Sea ice freeboard estimation method, device, equipment, medium and program

Abstract

The invention relates to the technical field of measurement and mapping engineering, in particular to a sea ice freeboard estimation method, device, equipment, medium and program, and the method comprises the steps: receiving global navigation satellite system (GNSS) measurement data through a receiver, and resolving positioning data according to the GNSS measurement data; calculating the height from the antenna of the receiver to the ice surface at the current moment according to the measurement data, and calculating the reflection surface elevation of the receiver at the current moment according to the height from the antenna to the ice surface and the positioning data; and estimating the sea ice freeboard according to the reflecting surface elevation of the receiver at the current moment and the reference sea surface elevation. Therefore, the problems of relatively low real-time performance, inaccurate measurement result, relatively high limitation and the like caused by the fact that a sea ice freeboard estimation result is easily interfered by equipment, a signal source, an environment and the like in related technologies are solved.

Description

Technical Field

[0001] This application relates to the field of surveying and mapping engineering technology, and in particular to a method, apparatus, equipment, medium and program for estimating sea ice freeboard. Background Technology

[0002] With the increasing severity of global warming, sea ice information sensing and sea ice environment monitoring have become important issues. Traditional sea ice detection methods...

[0003] Among related technologies, traditional sea ice detection methods have limitations to varying degrees:

[0004] (1) Ice core drilling method has high precision but has spatial limitations;

[0005] (2) Satellite remote sensing data has high spatiotemporal resolution, but satellite images in regions such as the polar regions are difficult to download quickly and lack real-time performance;

[0006] (3) Shipborne sea ice camera technology has good real-time performance and high accuracy, but it is easily affected by rain, sea fog, darkness and other factors, resulting in low camera visibility and unstable signal source. Summary of the Invention

[0007] This application provides a method, apparatus, equipment, medium, and program for estimating sea ice freeboard, in order to solve the problems in related technologies where sea ice freeboard estimation results are easily affected by interference from equipment, signal sources, and the environment, resulting in low real-time performance, inaccurate measurement results, and high limitations.

[0008] The first aspect of this application provides a method for estimating sea ice freeboard, comprising the following steps: receiving measurement data and positioning data from a Global Navigation Satellite System (GNSS) using a receiver; calculating the height of the receiver's antenna above the ice surface at the current moment based on the measurement data; calculating the reflector elevation of the receiver at the current moment based on the antenna height above the ice surface and the positioning data; and estimating the sea ice freeboard based on the reflector elevation of the receiver at the current moment and a reference sea surface elevation.

[0009] Optionally, calculating the height of the receiver's antenna above the ice surface at the current moment based on the measurement data includes: identifying the main signal frequency of each satellite in the measurement data during the target time period; calculating the height of the receiver's antenna above the ice surface corresponding to the main signal frequency of each satellite during the target time period; and weightedly fusing the heights of the receiver's antenna above the ice surface calculated from the multiple satellites to generate the height of the receiver's antenna above the ice surface at the current moment.

[0010] Optionally, identifying the dominant signal frequency of each satellite in the target time period in the measurement data includes: extracting the elevation angle, azimuth angle, and signal-to-noise ratio data of each satellite in the measurement data; using overlapping sliding windows to segment the sequence composed of the elevation angle and signal-to-noise ratio data of each satellite to generate corresponding sea surface height sequence segments; and performing spectral analysis on the sequence segments of each sliding window to extract the dominant signal frequency.

[0011] Optionally, the formula for calculating the sea ice freeboard is:

[0012] freeboard = H reflector -H SEA ;

[0013] Among them, H reflector H represents the elevation of the receiver's reflector surface at the current moment. SEA It represents the instantaneous elevation of the sea surface, that is, the distance from the instantaneous sea surface to the reference ellipsoid.

[0014] Optionally, the formula for calculating the elevation of the reflecting surface is:

[0015] H reflector =H GNSS -h GNSS-IR ;

[0016] Among them, H GNSS h is the ellipsoidal height of the GNSS antenna phase center. GNSS-IR This represents the height difference between the antenna and the reflector.

