A method for detecting water depth in coastal waters by integrating multi-beams

Abstract

The present invention discloses a method for detecting water depth in nearshore waters by integrating multiple beams, comprising: According to the first aspect of the present invention, a method for detecting water depth in nearshore waters by integrating multiple beams, the specific implementation steps are as follows: S1: Acquire original images and data, wherein the original images and data include seabed image data of the target sea area collected by a high-resolution camera and water body data of the target area detected by a multi-beam detector. The present invention belongs to the technical field of water depth detection in nearshore waters. The purpose of the present invention is to solve the problem in the prior art that the hull posture and hull draft are constantly changing, which has a great impact on the detection of depth, and the seabed conditions cannot be accurately detected and identified. The technical effect achieved is: the seabed conditions in the nearshore waters are processed and analyzed by fusion image processing, and the influencing factors such as the hull posture and hull draft are processed at the same time, thereby improving the accuracy of multi-beam nearshore waters depth detection.

Description

Technical Field

[0001] The present invention relates to the technical field of water depth detection in nearshore waters, and in particular to a water depth detection method in nearshore waters integrating multiple beams. Background Art

[0002] The nearshore waters refer to all the waters from the coastline to the sea, including the territorial sea baseline to the land side, as well as the seas and inland seas where the territorial sea baseline has not yet been announced, specifically to all the waters on the land side of the minus 10-meter isobath. At present, the water depth detection of the nearshore waters is the most basic work before marine surveys, marine mapping and fishery farming. The water depth detection of the nearshore waters is mainly carried out through the multi-beam bathymetry system. During the measurement process, the multi-beam bathymetry system transmits wide-sector sound waves to the seabed through the sound wave transmitter installed on the bottom of the ship, and the receiver receives these sound waves with narrow beams. By analyzing the propagation time and angle of the sound waves, a single detection can give the water depth values ​​of hundreds or even more seabed measured points in the vertical plane perpendicular to the heading, and can accurately and quickly measure the water depth value;

[0003] When measuring in nearshore waters, the coverage area is smaller, and the difficulty of wide-sector coverage measurement increases, and the measurement is required to be as close to the waterline as possible. However, there are frequent ship traffic in nearshore waters, abundant fishery farming, strong winds and waves, and complex water quality conditions, which bring a lot of interference and affect the transmission and reception of beams. Among them, the influence of wind and waves causes the hull to sway greatly, resulting in constant changes in the hull posture and hull draft, and large changes in water surface height, which has a greater impact on depth detection. At the same time, the seabed conditions cannot be accurately detected and identified, resulting in a decrease in water depth detection capability and accuracy, which is very inconvenient. Summary of the invention

[0004] To this end, the present invention provides a method for detecting water depth in nearshore waters by integrating multiple beams to solve the above-mentioned problems in the prior art.

[0005] In order to achieve the above object, the present invention provides the following technical solutions:

[0006] According to the first aspect of the present invention, a method for detecting water depth in coastal waters by integrating multiple beams is specifically implemented as follows:

[0007] S1: Acquire original images and data, wherein the original images and data include seabed image data of the target sea area collected by a high-resolution camera and water body data of the target area detected by a multi-beam detector;

[0008] S2: along the emission range of the fan-shaped beam, calculate each group of emission strips in turn, measure the angle θ between the selected emission strip and the vertical hull downward emission strip, and then calculate the relevant vector to obtain the first detection result h and the directional area S of each emission strip, and calculate the stacking rate W of the two adjacent groups of directional area areas S until the edge emission strip, to preliminarily verify the calculation results;

[0009] The calculation formula for the first detection result h is:

[0010]

[0011] Where d is the distance of the downward emission strip perpendicular to the hull, and the beam angle θ is the angle between the selected emission strip and the downward emission strip perpendicular to the hull;

[0012] The calculation formula of the directional area S is:

[0013]

[0014] In the formula, is the sound velocity of the sound velocity profiler cell phone;

