Sea ice thickness estimation method and device based on GNSS reflection remote sensing technology

Abstract

The present application relates to the field of sea ice detection technology, and in particular to a method and device for estimating the thickness of sea ice based on GNSS reflection remote sensing technology, wherein the method comprises: collecting target data of a ship during navigation in a target sea area, wherein the target data comprises real-time GNSS data, hull height, antenna height and ship draft; obtaining the dynamic sea surface height difference of the target sea area based on real-time GNSS data; estimating the sea ice thickness of the target sea area based on the hull height, antenna height, ship draft and dynamic sea surface height difference. Thus, the problems in the related technology that the ice core drilling method has spatial limitations, the real-time performance of satellite remote sensing data in polar regions is poor, and the ship-borne sea ice camera technology is easily affected by weather are solved.

Description

Technical Field

[0001] The present application relates to the field of sea ice detection technology, and in particular to a method and device for estimating sea ice thickness based on GNSS (Global Navigation Satellite System) reflection remote sensing technology. Background Art

[0002] Sea ice information perception is the primary issue to be overcome in realizing ship intelligence, and is also one of the key technologies to ensure maritime traffic safety. It can provide critical safety information for ship navigation, effectively guide ships to choose the safest and most economical routes, significantly improve navigation efficiency, and reduce navigation risks.

[0003] In the related technologies, sea ice detection can be carried out through ice core drilling method, sea ice thickness can be detected based on satellite remote sensing data, and the situation of sea ice can be collected in real time using ship-borne sea ice camera technology. With the development of GNSS, GNSS reflection remote sensing technology has the advantages of stable signal source, low receiver cost, low installation difficulty, good real-time performance, and is very suitable for being carried on the hull, providing a variety of reference information for ship navigation. Therefore, the ship navigation environment information perception technology combined with GNSS information has become an important technical means for ship intelligent navigation, providing strong support for ship intelligent navigation.

[0004] However, among the related technologies, the ice core drilling method has spatial limitations; satellite remote sensing data in polar regions and other areas are difficult to download quickly and lack real-time performance; ship-borne sea ice camera technology is easily affected by rainfall, sea fog, darkness, etc., resulting in low camera visibility and unstable signal source; and GNSS reflection remote sensing technology is limited in use in the field of sea ice freeboard and sea ice thickness estimation, and urgently needs to be improved. Summary of the invention

[0005] The present application provides a method and device for estimating sea ice thickness based on GNSS reflection remote sensing technology, in order to solve the problems in related technologies, such as the ice core drilling method having spatial limitations, the poor real-time performance of satellite remote sensing data in polar regions, and the ship-borne sea ice camera technology being easily affected by weather.

[0006] A first aspect of the present application provides a method for estimating sea ice thickness based on GNSS reflection remote sensing technology, comprising the following steps: collecting target data of a ship during its navigation in a target sea area, wherein the target data may include but is not limited to real-time GNSS data, hull height, antenna height and ship draft; obtaining a dynamic sea surface height difference in the target sea area based on the real-time GNSS data; and estimating the sea ice thickness in the target sea area based on the hull height, the antenna height, the ship draft and the dynamic sea surface height difference.

[0007] Optionally, in one embodiment of the present application, obtaining the dynamic sea surface height difference of the target sea area based on the real-time GNSS data includes: obtaining the altitude angle, azimuth angle of each GNSS satellite and initial signal-to-noise ratio data of different satellite signals in the GNSS satellite based on the real-time GNSS data; performing a first preprocessing on the initial signal-to-noise ratio data to obtain signal-to-noise ratio data that meets a first preset condition; performing a second preprocessing on the GNSS signal in the signal-to-noise ratio data based on the altitude angle and the azimuth angle to obtain a processed GNSS signal that meets a second preset condition; obtaining at least one signal segment corresponding to at least one window based on the processed GNSS signal; determining the main frequency of the at least one signal segment based on the at least one signal segment; and obtaining the initial dynamic sea surface height difference of the at least one signal segment based on the main frequency.

[0008] Optionally, in one embodiment of the present application, the dynamic sea surface height difference of the target sea area obtained based on the real-time GNSS data further includes: obtaining a weight value of the initial dynamic sea surface height difference of different signal segments in the same window based on the initial dynamic sea surface height difference; and obtaining the dynamic sea surface height difference corresponding to each window based on the weight value.

[0009] Optionally, in one embodiment of the present application, the estimating the sea ice thickness of the target sea area based on the hull height, the antenna height, the ship draft and the dynamic sea surface height difference includes: obtaining the sea ice freeboard of the target sea area based on the hull height, the antenna height, the ship draft and the dynamic sea surface height difference; and estimating the sea ice thickness of the target sea area based on the sea ice freeboard.

[0010] Optionally, in one embodiment of the present application, the calculation formula of the sea ice freeboard may be, but is not limited to,:

[0011] h f =h ship +h ant -h GNSS-IR -h daraft -h bias ,

[0012] Among them, h ship is the height of the ship, i.e. the height difference between the bottom of the GNSS antenna and the bottom of the ship; h ant h is the antenna height, i.e. the height of the antenna phase center from the deck surface; daraft h is the draft of the ship, i.e. the distance from the water surface to the bottom of the ship; bias Dynamic sea level correction, i.e. the deviation between the static estimate and the actual sea level height;

[0013] The estimation formula of the sea ice thickness may be, but is not limited to,:

[0014]

[0015] Among them, ρ ω is the density of seawater, ρ i is the density of sea ice, h f is the freeboard of sea ice, and H is the thickness of sea ice.

