Sea ice thickness calculation method based on image data

Abstract

The invention discloses a sea ice thickness calculation method based on image data, and the method comprises the following steps: obtaining the construction information and basic parameters of an icebreaker, and determining a camera installation point on the icebreaker and a sonar installation point on the side wall of the icebreaker; image data of sea ice on the ship side during icebreaking of the icebreaker are collected through a camera, sound waves are emitted to the underwater part of the sea ice through a sonar, echo data are received, and space-time alignment is conducted on the image data and the echo data; inputting the image data into a pre-trained neural network, and screening out image data of sea ice perpendicular to the sea surface; determining the height of the sea ice above the sea surface according to the echo data of the sea ice perpendicular to the sea surface, and determining the spacing by combining the camera mounting points; the sea ice imaging thickness is obtained according to the image data of the sea ice perpendicular to the sea surface, the actual sea ice thickness is calculated in combination with the sea ice imaging thickness, the distance and the camera focal length, the sea ice thickness can be rapidly determined through the image data, and the safety of polar region activity and icebreaker shipping is guaranteed.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of ocean monitoring, and in particular to a sea ice thickness calculation method based on image data. BACKGROUND

[0002] Sea ice thickness is a core parameter in the study of the climate of the North and South Poles, the safety guarantee of navigation, and the development of resources in the polar region. Its accurate acquisition is of great significance to understanding the evolution of the ecological environment in the polar region and planning human activities in the polar region. At present, the preliminary acquisition of large-scale sea ice thickness mainly relies on satellite observation technology. However, the inversion accuracy of satellite remote sensing data is affected by factors such as atmospheric interference and surface roughness, and further verification and calibration are needed through ground measurement data to ensure the reliability of the data.

[0003] However, sea ice is mainly distributed in the North and South Poles, which are subject to harsh climatic and geographical conditions such as low temperature, blizzards, and dense ice ridges all year round, making it difficult for humans or equipment to approach for observation. Even if an icebreaker is used to reach the polar region for operation, there are still safety hazards such as ice surface cracking and hypothermia for personnel directly measuring on the ice. Therefore, it is extremely difficult to directly obtain sea ice thickness information, and sea ice thickness has become one of the most difficult parameters to accurately obtain in sea ice.

[0004] Existing sea ice field observation methods mainly include the following three types, but all have significant technical limitations:

[0005] 1) Drilling measurement method: As the benchmark method for measuring sea ice thickness, it has the highest measurement accuracy. However, this method has strict implementation conditions, and it takes a long time to complete the measurement of a single point. In addition, the safety of the ice surface needs to be evaluated in advance to avoid operational risks, resulting in a very small number of sea ice thickness data points obtained through this method, which cannot meet the needs of large-scale and high-density observation.

[0006] 2) Bottom-looking sonar method: By deploying sonar equipment on the seabed, the water depth of sea ice can be accurately measured. However, this method has obvious shortcomings. On the one hand, the cost of purchasing and installing the equipment is high, and a professional team is needed for seabed deployment. On the other hand, a single instrument can only cover a fixed position and cannot be used for mobile observation, making it difficult to be widely applied in the vast polar region.

[0007] 3) Electromagnetic induction method: This method can be carried on an icebreaker to measure dynamic sea ice thickness during navigation, and has certain operational efficiency advantages. However, this method relies on expensive special measuring instruments, and the electromagnetic signal is easily disturbed by the complex ice structure in the ice ridge area, resulting in a significant decrease in measurement accuracy in this area, which cannot meet the needs of accurate measurement in all scenarios.

[0008] In summary, existing sea ice thickness field observation technologies have shortcomings in terms of measurement efficiency, cost control, coverage, and accuracy across all scenarios. There is an urgent need for a new sea ice thickness measurement method to solve the problems of difficult polar observation, low data acquisition efficiency, high cost, and limited accuracy. Summary of the Invention

[0009] In view of this, the present invention proposes a sea ice thickness calculation method based on image data, which can quickly and accurately obtain sea ice thickness to guide the navigation of icebreakers and personnel activities.