[0015] S3: The seabed image data collected from the same target sea area is evenly cut into a grid shape according to the preset grid area, and N frames are obtained after cutting. Image frames, (i=0, 1, 2, 3...n), then the N frames are divided into 3×3 small grids and preprocessed;

[0016] S4: Select the image drawn and generated by the transducer as the reference image, and after preprocessing The image frame is the matching image. The deep learning module is used to extract the same features of the matching image and the reference image, and the RST transformation model is selected for registration. The image frames are transformed and fused into the spatial coordinate system of the reference image to obtain the coordinates of each emission strip ( , , );

[0017] S5: Obtain the coordinate points corresponding to each transmission strip and the trim attitude of the ship at the moment of receiving the beam in real time and roll attitude , perform correction and reposition calculation of the relevant vector to obtain the actual water depth of the target area ;

[0018] The formula for the correction homing calculation is:

[0019]

[0020] In the formula, is the hull draft value.

[0021] Furthermore, the calculation formula of the stacking ratio W is:

[0022]

[0023] If the overlapping rate W≤10%, it means that there is continuity between the areas S of two adjacent groups of directional regions, and the preliminary verification is passed. If the overlapping rate W>10%, it means that there may be discontinuity between the areas S of two adjacent groups of directional regions, and there is an error, that is, the preliminary verification fails.

[0024] Furthermore, the target area water body data includes emission angles and hull attitude data of multiple emission strips in the fan-shaped beam provided by the transducer and the attitude sensor in the target area.

[0025] Furthermore, the preprocessing process in S3 is specifically as follows:

[0026] First, N frames of image frames are denoised and enhanced respectively. During the processing, the pixel values ​​of the 3×3 small grids are sorted, the middle threshold is found, and the middle threshold is assigned to the current In other adjacent grids in the image frame, the purpose of image denoising is achieved, and then the image contrast is enhanced through histogram equalization HE, and the insufficient light in the seabed is supplemented to highlight important seabed feature information.

[0027] Furthermore, in the registration process, a corresponding relationship between the multi-beam data and the image data is established by a matching algorithm based on mutual information, and the reference image and the corresponding The matching pairs of corresponding feature key points in the image frame are then filtered out through a proportional filter to select matching pairs with the same features, thereby improving the accuracy of matching.

[0028] Furthermore, the hull draft value The calculation formula is:

[0029]

[0030] Where L is the cross-sectional area of ​​the hull entering the water, h is the water depth corresponding to the shallow water area at that moment, is the ship speed, and k is the ship type coefficient.

[0031] The present invention has the following advantages:

[0032] 1. By integrating multi-beam and image processing methods to detect the water depth in the nearshore waters, the seabed conditions in the nearshore waters can be processed and analyzed, and the accuracy of multi-beam nearshore water depth detection can be improved. At the same time, during the detection process, the influencing factors such as the hull posture and hull draft can be processed to achieve accurate measurement of the water depth in the nearshore waters. BRIEF DESCRIPTION OF THE DRAWINGS

[0033] Figure 1 A flow chart of a method for detecting water depth in nearshore waters by integrating multiple beams is provided for some embodiments of the present invention. DETAILED DESCRIPTION

[0034] The following is a description of the implementation of the present invention by specific embodiments. People familiar with the art can easily understand other advantages and effects of the present invention from the contents disclosed in this specification. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention. Example

[0035] like Figure 1 As shown, a method for detecting water depth in coastal waters by integrating multiple beams in the first aspect of the present invention is specifically implemented as follows:

[0036] S1: Acquire original images and data, wherein the original images and data include seabed image data of the target sea area collected by a high-resolution camera and water body data of the target area detected by a multi-beam detector, and the water body data includes emission angles of multiple emission strips in a fan-shaped beam provided by a transducer and an attitude sensor in the target area and hull attitude data;