[0016] The second aspect of the present application provides a sea ice thickness estimation device based on GNSS reflection remote sensing technology, including: a collection module, used to collect target data of a ship during its navigation in a target sea area, wherein the target data may include but is not limited to real-time GNSS data, hull height, antenna height and ship draft; a generation module, used to obtain the dynamic sea surface height difference of the target sea area based on the real-time GNSS data; an estimation module, used to estimate the sea ice thickness of the target sea area based on the hull height, the antenna height, the ship draft and the dynamic sea surface height difference.

[0017] Optionally, in one embodiment of the present application, the generation module includes: a first generation unit, used to obtain the altitude angle, azimuth angle of each GNSS satellite and initial signal-to-noise ratio data of different satellite signals in the GNSS satellite based on the real-time GNSS data; a first preprocessing unit, used to perform a first preprocessing on the initial signal-to-noise ratio data to obtain signal-to-noise ratio data that meets a first preset condition; a second preprocessing unit, used to perform a second preprocessing on the GNSS signal in the signal-to-noise ratio data based on the altitude angle and the azimuth angle to obtain a processed GNSS signal that meets a second preset condition; a second generation unit, used to obtain at least one signal segment corresponding to at least one window based on the processed GNSS signal; a determination unit, used to determine the main frequency of the at least one signal segment according to the at least one signal segment; and a third generation unit, used to obtain the initial dynamic sea surface height difference of the at least one signal segment based on the main frequency.

[0018] Optionally, in one embodiment of the present application, the generation module also includes: a fourth generation unit, used to obtain the weight value of the initial dynamic sea surface height difference of different signal segments in the same window based on the initial dynamic sea surface height difference; and a fifth generation unit, used to obtain the dynamic sea surface height difference corresponding to each window based on the weight value.

[0019] Optionally, in one embodiment of the present application, the estimation module includes: a calculation unit, used to obtain the sea ice freeboard of the target sea area based on the hull height, the antenna height, the ship draft and the dynamic sea surface height difference; an estimation unit, used to estimate the sea ice thickness of the target sea area based on the sea ice freeboard.

[0020] Optionally, in one embodiment of the present application, the calculation formula of the sea ice freeboard may be, but is not limited to,:

[0021] h f =h ship +h ant -h GNSS-IR -h daraft -h bias ,

[0022] Among them, h ship is the height of the ship, i.e. the height difference between the bottom of the GNSS antenna and the bottom of the ship; h ant h is the antenna height, i.e. the height of the antenna phase center from the deck surface; daraft h is the draft of the ship, i.e. the distance from the water surface to the bottom of the ship; boas Dynamic sea level correction, i.e. the deviation between the static estimate and the actual sea level height;

[0023] The estimation formula of the sea ice thickness may be, but is not limited to,:

[0024]

[0025] Among them, ρ ω is the density of seawater, ρ i is the density of sea ice, h f is the freeboard of sea ice, and H is the thickness of sea ice.

[0026] The third aspect of the present application provides an electronic device, comprising: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the sea ice thickness estimation method based on GNSS reflection remote sensing technology as described in the above embodiment.

[0027] The fourth aspect embodiment of the present application provides a computer-readable storage medium, which stores a computer program, and when the program is executed by a processor, it implements the above-mentioned sea ice thickness estimation method based on GNSS reflection remote sensing technology.

[0028] The fifth aspect of the present application provides a computer program product, including a computer program, which, when executed, implements the above-mentioned sea ice thickness estimation method based on GNSS reflection remote sensing technology.

[0029] The embodiment of the present application can collect target data of the ship in the target sea area in real time during the navigation process, and then obtain the dynamic sea surface height difference of the target sea area, and use the dynamic sea surface height difference to estimate the sea ice thickness of the target sea area. The embodiment of the present application can independently measure all parameters, and the sea ice thickness can be obtained without relying on other models. In addition, the embodiment of the present application can greatly improve the inversion accuracy, spatiotemporal resolution, and real-time performance, verify the applicability and reliability of GNSS reflection remote sensing technology in complex sea ice environments, and provide new technical means for future sea ice monitoring. Therefore, it solves the problems in the related technology that the ice core drilling method has spatial limitations, the real-time performance of satellite remote sensing data in polar regions is poor, and the ship-borne sea ice camera technology is easily affected by weather.

[0030] Additional aspects and advantages of the present application will be given in part in the description below, and in part will become apparent from the description below, or will be learned through the practice of the present application. BRIEF DESCRIPTION OF THE DRAWINGS

[0031] The above and / or additional aspects and advantages of the present application will become apparent and easily understood from the following description of the embodiments in conjunction with the accompanying drawings, in which:

[0032] Figure 1 A flow chart of a method for estimating sea ice thickness based on GNSS reflection remote sensing technology provided according to an embodiment of the present application;

[0033] Figure 2 A flow chart for generating a dynamic sea surface height difference according to an embodiment of the present application;

[0034] Figure 3 A schematic block diagram of a draft method algorithm provided according to an embodiment of the present application;

[0035] Figure 4 A flowchart of the working principle of a method for estimating sea ice thickness based on GNSS reflection remote sensing technology provided according to an embodiment of the present application;

[0036] Figure 5 A schematic block diagram of a sea ice thickness estimation device based on GNSS reflection remote sensing technology provided according to an embodiment of the present application;

[0037] Figure 6 It is a schematic diagram of the structure of an electronic device provided according to an embodiment of the present application. DETAILED DESCRIPTION

[0038] Embodiments of the present application are described in detail below, and examples of the embodiments are shown in the accompanying drawings, wherein the same or similar reference numerals throughout represent the same or similar elements or elements having the same or similar functions. The embodiments described below with reference to the accompanying drawings are exemplary and are intended to be used to explain the present application, and should not be construed as limiting the present application.