[0017] Optionally, the formula for calculating the instantaneous elevation of the sea surface is:

[0018] H SEA =MSL+h tide ≈N+h tide ;

[0019] Among them, h tide The tidal height represents the location the trajectory passes through. MSL represents the distance from the mean sea level to the reference ellipsoid. N represents the geoid distance. In open sea, the geoid distance N can be used instead of the mean sea level ellipsoid height MSL.

[0020] Optionally, before estimating the sea ice freeboard based on the reflector elevation of the receiver and the reference sea surface elevation at the current moment, the method further includes: inputting the positioning data into a preset model, wherein the preset model outputs the tidal height and geoid distance of the corresponding trajectory location.

[0021] A second aspect of this application provides an electronic device, including: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to perform the sea ice freeboard estimation method as described in the above embodiments.

[0022] A third aspect of this application provides a computer-readable storage medium having a computer program stored thereon, which is executed by a processor to perform the sea ice freeboard estimation method as described in the above embodiments.

[0023] A fourth aspect of this application provides a computer program product, including a computer program or instructions, characterized in that, when the computer program or instructions are executed, they implement the sea ice freeboard estimation method as described in the above embodiments.

[0024] Therefore, this application has at least the following beneficial effects:

[0025] This application embodiment can utilize a receiver to receive measurement data from a Global Navigation Satellite System (GNSS) and calculate positioning data based on the GNSS measurement data. It calculates the current antenna height above the ice surface based on the measurement data, and then calculates the current reflector elevation based on the antenna height above the ice surface and the positioning data. Finally, it estimates the sea ice freeboard based on the current reflector elevation and a reference sea surface elevation. Automated data acquisition and processing can be achieved using only GNSS equipment. This is particularly useful for offshore platforms such as ships, buoys, and ice stations, eliminating the need for additional data acquisition of parameters such as draft. It fully leverages the positioning function of direct GNSS signals and the elevation difference measurement function of reflected GNSS signals. The system boasts high stability, more accurate real-time measurements, and requires no long-term manual maintenance. It is especially suitable for situations where manual measurement is inconvenient, such as large waves, demonstrating high applicability and practicality.

[0026] Additional aspects and advantages of this application will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of this application. Attached Figure Description

[0027] The above and / or additional aspects and advantages of this application will become apparent and readily understood from the following description of the embodiments taken in conjunction with the accompanying drawings, wherein:

[0028] Figure 1 This is a flowchart of a sea ice freeboard estimation method provided according to an embodiment of this application;

[0029] Figure 2 This is a flowchart of an automated sea ice freeboard inversion method based on GNSS, provided according to an embodiment of this application.

[0030] Figure 3This is a schematic diagram of the algorithm provided according to the embodiments of this application and a diagram showing the relative relationship between the main reference planes;

[0031] Figure 4 This is a schematic diagram of the structure of an electronic device provided according to an embodiment of this application. Detailed Implementation

[0032] The embodiments of this application are described in detail below. Examples of these embodiments are shown in the accompanying drawings, wherein the same or similar reference numerals denote the same or similar elements or elements having the same or similar functions throughout. The embodiments described below with reference to the accompanying drawings are exemplary and intended to explain this application, and should not be construed as limiting this application.

[0033] The following description, with reference to the accompanying drawings, outlines a sea ice freeboard estimation method, apparatus, vehicle, storage medium, and program according to embodiments of this application. Addressing the issues mentioned in the background section regarding the susceptibility of sea ice freeboard estimation results to interference from equipment, signal sources, and the environment, leading to low real-time performance, inaccurate measurement results, and significant limitations, this application provides a sea ice freeboard estimation method. In this method, a receiver receives measurement and positioning data from a Global Navigation Satellite System (GNSS). The height of the receiver's antenna above the ice surface at the current moment is calculated based on the measurement data. The reflector elevation of the receiver at the current moment is calculated based on the antenna height above the ice surface and the positioning data. The sea ice freeboard is estimated based on the reflector elevation of the receiver at the current moment and the reference sea surface elevation. This method requires only GNSS equipment for automated data acquisition and processing, fully utilizing the positioning function of direct GNSS signals and the elevation difference measurement function of reflected GNSS signals. The system exhibits high stability, more accurate real-time measurements, requires no long-term manual maintenance, and has high applicability and practicality. Therefore, it solves the problems in related technologies where sea ice freeboard estimation results are easily affected by interference from equipment, signal sources, and the environment, resulting in low real-time performance, inaccurate measurement results, and significant limitations.