[0037] S2: along the emission range of the fan-shaped beam, calculate each group of emission strips in turn, measure the angle θ between the selected emission strip and the vertical hull downward emission strip, and then calculate the relevant vector to obtain the first detection result h and the directional area S of each emission strip, and calculate the stacking rate W of the two adjacent groups of directional area areas S until the edge emission strip, to preliminarily verify the calculation results;

[0038] The calculation formula for the first detection result h is:

[0039]

[0040] Where d is the distance of the downward emission strip perpendicular to the hull, and the beam angle θ is the angle between the selected emission strip and the downward emission strip perpendicular to the hull;

[0041] The calculation formula of the directional area S is:

[0042]

[0043] In the formula, is the sound velocity of the sound velocity profiler cell phone;

[0044] The calculation formula of stacking ratio W is:

[0045]

[0046] If the overlapping rate W≤10%, it means that there is continuity between the two adjacent groups of directional area areas S, and the preliminary verification is passed. If the overlapping rate W>10%, it means that there may be discontinuity between the two adjacent groups of directional area areas S, and there is an error, that is, the preliminary verification fails, and the data of the two adjacent groups of directional area areas S in the target area are discarded. After adjusting the position of the ship, the fan beam is transmitted again to measure the area;

[0047] The transducer array transmits a fan-shaped beam to the seabed, and forms an illumination footprint of the seabed terrain through the orthogonality of the transmitting and receiving sector directions. It can accurately and quickly measure the size, shape and height changes of underwater targets, depict the three-dimensional features of the seabed terrain, and convert them into electrical signals, which are transmitted to the processing unit installed in the hull to analyze and process the received signals and generate images, including standard map coordinates and the water depth at the corresponding coordinates;

[0048] S3: The seabed image data collected from the same target sea area is evenly cut into a grid shape according to the preset grid area, and N frames are obtained after cutting. Image frames, (i=0, 1, 2, 3...n), then the N frames are divided into 3×3 small grids and preprocessed;

[0049] The preprocessing process is as follows:

[0050] First, N frames of image frames are denoised and enhanced respectively. During the processing, the pixel values ​​of the 3×3 small grids are sorted, the middle threshold is found, and the middle threshold is assigned to the current In other adjacent grids in the image frame, the purpose of image denoising is achieved, and then the image contrast is enhanced through histogram equalization HE, and the insufficient light in the seabed is supplemented to highlight important seabed feature information;

[0051] S4: Select the image drawn and generated by the transducer as the reference image, and after preprocessing The image frame is the matching image. The deep learning module is used to extract the same features of the matching image and the reference image, and the RST transformation model is selected for registration. The image frames are converted and fused into the spatial coordinate system of the reference image. The matching algorithm module based on mutual information is used to match and detect the fused parameters to ensure the accuracy of the fusion, providing a solid foundation for subsequent data analysis and application, and obtaining the coordinates of each emission strip ( , , );

[0052] During the registration process, the corresponding relationship between multi-beam data and image data is established through a matching algorithm based on mutual information, and the reference image and the corresponding The matching pairs of corresponding feature key points in the image frame are then filtered out through a proportional filter to select matching pairs with the same features, thereby improving the accuracy of matching;

[0053] S5: Obtain the coordinate points corresponding to each transmission strip and the trim attitude of the ship at the moment of receiving the beam in real time and roll attitude , perform correction and reposition calculation of the relevant vector to obtain the actual water depth of the target area ;

[0054] The formula for the correction homing calculation is:

[0055]

[0056] In the formula, is the hull draft value;

[0057] Hull draft value The calculation formula is:

[0058]

[0059] Where L is the cross-sectional area of ​​the hull entering the water, h is the water depth corresponding to the shallow water area at that moment, is the ship speed, and k is the ship type coefficient.

[0060] In summary, the present invention improves a method for detecting water depth in nearshore waters by integrating multiple beams. The seabed conditions in nearshore waters are processed and analyzed by integrating image processing, thereby improving the accuracy of multi-beam water depth detection in nearshore waters. At the same time, during the detection process, the influencing factors such as the hull posture and hull draft can be processed to achieve accurate measurement of the water depth in nearshore waters.