[0039] The following describes the sea ice thickness estimation method and device based on GNSS reflection remote sensing technology in the embodiment of the present application with reference to the accompanying drawings. In view of the problems mentioned in the above background technology that the ice core drilling method has spatial limitations, the real-time performance of satellite remote sensing data in polar regions and other regions is poor, and the ship-borne sea ice camera technology is easily affected by weather, the present application provides a sea ice thickness estimation method based on GNSS reflection remote sensing technology, in which the target data of the ship in the target sea area can be collected in real time, and then the dynamic sea surface height difference of the target sea area can be obtained, and the sea ice thickness of the target sea area can be estimated using the dynamic sea surface height difference. The embodiment of the present application can independently measure all parameters, and the sea ice thickness can be obtained without relying on other models. In addition, the embodiment of the present application can greatly improve the inversion accuracy, spatiotemporal resolution, and real-time performance, verifying the applicability and reliability of GNSS reflection remote sensing technology in complex sea ice environments, and providing new technical means for future sea ice monitoring. As a result, the problems in the related technology that the ice core drilling method has spatial limitations, the real-time performance of satellite remote sensing data in polar regions and other regions is poor, and the ship-borne sea ice camera technology is easily affected by weather are solved.

[0040] Specifically, Figure 1 The present invention provides a flow chart of a method for estimating sea ice thickness based on GNSS reflection remote sensing technology according to an embodiment of the present application.

[0041] like Figure 1 As shown, the sea ice thickness estimation method based on GNSS reflection remote sensing technology includes the following steps:

[0042] In step S101, target data of a ship sailing in a target sea area is collected, wherein the target data may include but is not limited to real-time GNSS data, hull height, antenna height and ship draft.

[0043] It can be understood that the target data of the embodiment of the present application may include but is not limited to real-time GNSS data, hull height, antenna height and ship draft, etc., and the present application does not impose any specific limitations.

[0044] As a possible implementation method, the embodiment of the present application can collect target data of the ship in real time during its navigation in the target sea area.

[0045] For example, the embodiment of the present application is based on target data collected on board a ship during a certain ice navigation plan, such as real-time GNSS data, the ship's draft, hull height and antenna height measured monthly during the navigation process. In addition, the height difference from the phase center of the GNSS antenna to the bottom of the ship in the embodiment of the present application can be obtained through ship design drawings and field measurements; the height of the antenna phase center from the deck surface can be obtained by field measurements.

[0046] In step S102, the dynamic sea surface height difference of the target sea area is obtained based on the real-time GNSS data.

[0047] It can be understood that the embodiments of the present application can adopt various algorithms such as sliding time window technology, sea surface dynamic deviation correction, multi-frequency multi-mode robust regression least squares method, etc. to generate the dynamic sea surface height difference of the target sea area, thereby greatly improving the time resolution and inversion accuracy of the height difference inversion of GNSS reflection remote sensing technology.

[0048] As a possible implementation method, the embodiment of the present application can use GNSS reflection remote sensing technology based on real-time GNSS data to perform dynamic sea surface height difference resolution.

[0049] Optionally, in one embodiment of the present application, the dynamic sea surface height difference of the target sea area is obtained based on real-time GNSS data, including: obtaining the altitude angle, azimuth angle of each GNSS satellite and initial signal-to-noise ratio data of different satellite signals in the GNSS satellite based on the real-time GNSS data; performing a first preprocessing on the initial signal-to-noise ratio data to obtain signal-to-noise ratio data that meets a first preset condition; performing a second preprocessing on the GNSS signal in the signal-to-noise ratio data based on the altitude angle and the azimuth angle to obtain a processed GNSS signal that meets a second preset condition; obtaining at least one signal segment corresponding to at least one window based on the processed GNSS signal; determining the main frequency of at least one signal segment based on at least one signal segment; obtaining the initial dynamic sea surface height difference of at least one signal segment based on the main frequency; obtaining a weight value of the initial dynamic sea surface height difference of different signal segments in the same window based on the initial dynamic sea surface height difference; and obtaining the dynamic sea surface height difference corresponding to each window based on the weight value.

[0050] In the actual implementation process, the process of generating a dynamic sea surface height difference based on real-time GNSS data in the embodiment of the present application is as follows: Figure 2 As shown, the steps may be:

[0051] Step S201: Based on the real-time GNSS data, the altitude angle, azimuth angle of each GNSS satellite and the initial signal-to-noise ratio data of different satellite signals in the GNSS satellite at each epoch are extracted, and the initial signal-to-noise ratio data are first preprocessed to obtain signal-to-noise ratio data that meets a first certain condition.

[0052] Among them, the initial signal-to-noise ratio data can be an initial file obtained by each GNSS satellite every day, and the initial file contains all signal-to-noise ratio data of different satellite signals in each GNSS satellite. Therefore, the embodiment of the present application performs a first preprocessing on the initial signal-to-noise ratio data, and then obtains a signal-to-noise ratio file that meets the first certain condition, such as useful signal-to-noise ratio data of all signals of all GNSS satellites. Among them, the first certain condition can be set by technicians in this field according to actual conditions, and this application does not make specific restrictions.

[0053] For example, the embodiment of the present application can extract the altitude angle, azimuth angle and initial signal-to-noise ratio data of each signal of each GNSS satellite at each epoch to produce signal-to-noise ratio data.