[0034] Specifically, Figure 1 This is a flowchart illustrating a sea ice freeboard estimation method provided in an embodiment of this application.

[0035] like Figure 1 As shown, the sea ice freeboard estimation method includes the following steps:

[0036] In step S101, the receiver receives GNSS measurement data from the Global Navigation Satellite System and calculates positioning data based on the GNSS measurement data.

[0037] It is understood that the embodiments of this application can utilize a receiver to receive measurement data from the Global Navigation Satellite System (GNSS) and calculate positioning data based on the GNSS measurement data. Real-time data acquisition and processing are applicable to dynamic environmental monitoring and have high applicability.

[0038] It should be noted that only the ship's altitude and antenna altitude need to be collected once before navigation. During sea ice observation, only real-time GNSS data of the sea ice surface needs to be collected, including real-time GNSS data and antenna altitude. The real-time GNSS data includes observation files in RINEX format (O file) and satellite ephemeris files (n file or sp3 file), which are automatically generated by the GNSS receiver installed on board and have a sampling frequency of 30 seconds, without specific limitations. The positioning method is determined by the navigation range: dynamic differential positioning is preferred to ensure high accuracy; when the ship's movement range is wide and base stations are frequently changed, precise single-point positioning is used.

[0039] Specifically, such as Figure 2 As shown, the data acquisition and preprocessing in this application include:

[0040] (1) Calculation of receiver geodetic height H_GNSS at the location of the flight path: You can choose any precise single-point positioning software, such as NETDIFF, RTKLIB, etc., and input the RINEX format observation file and satellite ephemeris file in step one to return the position coordinates (Xr, Yr, Zr) at each moment.

[0041] (2) Calculate the real-time elevation angle and azimuth angle of the satellite. Based on the calculated position of the ship's receiver (Xr, Yr, Zr) and the satellite position (Xs, Ys, Zs) provided by the ephemeris file, calculate the real-time elevation angle (Hs) and azimuth angle (As) of the satellite.

[0042]

[0043] (3) Preprocess and control the quality of GNSS signals in real time, taking into account the antenna installation and ship course. Specifically, this includes: screening satellite elevation angles, removing satellite signals with elevation angles greater than 30° or less than 5°. Excessive elevation angles result in weak signal reflection, while excessively small elevation angles cause the reflection point to be too far from the receiver, both leading to decreased accuracy; screening azimuth angles, as there may be obstructions near the antenna, should be done in conjunction with the actual installation conditions.

[0044] (4) Extract valid data and remove useless data. Extract the elevation angle, azimuth angle and signal-to-noise ratio data of each satellite and each signal for each epoch to prepare data for subsequent GNSS-IR elevation difference calculation; remove other useless data to reduce the amount of calculation.

[0045] In step S102, the height of the receiver's antenna above the ice surface at the current moment is calculated based on the measurement data, and the elevation of the receiver's reflector surface at the current moment is calculated based on the height of the antenna above the ice surface and the positioning data.

[0046] It is understood that the embodiments of this application can calculate the height of the receiver's antenna above the ice surface at the current moment based on the measurement data, and calculate the elevation of the receiver's reflector surface at the current moment based on the height of the antenna above the ice surface and the positioning data, thus meeting the needs of real-time calculation and being suitable for long-term sequence monitoring, so as to improve the accuracy of subsequent estimation of sea ice freeboard.

[0047] In this embodiment of the application, the calculation of the antenna height of the receiver above the ice surface at the current time based on measurement data includes: identifying the main signal frequency of each satellite in the measurement data during the target time period; calculating the antenna height of the corresponding receiver above the ice surface based on the main signal frequency of each satellite during the target time period; and weightedly fusing the antenna heights above the ice surface calculated from multiple satellites to generate the antenna height of the receiver above the ice surface at the current time.