Claims

1. A method for detecting water depth in coastal waters by integrating multiple beams, characterized in that: The specific implementation steps are as follows: S1: Acquire original images and data, wherein the original images and data include seabed image data of the target sea area collected by a high-resolution camera and water body data of the target area detected by a multi-beam detector; S2: along the emission range of the fan-shaped beam, calculate each group of emission strips in turn, measure the angle θ between the selected emission strip and the vertical hull downward emission strip, and then calculate the relevant vector to obtain the first detection result h and the directional area S of each emission strip, and calculate the stacking rate W of the two adjacent groups of directional area areas S until the edge emission strip, to preliminarily verify the calculation results; The calculation formula for the first detection result h is: Where d is the distance of the downward emission strip perpendicular to the hull, and the beam angle θ is the angle between the selected emission strip and the downward emission strip perpendicular to the hull; The calculation formula of the directional area S is: In the formula, is the sound velocity of the sound velocity profiler cell phone; S3: The seabed image data collected from the same target sea area is evenly cut into a grid shape according to the preset grid area, and N frames are obtained after cutting. Image frames, (i=0, 1, 2, 3...n), then the N frames are divided into 3×3 small grids and preprocessed; S4: Select the image drawn and generated by the transducer as the reference image, and after preprocessing The image frame is the matching image. The deep learning module is used to extract the same features of the matching image and the reference image, and the RST transformation model is selected for registration. The image frames are transformed and fused into the spatial coordinate system of the reference image to obtain the coordinates of each emission strip ( , , ); S5: Obtain the coordinate points corresponding to each transmission strip and the trim attitude of the ship at the moment of receiving the beam in real time and roll attitude , perform correction and reposition calculation of the relevant vector to obtain the actual water depth of the target area ; The formula for the correction homing calculation is: In the formula, is the hull draft value.

2. The method for detecting water depth in coastal waters by integrating multiple beams according to claim 1, characterized in that: The calculation formula of the stacking ratio W is: If the overlapping rate W≤10%, it means that there is continuity between the two adjacent groups of directional area areas S, and the preliminary verification passes. If the overlapping rate W>10%, it means that there may be discontinuity between the two adjacent groups of directional area areas S, and there is an error, that is, the preliminary verification fails.

3. The method for detecting water depth in coastal waters by integrating multiple beams according to claim 1, characterized in that: The target area water body data includes the emission angles of multiple emission strips in the fan-shaped beam provided by the transducer and the attitude sensor in the target area and the hull attitude data.

4. The method for detecting water depth in coastal waters by integrating multiple beams according to claim 1, characterized in that: The preprocessing process in S3 is as follows: First, N frames of image frames are denoised and enhanced respectively. During the processing, the pixel values ​​of the 3×3 small grids are sorted, the middle threshold is found, and the middle threshold is assigned to the current In other adjacent grids in the image frame, the purpose of image denoising is achieved, and then the image contrast is enhanced through histogram equalization HE, and the insufficient light in the seabed is supplemented to highlight important seabed feature information.

5. The method for detecting water depth in coastal waters by integrating multiple beams according to claim 1, characterized in that: In the registration process, the corresponding relationship between the multi-beam data and the image data is established by a matching algorithm based on mutual information, and the reference image and the corresponding image are found respectively. The matching pairs of corresponding feature key points in the image frame are then filtered out through a proportional filter to select matching pairs with the same features, thereby improving the accuracy of matching.

6. The method for detecting water depth in coastal waters by integrating multiple beams according to claim 1, characterized in that: The hull draft value The calculation formula is: Where L is the cross-sectional area of ​​the hull entering the water, h is the water depth corresponding to the shallow water area at that moment, is the ship speed, and k is the ship type coefficient.

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