[0010] The technical solution of this invention is implemented as follows:

[0011] A method for calculating sea ice thickness based on image data includes the following steps:

[0012] Step S1: Obtain the structural information and basic parameters of the icebreaker, and determine the camera mounting points on the icebreaker and the sonar mounting points on the sidewalls of the icebreaker.

[0013] Step S2: Collect image data of sea ice on the side of the icebreaker as it breaks ice using a camera, transmit sound waves to the underwater part of the sea ice using sonar, and receive echo data. Then, align the image data and echo data in time and space.

[0014] Step S3: Input the image data into the pre-trained neural network and filter out the image data of sea ice perpendicular to the sea surface;

[0015] Step S4: Determine the height of the sea ice above the sea surface based on the echo data of the sea ice perpendicular to the sea surface, and determine the spacing in conjunction with the camera installation points;

[0016] Step S5: Obtain the sea ice imaging thickness based on the image data of the sea ice perpendicular to the sea surface, and calculate the actual thickness of the sea ice by combining the sea ice imaging thickness, spacing and camera focal length.

[0017] Preferably, step S1 includes the following steps:

[0018] Step S11: Obtain the hull structure dimensions, center of gravity position, and deck height of the icebreaker as construction information;

[0019] Step S12: Determine the installation location that meets the shooting requirements based on the structural information as the camera installation point;

[0020] Step S13: Obtain the icebreaker's draft, heading speed, and hull layout as basic parameters, and determine the sonar installation point on the side of the hull below the waterline based on the basic parameters.

[0021] Preferably, step S2 includes the following specific steps:

[0022] Step S21: Acquire image data of sea ice on the side of the icebreaker at a predetermined frame rate using a camera;

[0023] Step S22: Transmit acoustic signals to the sea ice on the side of the ship using sonar at a period synchronized with the camera's predetermined frame rate, and receive echo data.

[0024] Step S23: Preprocess the image data and echo data, and add a unified timestamp;

[0025] Step S24: Establish a unified coordinate system that includes camera parameters and sonar parameters. Based on the unified coordinate system and timestamps, establish the spatiotemporal correspondence between image data and echo data.

[0026] Preferably, the preprocessing in step S23 includes:

[0027] Perform duplicate frame removal, Gaussian filtering, distortion correction, and image enhancement on image data;

[0028] The echo data is subjected to bandpass filtering, normalization, and invalid data removal.

[0029] Preferably, step S3 includes the following specific steps:

[0030] Step S31: Obtain an image dataset containing different sea ice postures, and train the neural network using the image dataset;

[0031] Step S32: Input the collected sea ice image data into the trained neural network, and the neural network outputs the verticality of each sea ice block;

[0032] Step S33: Filter out the image data of sea ice that is perpendicular to the sea surface based on verticality.

[0033] Preferably, step S4 includes the following specific steps:

[0034] Step S41: Determine the straight-line distance from the sonar to the bottom of the sea ice using the sound waves emitted by the sonar and the received echo data.

[0035] Step S42: Convert the straight-line distance into a vertical component based on the actual tilt angle of the sonar beam, and sum the vertical component with the depth of the sonar installation point below the water surface to obtain the height of the sea ice below the sea surface.

[0036] Step S43: Based on the principle of buoyancy and the height below the sea surface, calculate the overall height of the sea ice. Subtract the height below the sea surface from the overall height of the sea ice to obtain the height above the sea surface.

[0037] Step S44: Determine the spacing based on the height of the sea ice above the sea surface and the location of the camera installation point.

[0038] Preferably, step S41 includes the following specific steps:

[0039] Step S411: Use wavelet transform to extract the envelope of the echo data and identify all local maxima on the envelope;

[0040] Step S412: Set a dual discrimination threshold for echo amplitude and pulse width, and output the echo corresponding to the first local maximum point that simultaneously satisfies the dual discrimination threshold as the characteristic echo of the ice-water interface.

[0041] Step S413: Calculate the straight-line distance from the sonar to the bottom of the sea ice based on the arrival time of the characteristic echo at the ice-water interface and the propagation speed of the sound wave in the water.