[0048] It is understood that the embodiments of this application can identify the main signal frequency of each satellite in the measurement data during the target time period; calculate the antenna height of the corresponding receiver to the ice surface based on the main signal frequency of each satellite during the target time period; and weight and fuse the antenna heights of the receiver to the ice surface calculated from multiple satellites to generate the antenna height of the receiver to the ice surface at the current moment, thereby improving the accuracy of the antenna height calculation result.

[0049] Specifically, such as Figure 2 As shown, (1) the main frequency is calculated to obtain the height difference:

[0050]

[0051] Where H is the height difference between the antenna and the reflector; λ is the wavelength of the satellite signal. The wavelengths of different signals in different satellite systems are different. The specific value needs to be checked on the website of each GNSS system according to the satellite used; ω is the main frequency of the signal obtained in step 2.4.

[0052] (2) For multiple inversion results in the same window, the robust least squares method is used for fusion.

[0053] For each signal from each satellite, the state transition equations are as follows:

[0054]

[0055] in, A i =(M i ,1), h represents the height difference inversion result of the j-th signal in the i-th window. i h represents the height difference of the reflecting surface at the corresponding time of the i-th window. i e represents the rate of change of the reflective surface elevation difference at the time corresponding to the i-th window. i,j and t represents the elevation angle and the rate of change of the elevation angle, respectively. i,j t represents the midpoint of the signal segment. i This indicates the midpoint of the window.

[0056] This method not only leverages the multi-mode and multi-frequency advantages of GNSS systems but also dynamically weights different observation signals. To address the issue of varying observation accuracy for different signals, a robust regression strategy is introduced to automatically weight different observation signals.

[0057] Here, a bisquared weighting method is used to allocate weights, with points farther from the model's prediction point receiving lower weights. When the residual v after the k-th iteration... i (k) When the absolute value is less than 1, the weight is (1-(v)). i (k) )) 2 When the absolute value of the residual is greater than 1, the weight is 0. After the weight is determined, the solution of the (k+1)th iteration is recalculated using the weighted least squares method. The iteration continues until the difference between the estimated value and the previous estimated value stabilizes within a very small range.

[0058] In this embodiment of the application, identifying the dominant signal frequency of each satellite in the measurement data during the target time period includes: extracting the elevation angle, azimuth angle, and signal-to-noise ratio data of each satellite in the measurement data; using overlapping sliding windows to segment the sequence composed of the elevation angle and signal-to-noise ratio data of each satellite to generate the corresponding sea surface height sequence segment; and performing spectral analysis on the sequence segment of each sliding window to extract the dominant signal frequency.

[0059] It is understood that the embodiments of this application can extract the elevation angle, azimuth angle and signal-to-noise ratio data of each satellite in the measurement data; use overlapping sliding windows to segment the sequence composed of the elevation angle and signal-to-noise ratio data of each satellite to generate the corresponding sea surface height sequence segment; perform spectrum analysis on the sequence segment of each sliding window to extract the main frequency of the signal, thereby increasing the total amount of signal, effectively improving the signal utilization and resolution, and ensuring the inversion accuracy.

[0060] It's important to note that traditional land-based static GNSS-R technology primarily employs temporal clustering for altimetry: first, all quality-controlled satellite signals are processed, and their corresponding times are calculated. Then, all results are clustered by time, and the average of the results within each cluster is used as the representative result. The total signal count depends on the number of times the satellite is observed by the receiver, which is a constant. To improve temporal resolution, the number of clusters must be increased. However, in clustering algorithms, when the total number of observations is constant, more clusters result in fewer elements per cluster. In other words, when the total number of observations is constant, improving temporal resolution inevitably reduces the number of observations per unit time period, leading to a decrease in accuracy. Therefore, in clustering algorithms, improving temporal resolution requires sacrificing accuracy. Furthermore, in traditional methods, the length of the arc segment cannot be adjusted. The arc segment length reflects the time span of satellite ascent or descent, an objective quantity. Excessively long arc segments can only be discarded, not adjusted. This greatly increases the likelihood that the signal will fail to pass quality control.

