CN113255240A - Ocean internal wave amplitude remote sensing inversion method based on dynamic condition constraint - Google Patents

Ocean internal wave amplitude remote sensing inversion method based on dynamic condition constraint Download PDF

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CN113255240A
CN113255240A CN202110244782.3A CN202110244782A CN113255240A CN 113255240 A CN113255240 A CN 113255240A CN 202110244782 A CN202110244782 A CN 202110244782A CN 113255240 A CN113255240 A CN 113255240A
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谢华荣
徐青
范开国
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Hohai University HHU
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Abstract

The invention discloses a dynamic condition constrained ocean internal wave amplitude remote sensing inversion method, which belongs to the technical field of satellite remote sensing and comprises the following specific steps: collecting satellite remote sensing image data in an observation area, and extracting a crest line and a half-amplitude width of ocean internal waves in the image; calculating the depth of the upper ocean layer and the depth of the lower ocean layer by taking the central longitude and latitude value of the front guided wave crest line as the occurrence position of the internal wave at the imaging moment; calculating a judgment parameter value of the internal wave by taking the ratio of the dimensionless frequency dispersion coefficient to the square of the dimensionless nonlinear coefficient as a judgment parameter; the amplitude inversion method was determined according to the following criteria: when the judgment parameter is less than 10, adopting a Korteweg-de Vries equation method; when the judgment parameter is larger than 10, adopting a nonlinear Schrodinger equation method; and utilizing the determined method to obtain the amplitude of the ocean internal wave on the remote sensing image through inversion. The invention solves the problem that the traditional internal wave amplitude remote sensing inversion method has no universality, and establishes a remote sensing inversion method for accurately extracting internal wave amplitudes on different remote sensing images.