[0054] Step S202: performing a second preprocessing on the GNSS signal in the signal-to-noise ratio data based on the altitude angle and the azimuth angle to obtain a processed GNSS signal that meets a second certain condition.

[0055] That is to say, the embodiment of the present application can combine the antenna installation situation and the screening criteria of the azimuth and altitude angles of the ship's heading to adjust in real time, and perform a second preprocessing on the GNSS signal in the signal-to-noise ratio data to obtain a processed GNSS signal that meets the second certain condition. The second certain condition can be set by a person skilled in the art according to actual conditions, and the present application does not impose any specific restrictions.

[0056] For example, the embodiments of the present application can adjust the screening criteria of azimuth and altitude angles in real time in combination with the antenna installation condition and the ship's heading, and then pre-process and quality control the GNSS signals in the signal-to-noise ratio data.

[0057] Among them, in the embodiment of the present application, the range of the altitude angle can be set to 5-45°. If the altitude angle is too low, the reflection point will be too far away from the hull, and the result will not be representative; if the altitude angle is too high, the signal projection phenomenon will be enhanced and the inversion accuracy will be poor.

[0058] In addition, because the antenna of the embodiment of the present application is installed at the front end of the port side of the ship during the experiment, there is obvious obstruction at the rear end and left side of the antenna, and the signal reflection surface within a certain azimuth is the deck or obstacle rather than the ice surface. In addition, the position and sailing direction of the ship are constantly changing, and the azimuth of the satellite relative to the GNSS receiver is also changing all the time. Therefore, the embodiment of the present application can determine the sailing direction of the ship at each moment in real time through the GNSS positioning means, and eliminate the signals whose azimuth is not within the range during the satellite selection process, and try to avoid the interference of the reflected signals of other reflection surfaces on the inversion.

[0059] Step S203: Based on the processed GNSS signal, at least one signal segment corresponding to at least one window is obtained.

[0060] It can be understood that the embodiment of the present application can use overlapping sliding windows to replace the traditional time clustering algorithm to perform overlapping sliding window interception on the processed GNSS signal, thereby improving the time resolution and ensuring the inversion accuracy by ensuring that there are enough observation samples in a unit time period.

[0061] That is to say, the embodiments of the present application can process the processed GNSS signals in a different way from the time clustering algorithm, which is "first solve the signal, then classify the results". The sliding window algorithm adopts the idea of ​​"first segment the signal, then solve the segments": first use a sliding window to intercept and segment the signal arc segments, and establish a set of equations for each window; then, calculate a combination result for each window. The time resolution of the inversion result is related to the moving step size of the sliding window, while the inversion accuracy is related to the width of the sliding window. The time resolution and accuracy no longer have a direct relationship. The width of the window should be large enough to contain enough retrieval points for combination; at the same time, they should not be too large, otherwise they will not reflect the dynamic changes of the reflecting surface.

[0062] For example, the embodiment of the present application can perform overlapping sliding window capture on the signal, which can apply a moving time window. This selection of time interval and width is not only suitable for daily monitoring, but also for monitoring rapid changes in reflective surfaces.

[0063] Step S204: determining a main frequency of at least one signal segment according to at least one signal segment.

[0064] That is to say, the embodiment of the present application can perform spectrum analysis on the signal segments in each window, such as the least square spectrum analysis method, and then extract the main frequency.

[0065] For example, the embodiment of the present application performs spectrum analysis on the signal segments in each window to extract the main frequency. In particular, when selecting the peak value of the signal spectrum graph, the embodiment of the present application should exclude the interference of the reflected signals of other reflection surfaces on the inversion result.

[0066] Step S205: obtaining an initial dynamic sea surface height difference of at least one signal segment based on the main frequency.

[0067] Among them, the embodiment of the present application adopts a dynamic model that takes into account the sea surface fluctuation deviation to replace the traditional model, introduces the dynamic deviation correction caused by the fluctuation of the sea level, and then obtains the corresponding initial dynamic sea surface height difference by solving the main frequency.

[0068] That is to say, in the embodiment of the present application, there is a dynamic deviation h between the static estimated value and the actual sea surface height. bias , and the rate of change of sea surface height It can be used to describe the fluctuation of sea level, and its relationship can be expressed as but not limited to:

[0069]

[0070] in, f is the main frequency after spectrum analysis, is the phase delay, is the rate of change of altitude angle, and h is the dynamic height taking into account the floating of sea surface.

[0071] Furthermore, the embodiment of the present application can estimate the height change rate Then, the static height The time series of minus the dynamic bias is used to obtain the initial dynamic sea surface height difference h, which can be expressed as but not limited to:

[0072]

[0073] For example, the embodiment of the present application can obtain the initial dynamic sea surface height difference by solving the main frequency, wherein the embodiment of the present application adopts a dynamic model that takes into account the sea surface fluctuation deviation to replace the traditional model, and introduces the dynamic deviation correction caused by the fluctuation of the sea level.

[0074] Step S206: Based on the initial dynamic sea surface height difference, the initial dynamic sea surface height difference of different signal segments in the same window is obtained, and then the results of different signals are fused using the least squares method that fuses multiple systems and multiple frequencies to obtain the dynamic sea surface height difference corresponding to each window.

[0075] It can be understood that, in the embodiment of the present application, for the initial dynamic sea surface height difference of different signal segments in the same window, the robust regression least squares method integrating multiple systems and multiple frequencies can be used to fuse them to obtain the dynamic sea surface height difference corresponding to each window.