[0042] Preferably, the specific steps of step S42 are as follows:

[0043] Step S421: Collect roll and pitch angle data of the sonar location using the inertial measurement unit located near the sonar position on the icebreaker hull.

[0044] Step S422: Establish a coordinate transformation matrix from the icebreaker hull coordinate system to the horizontal geographic coordinate system based on the roll and pitch angle data;

[0045] Step S423: Obtain the initial installation angle of the sonar on the icebreaker hull, and use the coordinate transformation matrix to correct the initial installation angle to obtain the actual tilt angle of the sonar beam.

[0046] Step S424: Convert the straight-line distance into a vertical component based on the actual tilt angle of the sonar beam, and sum the vertical component with the depth of the sonar installation point below the water surface to obtain the initial height of the sea ice below the sea surface.

[0047] Step S425: Collect the vertical displacement of the ship's hull and the hydrostatic pressure change of the seawater using a high-frequency GNSS receiver and an underwater pressure sensor located near the sonar installation point on the icebreaker.

[0048] Step S426: After converting the vertical displacement of the hull and the hydrostatic pressure change of the seawater into the vertical displacement compensation amount of the hull and the seawater level fluctuation amount, the initial height of the sea ice below the sea surface is corrected to obtain the height of the sea ice below the sea surface.

[0049] Preferably, the vertical component The expression is: ,in This is the straight-line distance from the sonar to the bottom of the sea ice. The actual tilt angle of the sonar beam;

[0050] The height of the sea ice below the sea surface The expression is: ,in , which is the initial height of the sea ice below the sea surface. The depth at which the sonar installation point is located below the water surface. These are the seawater level fluctuation and the compensation for the vertical displacement of the ship, respectively.

[0051] The overall height of the sea ice The expression is: ( ),in These are the densities of seawater and sea ice, respectively.

[0052] The height of the sea ice above the sea surface The expression is: ;

[0053] The spacing The expression is: ,in The height of the camera mounting point above the sea surface.

[0054] Preferably, the formula for calculating the actual thickness of sea ice in step S5 is:

[0055] ;

[0056] Where L is the actual thickness of the sea ice, and D is the spacing. For the camera's focal length, The thickness of the sea ice image.

[0057] Compared with the prior art, the beneficial effects of the present invention are:

[0058] This invention discloses a method for calculating sea ice thickness based on image data. During icebreaker operations, image data of sea ice is collected. A neural network is then introduced to identify the sea ice perpendicular to the sea surface. Sonar is used to determine the height of the sea ice below the sea surface, and the buoyancy law is used to calculate the height of the sea ice above the sea surface. This determines the distance between the camera and the top of the sea ice. Finally, based on the camera's imaging principles, such as the sea ice imaging thickness and distance at the camera's side, and the camera's focal length, the actual thickness of the sea ice in a vertical state can be calculated. Based on the actual sea ice thickness, the icebreaker's navigation strategy can be adjusted. Simultaneously, data guidance can be provided for personnel disembarking for investigations, ensuring the safety of navigation and research. Attached Figure Description

[0059] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only preferred embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0060] Figure 1 This is a flowchart of a sea ice thickness calculation method based on image data according to the present invention;

[0061] Figure 2 This is a schematic diagram showing the ice floes flipping on both sides of the icebreaker as it moves forward.

[0062] Figure 3 This is a flowchart of step S1 of the sea ice thickness calculation method based on image data according to the present invention;

[0063] Figure 4 This is a flowchart of step S2 of the sea ice thickness calculation method based on image data according to the present invention;

[0064] Figure 5 This is a flowchart of step S3 of the sea ice thickness calculation method based on image data according to the present invention;

[0065] Figure 6 This is a flowchart of step S4 of the sea ice thickness calculation method based on image data according to the present invention;

[0066] Figure 7 This is a flowchart of step S41 of the sea ice thickness calculation method based on image data according to the present invention;

[0067] Figure 8 This is a flowchart of step S42 of the sea ice thickness calculation method based on image data according to the present invention. Detailed Implementation

[0068] To better understand the technical content of this invention, a specific embodiment is provided below, and the invention will be further described in conjunction with the accompanying drawings.