[0061] To improve temporal resolution while maintaining a sufficient number of observation samples per unit time period, this study employs a sliding time window to segment and adjust the arc segments. Unlike the temporal clustering algorithm's approach of "first solving the signal, then classifying the results," the sliding window algorithm adopts the approach of "first segmenting the signal, then solving the segments": first, a sliding window is used to truncate and segment the signal arc segments, establishing an equation set for each window; then, a combined result is calculated for each window.

[0062] The time window algorithm in this experiment works as follows: First, a sliding window is used to separate the sea level height sequence into different segments, establishing an equation set for each window. Then, a combined reflector height is calculated for each window. The window width should be large enough to include sufficient retrieval points for combination; however, the window width should not be too large, otherwise it will not reflect rapid changes in the reflector. The spacing of the sliding windows is related to the sampling interval required for the final output. The ephemeris interval should be less than or at most equal to this sampling interval. This study uses a moving time window with an interval of 10 minutes and a width of 1 hour. This time interval and width are not only suitable for daily monitoring but also for monitoring rapidly changing reflectors such as sea level.

[0063] The sliding window algorithm has several advantages over traditional temporal clustering algorithms:

[0064] 1. By truncating the entire arc segment, multiple results can be retrieved from a single arc segment, effectively increasing the total signal volume.

[0065] 2. By adjusting the window width, the length of the arc segments can be adjusted, instead of directly discarding arc segments that are too long or too short, which effectively improves signal utilization.

[0066] 3. The time resolution can be flexibly adjusted by changing the window translation span (step size); and the number of signals within the window will not be significantly affected by the reduction of the step size. While improving the time resolution, it still ensures a sufficient number of observation samples per unit time period to guarantee inversion accuracy.

[0067] Specifically, such as Figure 2 The following are the specific steps for identifying the dominant frequency of a signal in the measurement data:

[0068] (1) Preprocess and quality control of GNSS signals in real time based on antenna installation and ship course;

[0069] Besides the sea ice surface and the hull, signal reflection at the ice-water interface also occurs to some extent due to signal transmission, causing signal interference to the sea ice surface detection. To fully utilize the signal from surfaces exhibiting stratification, this study employs quality control to screen reflective surfaces. When selecting peak values ​​from the signal spectrum, a reasonable range is chosen based on actual conditions, eliminating interference from reflected signals from other surfaces and maximizing signal utilization.

[0070] (2) Extract the elevation angle, azimuth angle and signal-to-noise ratio data of each satellite and each signal on an epoch-by-epoch basis;

[0071] (3) Signal capture using overlapping sliding windows. This algorithm first segments the signal and then solves the segments, improving computational efficiency. The temporal resolution and accuracy of the inversion results are not directly related; the former is related to the step size of the sliding window, while the latter is related to the width of the sliding window. Furthermore, the window should have an appropriate width; it should not be too small to fully utilize the search points, but it should not be too large to avoid failing to track the dynamic changes of the reflector surface. Here, the signal refers to the sequence of elevation angle and signal-to-noise ratio data for each satellite; this step involves data segmentation of the sequence.

[0072] In shipborne dynamic sea ice freeboard inversion, the receiver position and altitude constantly change with the ship's motion. To adapt to the rapidly changing reflector surface conditions, this study employs an overlapping sliding window truncation method instead of the traditional temporal clustering method, improving temporal resolution without sacrificing inversion accuracy.

[0073] (4) The Lomb-Scargle periodogram (LSP) method was used to perform spectral analysis on the signal-to-noise ratio sequence segment. This method can analyze non-periodic signals and filter out noise present in the signal.

[0074] In step S103, the sea ice freeboard is estimated based on the current receiver reflector elevation and the reference sea surface elevation.