Description

Ocean internal wave amplitude remote sensing inversion method based on dynamic condition constraint
Technical Field
The invention relates to a dynamic condition constrained marine internal wave amplitude remote sensing inversion method, which is used for extracting the amplitude of marine internal waves on a satellite remote sensing image.
Background
Ocean internal waves are an important ocean phenomenon, have important influence on an ocean power process, and have different degrees of influence on activities related to ocean acoustics, such as underwater communication, target detection and the like. In addition, the propagation process of the internal wave is often accompanied by strong seawater convergence and sudden strong shear flow, which can cause serious damage to underwater buildings, submarines and the like. Therefore, the research of the internal waves has important research significance in the fields of marine science, marine engineering, marine military and the like.
The observation method of internal waves mainly comprises direct field observation and indirect remote sensing observation. Compared with field observation, remote sensing observation has the advantage of acquiring observation data in a large range and in real time, and is an important means for researching internal waves. Besides being used for space-time characteristic statistical analysis, the remote sensing image can also be used for extracting characteristic parameters of internal waves. Amplitude is one of the important characteristic parameters of internal waves. Common methods for inverting the amplitude of the internal wave on the remote sensing image include two inversion methods based on a Korteweg-de Vries (KdV) equation and an inversion method based on a nonlinear Schrodinger (NLS) equation. The two basic processes are consistent, namely, the half amplitude width of the internal wave is obtained from the remote sensing image, the occurrence position of the internal wave at the imaging moment is determined, the local seawater parameter is obtained, then the extracted half amplitude width and the local seawater parameter are substituted into the solution of the equation, and finally the inversion amplitude of the internal wave is obtained.
Research shows that in certain sea areas and under specific conditions, the two methods can extract the internal wave amplitude more accurately. However, when internal wave research is performed on the basis of the same remote sensing image, the internal wave amplitude inversion results obtained by the two methods are often greatly different, which is mainly caused by the fact that the relationship between the amplitude and parameters such as half-amplitude width is significantly different in KdV equation and NLS equation. In addition, the same ocean internal wave is often captured by quasi-synchronous multi-source satellite remote sensing images, the spatial resolution of the images has large difference, and the difference may be several times or even dozens of times, so that the half amplitude width of the internal wave extracted from different images also has large difference. In the above case, it is obviously unreasonable to simply or arbitrarily use one of the two methods to invert the amplitude of the internal wave on different images.
The existing ocean internal wave amplitude remote sensing inversion method is only suitable for remote sensing image data under certain specific conditions, and the internal wave amplitudes on different remote sensing images are difficult to accurately extract. Therefore, how to seek an internal wave amplitude inversion method generally suitable for different remote sensing images is a key problem to be solved urgently in the current ocean internal wave remote sensing research.
Disclosure of Invention
The purpose of the invention is as follows: the invention aims to provide a dynamic condition constrained ocean internal wave amplitude remote sensing inversion method, and solves the problem that the traditional internal wave amplitude inversion method cannot be generally applied to different remote sensing images.
The technical scheme is as follows: in order to achieve the purpose, the invention adopts the following technical scheme:
the marine internal wave amplitude remote sensing inversion method based on dynamic condition constraint comprises the following steps:
step 1, collecting and preprocessing ocean internal wave satellite remote sensing image data;
step 2, extracting an internal wave crest line in the remote sensing image, and measuring to obtain an internal wave half-amplitude width delta according to a distance l between adjacent bright stripes and adjacent dark stripes;
step 3, taking the longitude and latitude value of the center of the front wave crest line of the internal wave in the remote sensing image as the occurrence position of the internal wave at the imaging moment, obtaining the total water depth and the seawater temperature vertical profile of the position, and calculating to obtain the water depth h of the upper ocean layer1And the depth h of the ocean's lower water2；
Step 4, taking the ratio of the dimensionless frequency dispersion coefficient to the dimensionless nonlinear coefficient square as a judgment parameter, and taking the extracted half amplitude width delta of the internal wave and the depth h of the upper layer of the ocean1And the depth h of the ocean's lower water2Substituting, and calculating to obtain the value of the judgment parameter x;
step 5, determining an internal wave amplitude remote sensing inversion method: when the decision parameter χ is less than 10, adopting an inner wave amplitude inversion method based on a Korteweg-de Vries (KdV) equation, and when the decision parameter χ is more than 10, adopting an inner wave amplitude inversion method based on a nonlinear Schrodinger (NLS) equation;
step 6, utilizing the internal wave remote sensing inversion method determined in the step 5 to obtain the amplitude eta of the internal wave on the remote sensing image through inversion0。
Further, in step 1, the pretreatment specifically includes the following steps:
1) opening original image data by utilizing ENVI software, and carrying out Radiometric Calibration on an image in a Radiometric Calibration module;
2) performing Atmospheric Correction on the image subjected to radiation calibration in an Atmospheric Correction Module;
3) performing Orthorectification on the image after atmospheric rectification by using a tool in the ortho rectification;
4) performing Geometric Correction on the image subjected to the direct Correction by using a tool in the Geometric Correction;
5) and outputting the geometrically corrected image.
Further, step 2 specifically includes the following steps:
1) opening the preprocessed remote sensing image by utilizing ENVI software, zooming to the region of the ocean internal wave in the image, and drawing an internal wave crest line by using a drawing tool;