[0076] In the embodiment of the present application, for each signal on each GNSS satellite, the state transition equation group can be expressed as, but not limited to:

[0077]

[0078] Among them, in the embodiments of the present application,

[0079]

[0080] A i =(M i ,1),

[0081]

[0082] in, represents the height difference inversion result of the jth signal in the i-th window, h i represents the height difference of the reflecting surface at the corresponding moment of the i-th window, represents the change rate of the height difference of the reflecting surface at the corresponding moment of the i-th window, e i,j and Denote the altitude angle and altitude angle change rate respectively, t i,j represents the middle time of the signal segment, t i Indicates the middle moment of the window.

[0083] For example, the embodiment of the present application adopts the least square method of fusing multiple systems and multiple frequencies to fuse the initial dynamic sea surface height difference in the same window. Among them, the embodiment of the present application fuses the GNSS multi-system multi-frequency signals.

[0084] In step S103, the sea ice thickness of the target sea area is estimated based on the hull height, antenna height, ship draft and the dynamic sea surface height difference.

[0085] It can be understood that the embodiment of the present application adopts an inversion model based on draft depth when estimating the sea ice thickness. This method completely utilizes its own measurement data to achieve inversion, does not rely on other models, greatly reduces the unknown parameters in the inversion process, and avoids error accumulation as much as possible.

[0086] In some embodiments, the embodiments of the present application can estimate the sea ice thickness of the target sea area based on the hull height, antenna height, ship draft and dynamic sea surface height difference.

[0087] For example, the embodiment of the present application can calculate the thickness of sea ice in the navigation area based on the dynamic sea surface height difference combined with the static equilibrium equation.

[0088] Optionally, in one embodiment of the present application, estimating the sea ice thickness of the target sea area based on the hull height, antenna height, ship draft and dynamic sea surface height difference includes: obtaining the sea ice freeboard of the target sea area based on the hull height, antenna height, ship draft and dynamic sea surface height difference; estimating the sea ice thickness of the target sea area based on the sea ice freeboard, wherein the calculation formula of the sea ice freeboard may be but is not limited to:

[0089] h f =h ship +h ant -h GNSS-IR -h daraft -h bias ,

[0090] Among them, h ship is the height of the ship, i.e. the height difference between the bottom of the GNSS antenna and the bottom of the ship; h anth is the antenna height, i.e. the height of the antenna phase center from the deck surface; daraft h is the draft of the ship, i.e. the distance from the water surface to the bottom of the ship; bias Dynamic sea level correction, i.e. the deviation between the static estimate and the actual sea level height;

[0091] The estimation formula of sea ice thickness can be, but is not limited to:

[0092]

[0093] Among them, ρ ω is the density of seawater, ρ i is the density of sea ice, h f is the freeboard of sea ice, and H is the thickness of sea ice.

[0094] It can be understood by those skilled in the art that the embodiment of the present application can obtain the sea ice freeboard of the target sea area based on the hull height, antenna height, ship draft and dynamic sea surface height difference, such as Figure 3 As shown, the calculation formula of sea ice freeboard can be but not limited to:

[0095] h f =h ship +h ant -h GNSS-IR -h daraft -h bias ,

[0096] Among them, h ship is the height difference from the phase center of the GNSS antenna to the bottom of the ship, obtained through ship design drawings and field measurements, h ant It is the height of the antenna phase center from the deck surface, obtained by field measurement, h daraft The draft of the ship is the distance from the water surface to the bottom of the ship. It needs to be measured regularly during the voyage, and more detailed measurements are required before and after the time when the weight of the ship changes significantly, such as during unloading and replenishment. bias is the deviation between the static estimate and the actual sea surface height.

[0097] Furthermore, the embodiment of the present application estimates the sea ice thickness based on the sea ice freeboard and the static equilibrium equation, wherein the estimation formula of the sea ice thickness may be, but is not limited to,:

[0098]

[0099] Among them, ρ ω is the density of seawater, ρ i is the density of sea ice, h f is the freeboard of sea ice, and H is the thickness of sea ice.

[0100] Combine the following Figure 4 As shown, the working principle of the sea ice thickness estimation method based on GNSS reflection remote sensing technology proposed in the embodiment of the present application is described in detail with a specific embodiment.

[0101] in, Figure 4 The present invention is a flowchart of the working principle of a method for estimating sea ice thickness based on GNSS reflection remote sensing technology according to an embodiment of the present application.

[0102] Step S401: target data acquisition.

[0103] Step S402: extracting information such as altitude angle, azimuth angle, signal-to-noise ratio, etc., and generating signal-to-noise ratio data.

[0104] Step S403: adjusting the screening criteria of the azimuth angle and the elevation angle in real time in combination with the antenna installation condition and the ship's heading.

[0105] Step S404: performing overlapping sliding window capture on the signal.

[0106] Step S405: Perform spectrum analysis on the signal segments in each window to extract the main frequency.

[0107] Step S406: using a dynamic model that takes into account sea surface fluctuation deviation to calculate the corresponding dynamic sea surface height difference.

[0108] Step S407: The least square method of fusing multiple systems and multiple frequencies is used to fuse the results in the same window to obtain the height difference between the antenna and the ice surface.

[0109] Step S408: measuring the ship's draft, hull height, and antenna height.

[0110] Step S409: Calculate sea ice freeboard.

[0111] Step S410: measuring sea ice snow thickness, snow density and ice density.

[0112] Step S411: Estimation of sea ice thickness.