[0069] See Figures 1 to 8 The present invention provides a method for calculating sea ice thickness based on image data, comprising the following steps:

[0070] Step S1: Obtain the structural information and basic parameters of the icebreaker, and determine the camera mounting points on the icebreaker and the sonar mounting points on the sidewalls of the icebreaker.

[0071] Step S2: Collect image data of sea ice on the side of the icebreaker as it breaks ice using a camera, transmit sound waves to the underwater part of the sea ice using sonar, and receive echo data. Then, align the image data and echo data in time and space.

[0072] Step S3: Input the image data into the pre-trained neural network and filter out the image data of sea ice perpendicular to the sea surface;

[0073] Step S4: Determine the height of the sea ice above the sea surface based on the echo data of the sea ice perpendicular to the sea surface, and determine the spacing in conjunction with the camera installation points;

[0074] Step S5: Obtain the sea ice imaging thickness based on the image data of the sea ice perpendicular to the sea surface, and calculate the actual thickness of the sea ice by combining the sea ice imaging thickness, spacing and camera focal length.

[0075] When icebreakers navigate, they break up large chunks of floating ice on the sea surface. The ice on both sides of the ship is compressed and breaks apart, often causing the ice to flip and become vertical. This vertical ice thickness can be observed, allowing adjustments to the icebreaker's navigation strategy and speed. To accurately assess ice thickness, this invention uses image data. Cameras are installed at appropriate locations on the icebreaker to capture images of the ice. These images include not only vertically positioned ice but also ice that is tilted. To achieve accurate assessment of vertically positioned ice image data... This invention employs a neural network for rapid extraction. A pre-trained neural network can quickly filter image data of sea ice in a vertical state. The image data reveals the sea ice imaging thickness. According to imaging principles, the ratio between the imaging thickness and the actual sea ice thickness is related to the distance between the camera and the sea ice, as well as the camera's focal length. The camera's focal length can be directly obtained from camera parameters, and the sea ice imaging thickness can be directly identified from the image data. Therefore, once the distance is determined, the actual sea ice thickness can be quickly calculated, allowing for adjustments to the icebreaker's navigation strategy and providing data support for polar expeditions.

[0076] During icebreaker navigation, the distance between the camera and sea ice is mostly dynamic due to weather and sea currents. Calculating the actual thickness of sea ice based on the static distance would introduce errors. Therefore, this invention incorporates a sonar system on the sidewall of the icebreaker. Positioned below the waterline during icebreaking, the sonar emits sound waves towards the sea ice and receives echo data. By aligning the echo data with the image data in time and space, a one-to-one correspondence between sea ice segments can be established. After filtering image data of vertically positioned sea ice, the echo data can be quickly determined. Based on the echo data, the height of the sea ice above the sea surface can be calculated. Finally, combined with the specific location of the camera installation point, the distance between the camera and the top of the sea ice can be calculated. Using sonar to transmit and receive sound waves avoids the influence of weather conditions. Compared to direct ranging with lidar, it is less affected by the environment and can more accurately calculate the height of the sea ice above the sea surface, thus allowing for precise estimation of the actual thickness of the sea ice based on imaging principles.

[0077] Preferably, step S1 includes the following steps:

[0078] Step S11: Obtain the hull structure dimensions, center of gravity position, and deck height of the icebreaker as construction information;

[0079] Step S12: Determine the installation location that meets the shooting requirements based on the structural information as the camera installation point;

[0080] Step S13: Obtain the icebreaker's draft, heading speed, and hull layout as basic parameters, and determine the sonar installation point on the side of the hull below the waterline based on the basic parameters.

[0081] Calculating sea ice thickness requires the use of cameras and sonar. Therefore, cameras and sonar need to be installed on the icebreaker in advance. The camera is installed at a high point on the icebreaker to collect image data of multiple sea ice formations on the side of the ship. After obtaining the structural information of the icebreaker, a suitable location with minimal weather influence is selected as the camera installation point based on the ship's structural dimensions, center of gravity, and deck height. The sonar needs to be located underwater to emit sound waves, so the draft of the icebreaker needs to be obtained. At the same time, the sonar installation point is determined based on the ship's layout. Then, the camera and sonar can be installed at the camera installation point and the sonar installation point.

