the method embodiments. In the description of this specification, the reference to the terms "one embodiment," "some embodiments," "example," "specific example," or "some examples," etc., means that a specific feature, structure, material, or characteristic described in connection with that embodiment or example is included in at least one embodiment or example of the embodiments of this specification.

[0111] In this specification, the illustrative expressions of the terms used do not necessarily refer to the same embodiments or examples. Furthermore, those skilled in the art can combine and integrate different embodiments or examples described in this specification, as well as features of different embodiments or examples, without contradiction. The above descriptions are merely embodiments of this specification and are not intended to limit the embodiments of this specification. Various modifications and variations can be made to the embodiments of this specification by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principle of the embodiments of this specification should be included within the scope of the claims of the embodiments of this specification.

Claims

1. A method for tide measurement on a floating platform based on offshore GNSS data, comprising GNSS equipment and communication equipment, characterized in that, Includes the following steps: S01. Deploy at least one GNSS device sufficient to cover the detection area, and establish a connection between the GNSS device and the user terminal through the communication device; S02. The data center at the user end receives and stores the real-time GNSS data transmitted by the GNSS device to obtain a GNSS dataset. S03. The received GNSS dataset is processed by deleting outliers and correcting data filtering to obtain the tide data of the offshore point. S04. The user terminal feeds back the tide height data of the offshore point to the user; Step S03, which involves deleting outliers and correcting data filtering in the received GNSS dataset, includes: S31. Based on the GNSS dataset obtained from one of the GNSS devices, H is processed sequentially. 秒平均 H 分钟平均 and H 小时平均 Anomaly filtering is constructed from top to bottom using hourly averages. Points exceeding the threshold are deleted as anomalies, resulting in anomaly data set and normal data set. Then, a polynomial is used to fit them to obtain a fitting curve. S32. After smoothing the obtained fitted curve, perform interpolation and then use polynomial interpolation to solve for the tidal level at that point. The execution steps of step S32 include: S321. Use the moving average method to smooth the GNSS dataset after deleting outliers. （6）； S322. Calculate the GNSS dataset for deleting outliers using an interpolation method. （7）； The execution steps of step S31 include: S311. Calculate the average height of the GNSS dataset for 1 second, 1 minute, and 60 minutes sequentially, where: The method for calculating the average value over one second is as follows: （1）； Where H represents the high-frequency data within the GNSS data, and i represents 10 GNSS data points obtained by deploying at least one GNSS device sufficient to cover the detection area and performing 10Hz observations within 1 second. The method for calculating the 1-minute average is as follows: （2）； Among them, H 分钟平均 For H within 60 seconds 秒平均 Calculate the average value of the results; The method for calculating the 1-hour average is as follows: （3）； Among them, H 小时平均 For 60 minutes of H 分钟平均 Calculate the average value of the results; S312, the resulting multiple H 小时平均 By fitting it with a polynomial, L is obtained. 小时 Fit a curve, and denote the data of the fitted curve as H. 小时拟合 Calculate the difference between the data before and after fitting: （4）； Double The size is used as a threshold to filter out values ​​that exceed the fitted curve. range of H 分钟平均 The data points are treated as gross errors and removed from the GNSS dataset. The H value for removing these gross errors is denoted as H. 分钟平均 For H 分钟剔除 ; S313. Fit it again using a polynomial to obtain L. 分钟 Fit a curve, and denote the data of the fitted curve as H. 分钟拟合 Calculate the difference between the data before and after fitting: （5）； Double The size is used as a threshold to filter out values ​​that exceed the fitted curve. The data of H observations within the range are treated as gross errors and removed from the GNSS dataset. The H observations with gross errors removed are denoted as H-second removals.

2. The method for tide measurement using a floating platform based on offshore GNSS data according to claim 1, characterized in that, The GNSS data includes time, east, north, and altitude.

3. The method for tide measurement using a floating platform based on offshore GNSS data according to claim 1, characterized in that, The observation frequency of the GNSS equipment is 10 Hz.

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