[0113] According to the sea ice thickness estimation method based on GNSS reflection remote sensing technology proposed in the embodiment of the present application, the target data of the ship in the target sea area during navigation can be collected in real time, and then the dynamic sea surface height difference of the target sea area can be obtained, and the sea ice thickness of the target sea area can be estimated by using the dynamic sea surface height difference. The embodiment of the present application can independently measure all parameters, and the sea ice thickness can be obtained without relying on other models. In addition, the embodiment of the present application can greatly improve the inversion accuracy, spatiotemporal resolution, and real-time performance, verifying the applicability and reliability of GNSS reflection remote sensing technology in complex sea ice environments, and providing new technical means for future sea ice monitoring. Therefore, the problems in the related technology that the ice core drilling method has spatial limitations, the real-time performance of satellite remote sensing data in polar regions is poor, and the ship-borne sea ice camera technology is easily affected by weather are solved.

[0114] Next, a device for estimating the thickness of sea ice based on GNSS reflection remote sensing technology proposed in an embodiment of the present application will be described with reference to the accompanying drawings.

[0115] Figure 5 This is a block diagram of a sea ice thickness estimation device based on GNSS reflection remote sensing technology provided according to an embodiment of the present application.

[0116] like Figure 5 As shown, the sea ice thickness estimation device 10 based on GNSS reflection remote sensing technology includes: a collection module 100, a generation module 200 and an estimation module 300.

[0117] The acquisition module 100 is used to collect target data of the ship during its navigation in the target sea area, wherein the target data may include but is not limited to real-time GNSS data, hull height, antenna height and ship draft.

[0118] The generating module 200 is used to obtain the dynamic sea surface height difference of the target sea area based on the real-time GNSS data.

[0119] The estimation module 300 is used to estimate the sea ice thickness of the target sea area based on the hull height, antenna height, ship draft and dynamic sea surface height difference.

[0120] Optionally, in one embodiment of the present application, the generation module 200 includes: a first generation unit, a first preprocessing unit, a second preprocessing unit, a second generation unit, a determination unit and a third generation unit.

[0121] The first generating unit is used to obtain the altitude angle, azimuth angle of each GNSS satellite and the initial signal-to-noise ratio data of different satellite signals in the GNSS satellite based on the real-time GNSS data.

[0122] The first preprocessing unit is used to perform a first preprocessing on the initial signal-to-noise ratio data to obtain signal-to-noise ratio data that meets a first preset condition.

[0123] The second preprocessing unit is used to perform second preprocessing on the GNSS signal in the signal-to-noise ratio data based on the altitude angle and the azimuth angle to obtain a processed GNSS signal that meets a second preset condition.

[0124] The second generating unit is configured to obtain at least one signal segment corresponding to at least one window based on the processed GNSS signal.

[0125] The determining unit is configured to determine a main frequency of at least one signal segment according to at least one signal segment.

[0126] The third generating unit is used to obtain an initial dynamic sea surface height difference of at least one signal segment based on the main frequency.

[0127] Optionally, in one embodiment of the present application, the generation module 200 further includes: a fourth generation unit and a fifth generation unit.

[0128] The fourth generating unit is used to obtain the weight value of the initial dynamic sea surface height difference of different signal segments in the same window based on the initial dynamic sea surface height difference.

[0129] The fifth generating unit is used to obtain the dynamic sea surface height difference corresponding to each window based on the weight value.

[0130] Optionally, in one embodiment of the present application, the estimation module 300 includes: a calculation unit and an estimation unit.

[0131] Among them, the calculation unit is used to obtain the sea ice freeboard of the target sea area based on the hull height, antenna height, ship draft and dynamic sea surface height difference.

[0132] An estimation unit is used to estimate the sea ice thickness in the target sea area based on the sea ice freeboard.

[0133] Optionally, in one embodiment of the present application, the calculation formula of sea ice freeboard may be, but is not limited to,:

[0134] h f =h ship +h ant -h GNSS-IR -h daraft -h bias ,

[0135] Among them, h ship is the height of the ship, i.e. the height difference between the bottom of the GNSS antenna and the bottom of the ship; h ant h is the antenna height, i.e. the height of the antenna phase center from the deck surface; daraft h is the draft of the ship, i.e. the distance from the water surface to the bottom of the ship; boasDynamic sea level correction, i.e. the deviation between the static estimate and the actual sea level height;

[0136] The estimation formula of sea ice thickness can be, but is not limited to:

[0137]

[0138] Among them, ρ ω is the density of seawater, ρ i is the density of sea ice, h f is the freeboard of sea ice, and H is the thickness of sea ice.

[0139] It should be noted that the aforementioned explanation of the embodiment of the sea ice thickness estimation method based on GNSS reflection remote sensing technology is also applicable to the sea ice thickness estimation device based on GNSS reflection remote sensing technology in this embodiment, and will not be repeated here.

[0140] According to the sea ice thickness estimation device based on GNSS reflection remote sensing technology proposed in the embodiment of the present application, the target data of the ship in the target sea area during navigation can be collected in real time, and then the dynamic sea surface height difference of the target sea area can be obtained, and the sea ice thickness of the target sea area can be estimated by using the dynamic sea surface height difference. The embodiment of the present application can independently measure all parameters, and the sea ice thickness can be obtained without relying on other models. In addition, the embodiment of the present application can greatly improve the inversion accuracy, spatiotemporal resolution, and real-time performance, verifying the applicability and reliability of GNSS reflection remote sensing technology in complex sea ice environments, and providing new technical means for future sea ice monitoring. Therefore, the problems in the related technology that the ice core drilling method has spatial limitations, the real-time performance of satellite remote sensing data in polar regions is poor, and the ship-borne sea ice camera technology is easily affected by weather are solved.

[0141] Figure 6 This is a schematic diagram of the structure of an electronic device provided according to an embodiment of the present application. The electronic device may include:

[0142] A memory 601 , a processor 602 , and a computer program stored in the memory 601 and executable on the processor 602 .