[0075] like Figure 3 As shown in the embodiments of this application, the formula for calculating the sea ice freeboard is:

[0076] freeboard = H reflector -H SEA ;

[0077] Among them, H reflector H represents the elevation of the receiver's reflector surface at the current moment. SEA It represents the instantaneous elevation of the sea surface, that is, the distance from the instantaneous sea surface to the reference ellipsoid.

[0078] In this embodiment, the formula for calculating the elevation of the reflecting surface is:

[0079] H reflector =H GNSS -h GNSS-IR ;

[0080] Among them, H GNSS h is the ellipsoidal height of the GNSS antenna phase center. GNSS-IR This represents the height difference between the antenna and the reflector.

[0081] It should be noted that the receiver's ground height H GNSS The solution was obtained using Precise Point Positioning (PPP). PPP technology is an ideal choice because it does not rely on ground base stations and does not require the establishment and maintenance of a complex ground base station network, enabling it to provide high-precision positioning services in environments with insufficient base station coverage, such as Antarctica. Furthermore, for ships moving over large areas, PPP technology can avoid errors caused by excessively long baselines or frequent changes in reference stations.

[0082] In this embodiment of the application, the formula for calculating the instantaneous elevation of the sea surface is:

[0083] H SEA =MSL+h tide ≈N+h tide ;

[0084] Where h_tide represents the tidal height at the location the trajectory passes through, MSL represents the distance from the mean sea level to the reference ellipsoid, and N represents the geoid distance. In open sea, the geoid distance N can be used instead of the mean sea level ellipsoid height MSL.

[0085] It is understood that the embodiments of this application can fully utilize the positioning function of GNSS direct signals and the elevation difference measurement function of GNSS reflected signals. The system has high stability, requires no long-term manual maintenance, and has high applicability and practicality.

[0086] Specifically, such as Figure 2 As shown, the elevation of the reflecting surface can be obtained by subtracting the elevation difference calculated by GNSS-IR technology from the GNSS positioning result on the elevation.

[0087] H reflector =H GNSS -h GNSS-IR

[0088] Subtracting the elevation of the reflecting surface from the reference sea level gives the sea ice drywall value.

[0089] freeboard = H reflector -H SEA

[0090] Among them, H GNSS The ellipsoidal height of the GNSS antenna phase center is obtained from the GNSS elevation positioning results. GNSS-IR The height difference between the antenna and the reflector is obtained using GNSS-IR altimetry technology. bias The calculation method for this parameter, which accounts for the dynamic deviation caused by sea surface fluctuations during the measurement process, will be described in detail in Section 3.3. H SEA H represents the instantaneous elevation of the sea surface, that is, the distance from the instantaneous sea surface to the reference ellipsoid. SEA It can be obtained by superimposing the mean sea level ellipsoid height and the tide height, that is:

[0091] H SEA =MSL+h tide

[0092] Where h tide The height representing tidal variations can be obtained using a global tidal model. MSL represents the distance from mean sea level to the reference ellipsoid. In open seas, the geoid distance N can be used to replace the ellipsoidal height MSL of mean sea level, i.e.:

[0093] H SEA ≈N+h tide

[0094] In this embodiment of the application, before estimating the sea ice freeboard based on the current receiver reflector elevation and reference sea surface elevation, the method further includes: inputting positioning data into a preset model, and the preset model outputting the tidal height and geoid distance of the corresponding trajectory location.

[0095] The preset model can be either a global tide model or a global sea level height model, whichever is selected according to the needs, without any specific limitations.

[0096] It is understood that, in the embodiments of this application, positioning data can be input into a preset model, and the preset model can output the tidal height and geoid distance of the corresponding trajectory location, thereby improving processing accuracy.

[0097] Specifically, (1) the elevation of the reflecting surface can be obtained by subtracting the elevation difference calculated by GNSS-IR technology from the GNSS positioning result on the elevation.

[0098] (2) Calculation of tidal height h_tide at the location traversed by the navigation trajectory: Based on the GNSS positioning results and combined with the global tide model, the tidal height at the location traversed by the trajectory is calculated. The specific calculation method can use the classic tidal harmonic analysis model t_tide, which can be directly called in the t_tide toolkit on the MATLAB platform. Input the position coordinates into the model to return the tidal height at that location.