[0082] Preferably, step S2 includes the following specific steps:

[0083] Step S21: Acquire image data of sea ice on the side of the icebreaker at a predetermined frame rate using a camera;

[0084] Step S22: Transmit acoustic signals to the sea ice on the side of the ship using sonar at a period synchronized with the camera's predetermined frame rate, and receive echo data.

[0085] Step S23: Preprocess the image data and echo data, and add a unified timestamp;

[0086] Step S24: Establish a unified coordinate system that includes camera parameters and sonar parameters. Based on the unified coordinate system and timestamps, establish the spatiotemporal correspondence between image data and echo data.

[0087] During the icebreaker's voyage, a preset frame rate is established, and then the camera can capture image data of the sea ice on the side of the ship at the preset frame rate. At the same time, the sonar can emit sound wave signals to the sea ice according to the corresponding period. The sound wave signals will return after contacting the sea ice, and the sonar will receive the echo data. The image data and echo data are preprocessed and stamped with a unified timestamp. At the same time, according to the set unified coordinate system, the image data and echo data are matched one by one to facilitate the search for the selected vertical sea ice echo data.

[0088] Preferably, the preprocessing in step S23 includes:

[0089] Perform duplicate frame removal, Gaussian filtering, distortion correction, and image enhancement on image data;

[0090] The echo data is subjected to bandpass filtering, normalization, and invalid data removal.

[0091] Image data may contain duplicate frames or noise. Preprocessing can remove duplicate frames and filter noise. In addition, to improve the recognition rate of neural networks, distortion correction and image enhancement are performed on the image data. Echo data also contains some noise, so bandpass filtering is required to remove invalid data and normalize the data to unify the magnitude.

[0092] Preferably, step S3 includes the following specific steps:

[0093] Step S31: Obtain an image dataset containing different sea ice postures, and train the neural network using the image dataset;

[0094] Step S32: Input the collected sea ice image data into the trained neural network, and the neural network outputs the verticality of each sea ice block;

[0095] Step S33: Filter out the image data of sea ice that is perpendicular to the sea surface based on verticality.

[0096] The image dataset contains a large number of sea ice images in different poses. The image dataset is divided into a training set and a test set. The neural network is trained using the training set. After training for a period of time, the neural network is tested using the test set. When the accuracy reaches a preset threshold, training stops. At this point, the image data of sea ice collected from the side of the icebreaker can be input into the neural network. The neural network can output the verticality of each piece of sea ice. The verticality can be used to filter out the image data of sea ice that is perpendicular to the sea surface.

[0097] Preferably, step S4 includes the following specific steps:

[0098] Step S41: Determine the straight-line distance from the sonar to the bottom of the sea ice using the sound waves emitted by the sonar and the received echo data.

[0099] Step S42: Convert the straight-line distance into a vertical component based on the actual tilt angle of the sonar beam, and sum the vertical component with the depth of the sonar installation point below the water surface to obtain the height of the sea ice below the sea surface.

[0100] Step S43: Based on the principle of buoyancy and the height below the sea surface, calculate the overall height of the sea ice. Subtract the height below the sea surface from the overall height of the sea ice to obtain the height above the sea surface.

[0101] Step S44: Determine the spacing based on the height of the sea ice above the sea surface and the location of the camera installation point.

[0102] The sonar is located below the waterline. When it emits sound waves towards the sea ice, the sea ice reflects the sound waves, and the sonar receives the echo data. Based on the echo data, the straight-line distance from the sonar to the bottom of the sea ice can be determined. The horizontal line extending from the sonar's location to the sea ice, together with the line connecting the sea ice and the bottom of the sonar, forms a right triangle. The length of the hypotenuse of this right triangle is the straight-line distance. Then, based on the actual tilt angle of the sonar beam, the straight-line distance can be converted into a vertical component, i.e., the vertical side of the right triangle. Since the sonar is located below the sea surface, its installation point is known. By adding the depth of the sonar installation point below the water surface to the vertical component, the height of the sea ice below the sea surface can be obtained. Finally, based on the principle of buoyancy, the height of the sea ice above the sea surface can be deduced. Combined with the specific location of the camera installation point, the precise spacing can be calculated.