[0143] When the processor 602 executes the program, the sea ice thickness estimation method based on GNSS reflection remote sensing technology provided in the above embodiment is implemented.

[0144] Furthermore, the electronic device further comprises:

[0145] The communication interface 603 is used for communication between the memory 601 and the processor 602 .

[0146] The memory 601 is used to store computer programs that can be executed on the processor 602 .

[0147] The memory 601 may include a high-speed RAM memory, and may also include a non-volatile memory (non-volatile memory), such as at least one disk memory.

[0148] If the memory 601, the processor 602 and the communication interface 603 are implemented independently, the communication interface 603, the memory 601 and the processor 602 can be connected to each other through a bus and communicate with each other. The bus can be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus or an Extended Industry Standard Architecture (EISA) bus. The bus can be divided into an address bus, a data bus, a control bus, etc. For ease of representation, Figure 6 Only one thick line is used in the diagram, but this does not mean that there is only one bus or only one type of bus.

[0149] Optionally, in a specific implementation, if the memory 601, the processor 602 and the communication interface 603 are integrated on a chip, the memory 601, the processor 602 and the communication interface 603 can communicate with each other through an internal interface.

[0150] The processor 602 may be a central processing unit (CPU), or an application specific integrated circuit (ASIC), or one or more integrated circuits configured to implement the embodiments of the present application.

[0151] An embodiment of the present application also provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the above-mentioned method for estimating sea ice thickness based on GNSS reflection remote sensing technology.

[0152] An embodiment of the present application also provides a computer program product, including a computer program, which, when executed, implements the above-mentioned sea ice thickness estimation method based on GNSS reflection remote sensing technology.

[0153] In the description of this specification, the description with reference to the terms "one embodiment", "some embodiments", "example", "specific example", or "some examples" etc. means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present application. In this specification, the schematic representations of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described may be combined in any one or N embodiments or examples in a suitable manner. In addition, those skilled in the art may combine and combine the different embodiments or examples described in this specification and the features of the different embodiments or examples, without contradiction.

[0154] In addition, the terms "first" and "second" are used for descriptive purposes only and should not be understood as indicating or implying relative importance or implicitly indicating the number of technical features indicated. Therefore, a feature defined as "first" or "second" may explicitly or implicitly include at least one of the features. In the description of this application, "N" means at least two, such as two, three, etc., unless otherwise clearly and specifically defined.

[0155] Any process or method description in a flowchart or otherwise described herein may be understood to represent a module, fragment or portion of code comprising one or N executable instructions for implementing the steps of a custom logical function or process, and the scope of the preferred embodiments of the present application includes alternative implementations in which functions may not be performed in the order shown or discussed, including performing functions in a substantially simultaneous manner or in reverse order depending on the functions involved, which should be understood by technicians in the technical field to which the embodiments of the present application belong.

[0156] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as an ordered list of executable instructions for implementing logical functions, and can be embodied in any computer-readable medium for use by an instruction execution system, device or apparatus (such as a computer-based system, a system including a processor, or other system that can fetch instructions from an instruction execution system, device or apparatus and execute instructions), or in combination with these instruction execution systems, devices or apparatuses. For the purpose of this specification, "computer-readable medium" can be any device that can contain, store, communicate, propagate or transmit a program for use by an instruction execution system, device or apparatus, or in combination with these instruction execution systems, devices or apparatuses. More specific examples of computer-readable media (a non-exhaustive list) include the following: an electrical connection with one or N wirings (electronic devices), a portable computer disk box (magnetic device), a random access memory (RAM), a read-only memory (ROM), an erasable and programmable read-only memory (EPROM or flash memory), a fiber optic device, and a portable compact disk read-only memory (CDROM). In addition, the computer-readable medium may even be paper or other suitable medium on which the program is printed, since the program may be obtained electronically by optically scanning the paper or other medium and then editing, interpreting or processing in other suitable ways as necessary and then storing it in a computer memory.

[0157] It should be understood that the various parts of the present application can be implemented by hardware, software, firmware or a combination thereof. In the above embodiment, the N steps or methods can be implemented by software or firmware stored in a memory and executed by a suitable instruction execution system. If implemented by hardware, as in another embodiment, it can be implemented by any one or a combination of multiple of the following technologies known in the art: a discrete logic circuit having a logic gate circuit for implementing a logic function for a data signal, a dedicated integrated circuit having a suitable combination of logic gate circuits, a programmable gate array (PGA), a field programmable gate array (FPGA), etc.

[0158] A person skilled in the art may understand that all or part of the steps in the method for implementing the above-mentioned embodiment may be completed by instructing related hardware through a program, and the program may be stored in a computer-readable storage medium, which, when executed, includes one or a combination of the steps of the method embodiment.

[0159] In addition, each functional unit in each embodiment of the present application may be integrated into a processing module, or each unit may exist physically separately, or two or more units may be integrated into one module. The above-mentioned integrated module may be implemented in the form of hardware or in the form of a software functional module. If the integrated module is implemented in the form of a software functional module and sold or used as an independent product, it may also be stored in a computer-readable storage medium.

[0160] The storage medium mentioned above may be a read-only memory, a magnetic disk or an optical disk, etc. Although the embodiments of the present application have been shown and described above, it can be understood that the above embodiments are exemplary and cannot be understood as limiting the present application. A person of ordinary skill in the art may change, modify, replace and modify the above embodiments within the scope of the present application.