[0099] (3) Calculation of the geoid distance N at the locations traversed by the navigation trajectory. Based on the GNSS positioning results and the global sea level model, the geoid distance at the locations traversed by the trajectory is calculated. Specifically, the classic geoid distance model EGM2008 can be used, which can be directly called in the MATLAB platform. Inputting the location coordinates into the model will return the geoid distance at that location.

[0100] The sea ice freeboard estimation method proposed in this application utilizes a receiver to receive measurement and positioning data from a Global Navigation Satellite System (GNSS). Based on the measurement data, the height of the receiver's antenna above the ice surface at the current moment is calculated. Then, based on the antenna height above the ice surface and the positioning data, the elevation of the receiver's reflector surface at the current moment is calculated. Finally, the sea ice freeboard is estimated based on the receiver's reflector surface elevation and a reference sea surface elevation. This method requires only GNSS equipment to achieve automated data acquisition and processing, fully leveraging the positioning function of direct GNSS signals and the elevation difference measurement function of reflected GNSS signals. The system exhibits high stability, more accurate real-time measurements, requires no long-term manual maintenance, and has high applicability and practicality.

[0101] Figure 4 A schematic diagram of the structure of an electronic device provided in an embodiment of this application. The electronic device may include:

[0102] The memory 401, the processor 402, and the computer program stored on the memory 401 and capable of running on the processor 402.

[0103] When processor 402 executes the program, it implements the sea ice freeboard estimation method provided in the above embodiments.

[0104] Furthermore, electronic devices also include:

[0105] Communication interface 403 is used for communication between memory 401 and processor 402.

[0106] The memory 401 is used to store computer programs that can run on the processor 402.

[0107] The memory 401 may include high-speed RAM memory, and may also include non-volatile memory, such as at least one disk storage device.

[0108] If the memory 401, processor 402, and communication interface 403 are implemented independently, then the communication interface 403, memory 401, and processor 402 can be interconnected via a bus to complete communication between them. The bus can be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus, or an Extended Industry Standard Architecture (EISA) bus, etc. Buses can be divided into address buses, data buses, control buses, etc. For ease of representation, Figure 4 The bus is represented by a single thick line, but this does not mean that there is only one bus or one type of bus.

[0109] Optionally, in a specific implementation, if the memory 401, processor 402, and communication interface 403 are integrated on a single chip, then the memory 401, processor 402, and communication interface 403 can communicate with each other through an internal interface.

[0110] Processor 402 may be a central processing unit (CPU), an application specific integrated circuit (ASIC), or one or more integrated circuits configured to implement the embodiments of this application.

[0111] This application also provides a computer-readable storage medium storing a computer program or instructions thereon, which, when executed by a processor, implements the above-described sea ice freeboard estimation method.

[0112] This application also provides a computer program product, including a computer program or instructions, characterized in that, when the computer program or instructions are executed, they implement the above-mentioned sea ice freeboard estimation method.

[0113] In the description of this specification, the references to terms such as "one embodiment," "some embodiments," "example," "specific example," or "some examples," etc., indicate 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 this application. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples. Moreover, without contradiction, those skilled in the art can combine and integrate the different embodiments or examples described in this specification, as well as the features of different embodiments or examples.

[0114] Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include at least one of that feature. In the description of this application, "N" means at least two, such as two, three, etc., unless otherwise explicitly specified.

[0115] Any process or method described in the flowchart or otherwise herein can be understood as representing a module, segment, or portion of code comprising one or N executable instructions for implementing custom logic functions or processes, and the scope of the preferred embodiments of this application includes additional implementations in which functions may be performed not in the order shown or discussed, including substantially simultaneously or in reverse order depending on the functions involved, as should be understood by those skilled in the art to which embodiments of this application pertain.