[0103] Preferably, step S41 includes the following specific steps:

[0104] Step S411: Use wavelet transform to extract the envelope of the echo data and identify all local maxima on the envelope;

[0105] Step S412: Set a dual discrimination threshold for echo amplitude and pulse width, and output the echo corresponding to the first local maximum point that simultaneously satisfies the dual discrimination threshold as the characteristic echo of the ice-water interface.

[0106] Step S413: Calculate the straight-line distance from the sonar to the bottom of the sea ice based on the arrival time of the characteristic echo at the ice-water interface and the propagation speed of the sound wave in the water.

[0107] The bottom of sea ice in a vertical state is not horizontal, but uneven. In order to accurately calculate the height of sea ice below the sea surface, it is necessary to accurately identify the ice-water interface. After wavelet transform, the envelope of the echo data can be obtained, and the local maxima points on the envelope can be identified. Then, using a dual-discrimination thresholding method, the local maxima points are compared with the echo amplitude and pulse width thresholds. The echo corresponding to the first local maxima point that simultaneously exceeds the amplitude and pulse width thresholds is output as the characteristic echo of the ice-water interface. Then, the straight-line distance from the sonar to the bottom of the sea ice is calculated based on the characteristic echo.

[0108] Preferably, the specific steps of step S42 are as follows:

[0109] Step S421: Collect roll and pitch angle data of the sonar location using the inertial measurement unit located near the sonar position on the icebreaker hull.

[0110] Step S422: Establish a coordinate transformation matrix from the icebreaker hull coordinate system to the horizontal geographic coordinate system based on the roll and pitch angle data;

[0111] Step S423: Obtain the initial installation angle of the sonar on the icebreaker hull, and use the coordinate transformation matrix to correct the initial installation angle to obtain the actual tilt angle of the sonar beam.

[0112] Step S424: Convert the straight-line distance into a vertical component based on the actual tilt angle of the sonar beam, and sum the vertical component with the depth of the sonar installation point below the water surface to obtain the initial height of the sea ice below the sea surface.

[0113] Step S425: Collect the vertical displacement of the ship's hull and the hydrostatic pressure change of the seawater using a high-frequency GNSS receiver and an underwater pressure sensor located near the sonar installation point on the icebreaker.

[0114] Step S426: After converting the vertical displacement of the hull and the hydrostatic pressure change of the seawater into the vertical displacement compensation amount of the hull and the seawater level fluctuation amount, the initial height of the sea ice below the sea surface is corrected to obtain the height of the sea ice below the sea surface.

[0115] In addition, during navigation and icebreaking, the attitude of the sonar changes, and the tilt angle of its emitted beam also changes slightly. In order to accurately calculate the vertical component, attitude correction is required. An inertial measurement unit is installed on the hull near the sonar to collect the roll and pitch angle data of the sonar. Then, based on the roll and pitch angle data, a coordinate transformation matrix can be established from the hull coordinate system to the horizontal geographic coordinate system. The initial installation angle of the sonar can be corrected through the coordinate transformation matrix, thereby obtaining the actual tilt angle of the sonar emitted beam.

[0116] By converting the straight-line distance into a vertical component using the actual tilt angle of the sonar beam, and then summing this component with the depth of the sonar installation point below the water surface, the initial subsurface height can be obtained. However, during icebreaker navigation, sea ice is in a floating state, not stationary. If the initial subsurface height is directly used to deduce the above-surface height based on the buoyancy theorem, there will be some error. Therefore, this invention installs a high-frequency GNSS receiver and an underwater pressure sensor on the side of the ship near the sonar. The high-frequency GNSS receiver can collect the vertical displacement of the hull. By comparing the vertical displacement with a reference value, the vertical displacement compensation of the hull can be calculated. The underwater pressure sensor can collect the hydrostatic pressure changes of the seawater. According to the hydrostatic pressure formula... The distance h from the underwater pressure sensor to the sea surface can be calculated and compared with the distance under conditions of no ship wave disturbance to obtain the amount of seawater level fluctuation. This allows for the correction of the initial height below the sea surface and compensation for measurement errors caused by the icebreaker's navigation.