Claims

1. A method for estimating sea ice thickness based on GNSS reflection remote sensing technology, characterized in that: The following steps are involved: Collecting target data of the ship during its navigation in the target sea area, wherein the target data includes real-time global navigation satellite system GNSS data, hull height, antenna height and ship draft; Obtaining a dynamic sea surface height difference of the target sea area based on the real-time GNSS data; estimating the sea ice thickness of the target sea area based on the hull height, the antenna height, the ship draft and the dynamic sea surface height difference; The estimating the sea ice thickness of the target sea area based on the hull height, the antenna height, the ship draft and the dynamic sea surface height difference includes: Obtaining the sea ice freeboard of the target sea area based on the hull height, the antenna height, the ship draft and the dynamic sea surface height difference; estimating the sea ice thickness of the target sea area based on the sea ice freeboard; The calculation formula of sea ice freeboard is: h f =h ship +h ant -h GNSS-IR -h daraft -h bias , Among them, h ship is the height of the ship, i.e. the height difference from the bottom of the GNSS antenna to the bottom of the ship; h ant h is the antenna height, i.e. the height of the antenna phase center from the deck surface; daraft h is the draft of the ship, i.e. the distance from the water surface to the bottom of the ship; bias Dynamic sea surface correction, i.e. the deviation between the static estimate and the actual sea surface height; The estimation formula for sea ice thickness is: Among them, ρ ω is the density of seawater, ρ i is the density of sea ice, h f is the freeboard of sea ice, and H is the thickness of sea ice.

2. The method according to claim 1, characterized in that The step of obtaining the dynamic sea surface height difference of the target sea area based on the real-time GNSS data includes: Based on the real-time GNSS data, obtain the altitude angle and azimuth angle of each GNSS satellite and initial signal-to-noise ratio data of different satellite signals among the GNSS satellites; Performing a first preprocessing on the initial signal-to-noise ratio data to obtain signal-to-noise ratio data that meets a first preset condition; Based on the altitude angle and the azimuth angle, performing a second preprocessing on the GNSS signal in the signal-to-noise ratio data to obtain a processed GNSS signal that meets a second preset condition; Based on the processed GNSS signal, obtaining at least one signal segment corresponding to at least one window; determining a dominant frequency of the at least one signal segment based on the at least one signal segment; An initial dynamic sea surface height difference of the at least one signal segment is obtained based on the main frequency.

3. The method according to claim 2, characterized in that The step of obtaining the dynamic sea surface height difference of the target sea area based on the real-time GNSS data further includes: Based on the initial dynamic sea surface height difference, obtaining weight values ​​of the initial dynamic sea surface height difference of different signal segments in the same window; The dynamic sea surface height difference corresponding to each window is obtained based on the weight value.

4. A sea ice thickness estimation device based on GNSS reflection remote sensing technology, characterized in that: include: A collection module is used to collect target data of the ship during its navigation in the target sea area, wherein the target data includes real-time GNSS data, hull height, antenna height and ship draft; A generating module, used for obtaining the dynamic sea surface height difference of the target sea area based on the real-time GNSS data; An estimation module, configured to estimate the sea ice thickness of the target sea area based on the hull height, the antenna height, the ship draft and the dynamic sea surface height difference; Wherein, the estimation module comprises: A calculation unit, configured to obtain the sea ice freeboard of the target sea area based on the hull height, the antenna height, the ship draft and the dynamic sea surface height difference; an estimating unit, configured to estimate the sea ice thickness of the target sea area based on the sea ice freeboard; The calculation formula of sea ice freeboard is: h f =h ship +h ant -h GNSS-IR -h daraft -h bias , Among them, h ship is the height of the ship, i.e. the height difference from the bottom of the GNSS antenna to the bottom of the ship; h ant h is the antenna height, i.e. the height of the antenna phase center from the deck surface; daraft h is the draft of the ship, i.e. the distance from the water surface to the bottom of the ship; bias Dynamic sea surface correction, i.e. the deviation between the static estimate and the actual sea surface height; The estimation formula for sea ice thickness is: Among them, ρ ω is the density of seawater, ρ i is the density of sea ice, h f is the freeboard of sea ice, and H is the thickness of sea ice.

5. The device according to claim 4, characterized in that The generating module comprises: A first generating unit is used to obtain the altitude angle and azimuth angle of each GNSS satellite and initial signal-to-noise ratio data of different satellite signals in the GNSS satellite based on the real-time GNSS data; A first preprocessing unit, configured to perform a first preprocessing on the initial signal-to-noise ratio data to obtain signal-to-noise ratio data that meets a first preset condition; a second preprocessing unit, configured to perform a second preprocessing on the GNSS signal in the signal-to-noise ratio data based on the altitude angle and the azimuth angle, so as to obtain a processed GNSS signal that meets a second preset condition; A second generating unit, configured to obtain at least one signal segment corresponding to at least one window based on the processed GNSS signal; a determining unit, configured to determine a main frequency of the at least one signal segment according to the at least one signal segment; The third generating unit is configured to obtain an initial dynamic sea surface height difference of the at least one signal segment based on the main frequency.

6. An electronic device, characterized in that: include: A memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the method for estimating sea ice thickness based on GNSS reflection remote sensing technology as described in any one of claims 1 to 3.

7. A computer-readable storage medium having a computer program stored thereon, characterized in that: The program is executed by a processor to implement the sea ice thickness estimation method based on GNSS reflection remote sensing technology as described in any one of claims 1 to 3.

8. A computer program product, characterized in that It comprises a computer program, which, when executed, is used to implement the sea ice thickness estimation method based on GNSS reflection remote sensing technology as described in any one of claims 1 to 3.

Images