[0116] It should be understood that the various parts of this application can be implemented using hardware, software, firmware, or a combination thereof. In the above embodiments, the N steps or methods can be implemented using software or firmware stored in memory and executed by a suitable instruction execution system. For example, if implemented in hardware, as in another embodiment, it can be implemented using any one or more of the following techniques known in the art: discrete logic circuits having logic gates for implementing logical functions on data signals, application-specific integrated circuits (ASICs) having suitable combinational logic gates, programmable gate arrays (PGAs), field-programmable gate arrays (FPGAs), etc.

[0117] Those skilled in the art will understand that all or part of the steps of the methods in the above embodiments can be implemented by a program instructing related hardware. The program can be stored in a computer-readable storage medium, and when executed, the program includes one or a combination of the steps of the method embodiments.

Claims

1. A method for estimating sea ice freeboard, characterized in that, Includes the following steps: The receiver receives GNSS measurement data from the Global Navigation Satellite System and calculates positioning data based on the GNSS measurement data; Calculate the height of the receiver's antenna above the ice surface at the current moment based on the measurement data, and calculate the elevation of the receiver's reflector surface at the current moment based on the height of the antenna above the ice surface and the positioning data; Estimate the sea ice freeboard based on the current receiver reflector elevation and reference sea surface elevation.

2. The sea ice freeboard estimation method according to claim 1, characterized in that, The step of calculating the height of the receiver's antenna above the ice surface at the current moment based on the measurement data includes: Identify the dominant signal frequency of each satellite in the measurement data within the target time period; The height of the receiver antenna above the ice surface is calculated based on the main signal frequency of each satellite during the target time period. The antenna heights above the ice surface of the receiver, calculated from multiple satellites, are weighted and fused to generate the current antenna height above the ice surface of the receiver.

3. The sea ice freeboard estimation method according to claim 2, characterized in that, The dominant signal frequency of each satellite in the target time period in the identification measurement data includes: Extract the elevation angle, azimuth angle, and signal-to-noise ratio data of each satellite and each signal from the measurement data; The sequence of elevation angle and signal-to-noise ratio data of each satellite is segmented using an overlapping sliding window to generate the corresponding sea surface height sequence segment; Spectral analysis is performed on the sequence segments of each sliding window to extract the main frequency of the signal.

4. The sea ice freeboard estimation method according to claim 1, characterized in that, The formula for calculating the sea ice freeboard is: freeboard=H reflector -H SEA ; Among them, H reflector H represents the elevation of the receiver's reflecting surface at the current moment. SEA It represents the instantaneous elevation of the sea surface, that is, the distance from the instantaneous sea surface to the reference ellipsoid.

5. The sea ice freeboard estimation method according to claim 4, characterized in that, The formula for calculating the elevation of the reflecting surface is: H reflector =H GNSS -h GNSS-IR ; Among them, H GNSS h is the ellipsoidal height of the GNSS antenna phase center. GNSS-IR This represents the height difference between the antenna and the reflector.

6. The sea ice freeboard estimation method according to claim 5, characterized in that, The formula for calculating the instantaneous elevation of the sea surface is: H SEA =MSL+h tide ≈N+h tide ; Among them, h tide The tidal height represents the location the trajectory passes through, MSL represents the distance from the mean sea level to the reference ellipsoid, and N represents the geoid distance. In open sea, the geoid distance N can be used instead of the mean sea level ellipsoid height MSL.

7. The sea ice freeboard estimation method according to claim 1, characterized in that, Before estimating the sea ice freeboard based on the reflector elevation of the receiver at the current moment and the reference sea surface elevation, the following steps are also included: The positioning data is input into a preset model, and the preset model outputs the tidal height and geoid distance of the corresponding trajectory location.

8. An electronic device, characterized in that, include: A memory, a processor, and a computer program stored in the memory and executable on the processor, the processor executing the program to implement the sea ice freeboard estimation method as described in any one of claims 1-7.

9. A computer-readable storage medium having a computer program or instructions stored thereon, characterized in that, When the computer program or instructions are executed by the processor, they are used to implement the sea ice freeboard estimation method as described in any one of claims 1-7.

10. A computer program product, comprising a computer program or instructions, characterized in that, When the computer program or instructions are executed, they implement the sea ice freeboard estimation method as described in any one of claims 1-7.

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