[0117] Preferably, the vertical component The expression is: ,in This is the straight-line distance from the sonar to the bottom of the sea ice. The actual tilt angle of the sonar beam;

[0118] The height of the sea ice below the sea surface The expression is: ,in , which is the initial height of the sea ice below the sea surface. The depth at which the sonar installation point is located below the water surface. These are the seawater level fluctuation and the compensation for the vertical displacement of the ship, respectively.

[0119] The overall height of the sea ice The expression is: ( ),in These are the densities of seawater and sea ice, respectively.

[0120] The height of the sea ice above the sea surface The expression is: ;

[0121] The spacing The expression is: ,in The height of the camera mounting point above the sea surface.

[0122] The vertical component can be calculated using the straight-line distance and the actual tilt angle of the sonar beam. After determining the vertical component, the depth of the sonar installation point below the water surface can be determined based on its location. This depth is then added to the vertical component to obtain the initial height of the sea ice below the sea surface. After compensation, the height below the sea surface is obtained. Then, using the buoyancy theorem, the overall height of the sea ice can be calculated based on the density of seawater and the density of sea ice. At this point, the height of the sea ice above the sea surface can be obtained by subtracting the height below the sea surface from the overall height of the sea ice. Finally, by subtracting the height above the sea surface from the height of the camera installation point from the sea surface, the distance between the camera and the top surface of the sea ice can be obtained.

[0123] Preferably, the formula for calculating the actual thickness of sea ice in step S5 is:

[0124] ;

[0125] Where L is the actual thickness of the sea ice, and D is the spacing. For the camera's focal length, The thickness of the sea ice image.

[0126] During the imaging process, the length of the object of length L projected onto the photograph is... The following proportional relationship exists: ,in It can be obtained through measurement of image data. The thickness of the sea ice can be obtained from the camera's internal parameters, and D can be calculated from step S4. Therefore, the actual thickness of the sea ice can be calculated.

[0127] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A method of sea ice thickness calculation based on image data, characterized in that, The method comprises the following steps: Step S1, obtaining the structure information and basic parameters of the icebreaker, determining the camera installation point on the icebreaker and the sonar installation point on the side wall of the icebreaker; Step S2, collecting image data of sea ice on the side of the icebreaker during ice breaking by the camera, emitting sound waves to the underwater part of the sea ice by the sonar, and receiving echo data, and spatiotemporally aligning the image data and the echo data; Step S3, inputting the image data into a pre-trained neural network, and screening out the image data of the sea ice perpendicular to the sea surface; Step S4, determining the height of the sea ice above the sea surface according to the echo data of the sea ice perpendicular to the sea surface, and determining the distance in combination with the camera installation point; Step S5, obtaining the imaging thickness of the sea ice according to the image data of the sea ice perpendicular to the sea surface, and calculating the actual thickness of the sea ice in combination with the imaging thickness of the sea ice, the distance, and the focal length of the camera.

2. The method of claim 1, wherein, The specific steps of the step S1 comprise: Step S11, obtaining the hull structure size, the center of gravity position, and the deck height of the icebreaker as the structure information; Step S12, determining the installation position meeting the shooting requirement as the camera installation point according to the structure information; Step S13, obtaining the draft depth, the heading speed, and the hull layout of the icebreaker as the basic parameters, and determining the sonar installation point on the hull side below the waterline according to the basic parameters.

3. The method of claim 1, wherein, The specific steps of the step S2 comprise: Step S21, collecting the image data of the sea ice on the side of the icebreaker during ice breaking by the camera at a predetermined frame rate; Step S22, emitting sound wave signals to the sea ice on the side of the icebreaker by the sonar at a period synchronized with the predetermined frame rate of the camera, and receiving echo data; Step S23, pre-processing the image data and the echo data, and marking them with a unified timestamp; Step S24, establishing a unified coordinate system containing camera parameters and sonar parameters, and establishing the spatiotemporal correspondence of the image data and the echo data based on the unified coordinate system and the timestamp.

4. The method of claim 3, wherein, The pre-processing of the step S23 comprises: repeating frame elimination, Gaussian filtering, distortion correction, and image enhancement on the image data; band-pass filtering, normalization processing, and invalid data elimination on the echo data.

5. The method of claim 1, wherein, The specific steps of the step S3 comprise: Step S31, obtaining an image data set containing different sea ice postures, and training the neural network through the image data set; Step S32, inputting the collected image data of the sea ice into the trained neural network, and outputting the perpendicularity of each piece of sea ice by the neural network; Step S33, screening out the image data of the sea ice perpendicular to the sea surface according to the perpendicularity.

6. The method of claim 1, wherein, The specific steps of the step S4 comprise: Step S41, determining the straight-line distance from the sonar to the bottom of the sea ice through the emitted sound waves and the received echo data; Step S42, converting the straight-line distance into a vertical component according to the actual inclination of the beam emitted by the sonar, summing up the vertical component and the depth of the sonar installation point below the water surface, and obtaining the height of the sea ice below the sea surface; Step S43, calculating the overall height of the sea ice according to the buoyancy principle in combination with the height below the sea surface, and obtaining the height of the sea ice above the sea surface by subtracting the overall height of the sea ice from the height below the sea surface. Step S44, determining the distance according to the height of sea ice above sea level and the position of camera installation point.

7. The method of claim 6, wherein, The specific steps of the step S41 include: Step S411, extracting the envelope line of echo data by using wavelet transform, and identifying all local maximum points on the envelope line; Step S412, setting double-discrimination threshold of echo amplitude and pulse width, and outputting the echo corresponding to the first local maximum point satisfying the double-discrimination threshold as the characteristic echo of ice-water interface; Step S413, calculating the straight-line distance from the sonar to the bottom of sea ice according to the arrival time of the characteristic echo of ice-water interface and the transmission speed of sound wave in water.

8. The method of claim 6, wherein, The specific steps of the step S42 are: Step S421, collecting the roll angle and pitch angle data of the position of the sonar by the inertial measurement unit near the position of the sonar on the icebreaker hull; Step S422, establishing the coordinate conversion matrix from the icebreaker hull coordinate system to the horizontal geographic coordinate system according to the roll angle and pitch angle data; Step S423, obtaining the initial installation angle of the sonar on the icebreaker hull, correcting the initial installation angle by using the coordinate conversion matrix, and obtaining the actual inclination angle of the beam emitted by the sonar; Step S424, converting the straight-line distance into a vertical component according to the actual inclination angle of the beam emitted by the sonar, summing the vertical component and the depth of the sonar installation point below the water surface, and obtaining the initial height of sea ice below sea level; Step S425, collecting the vertical motion displacement of the hull and the change of hydrostatic pressure of seawater by the high-frequency GNSS receiver and the underwater pressure sensor near the sonar installation point on the icebreaker, respectively; Step S426, converting the vertical motion displacement of the hull and the change of hydrostatic pressure of seawater into the vertical displacement compensation of the hull and the water level fluctuation of seawater, respectively, and correcting the initial height of sea ice below sea level to obtain the height of sea ice below sea level.

9. The method of claim 8, wherein, the vertical component is expressed as: wherein is the straight-line distance from the sonar to the bottom of the sea ice, is the actual angle of the sonar beam. the undersea level of the sea ice is expressed as: wherein is the initial undersea level of the sea ice, is the depth of the sonar installation point below the water surface, are the sea water level fluctuation and the hull vertical displacement compensation, respectively; The overall height of the sea ice The expression for , where are the densities of seawater and sea ice, respectively.​ the height above sea level of the sea ice The expression for this is: ; The spacing The expression for: where is the height of the camera mount point above sea level.

10. The method of claim 1, wherein, The calculation formula of the actual thickness of sea ice in the step S5 is: ； where L is the actual thickness of sea ice, D is the distance, is the focal length of the camera, is the imaged thickness of sea ice.

Images