2) after determining the crest line of the internal wave, drawing an internal wave direction line vertical to the crest line according to the wave direction;
3) drawing gray value distribution of the image along the inner wave direction line, determining the positions of the light stripes and the dark stripes according to the maximum value and the minimum value of the gray value, and measuring to obtain the distance l between the adjacent light stripes and the adjacent dark stripes;
4) and obtaining the half amplitude width delta of the internal wave according to the linear relation between the spacing l and the half amplitude width delta determined by a peak-to-peak method.
Further, in step 3, the depth h of the upper ocean layer water1And the depth h of the ocean's lower water2The calculation specifically comprises the following steps:
1) converting the seawater temperature vertical profile into a buoyancy frequency vertical profile by using an oceans toolkit in an MATLAB program, and searching the water layer depth where the maximum buoyancy frequency is located by using the program, wherein the depth is the water depth h of the upper ocean layer1；
2) Total water depth and seaDepth h of upper water1Is the difference value of the ocean lower layer water depth h2。
Further, in step 4, the calculation of the determination parameter specifically includes the following steps:
1) the expression of the decision parameter χ is
Figure RE-GDA0003119336960000031
2) The expressions of the dimensionless nonlinear coefficient A and the dimensionless frequency dispersion coefficient B are respectively
Figure RE-GDA0003119336960000032
Figure RE-GDA0003119336960000033
3) Substituting the expressions of A and B, and finally calculating to obtain a judgment parameter chi of
Figure RE-GDA0003119336960000034
Further, in step 5, the method for inverting the amplitude of the internal wave based on the KdV equation specifically includes the following steps:
1) in the KdV equation under the two-layer layered model, the internal wave amplitude η0Is expressed as
Figure RE-GDA0003119336960000035
Wherein, alpha and beta are respectively a nonlinear coefficient and a dispersion coefficient;
2) according to the depth h of the upper sea layer1And the depth h of the ocean's lower water2Calculating a nonlinear coefficient alpha and a dispersion coefficient beta;
3) extracting the half amplitude width delta of the internal wave from the remote sensing image, substituting the width delta into the expression to obtain the internal waveWave amplitude η0。
Further, in step 5, the method for inverting the amplitude of the internal wave based on the NLS equation specifically includes the following steps:
1) in NLS equation under two-layer layered model, internal wave amplitude eta0Is expressed as
Figure RE-GDA0003119336960000041
Wherein, alpha and beta are respectively a nonlinear coefficient and a dispersion coefficient;
2) according to the depth h of the upper sea layer1And the depth h of the ocean's lower water2Calculating a nonlinear coefficient alpha and a dispersion coefficient beta;
3) extracting the half amplitude width delta of the internal wave from the remote sensing image, substituting the width delta into the expression to obtain the amplitude eta of the internal wave0。
Further, in step 6, the method for inverting the amplitude of the internal wave specifically includes the following steps:
1) when the determination parameter χ is smaller than 10, the internal wave amplitude η0Calculated by the following formula
Figure RE-GDA0003119336960000042
2) When the determination parameter χ is greater than 10, the internal wave amplitude η0Calculated by the following formula
Figure RE-GDA0003119336960000043
Has the advantages that: compared with the prior art, the ocean internal wave amplitude remote sensing inversion method constrained by the power conditions takes the ratio of the dimensionless frequency dispersion coefficient to the square of the dimensionless nonlinear coefficient as a judgment parameter, determines a judgment standard according to the relation between the parameter and a critical value, selects the corresponding internal wave amplitude inversion method, solves the problem that the traditional internal wave amplitude inversion method cannot be generally applied to different remote sensing images, and can accurately extract the internal wave amplitudes of different remote sensing images.
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FIG. 1 is a schematic flow diagram of the present invention.
Detailed Description
The invention is explained in detail below with reference to the figures and examples.
As shown in FIG. 1, the marine internal wave amplitude remote sensing inversion method based on dynamic condition constraint comprises the following steps:
step 1, collecting and preprocessing ocean internal wave satellite remote sensing image data;
step 2, extracting an internal wave crest line in the remote sensing image, and measuring to obtain an internal wave half-amplitude width delta according to a distance l between adjacent bright stripes and adjacent dark stripes;
step 3, taking the longitude and latitude value of the center of the front wave crest line of the internal wave in the remote sensing image as the occurrence position of the internal wave at the imaging moment, obtaining the total water depth and the seawater temperature vertical profile of the position, and calculating to obtain the water depth h of the upper ocean layer1And the depth h of the ocean's lower water2；
Step 4, taking the ratio of the dimensionless frequency dispersion coefficient to the dimensionless nonlinear coefficient square as a judgment parameter, and taking the extracted half amplitude width delta of the internal wave and the depth h of the upper layer of the ocean1And the depth h of the ocean's lower water2Substituting, and calculating to obtain the value of the judgment parameter x;
step 5, determining an internal wave amplitude remote sensing inversion method: when the decision parameter χ is less than 10, adopting an inner wave amplitude inversion method based on a Korteweg-de Vries (KdV) equation, and when the decision parameter χ is more than 10, adopting an inner wave amplitude inversion method based on a nonlinear Schrodinger (NLS) equation;
and 6, utilizing the internal wave remote sensing inversion method determined in the step 5 to invert to obtain the amplitude of the internal wave on the remote sensing image.
In step 1, the pretreatment specifically comprises the following steps:
1) opening original image data by utilizing ENVI software, and carrying out Radiometric Calibration on an image in a Radiometric Calibration module;
2) performing Atmospheric Correction on the image subjected to radiation calibration in an Atmospheric Correction Module;
3) performing Orthorectification on the image after atmospheric rectification by using a tool in the ortho rectification;
4) performing Geometric Correction on the image subjected to the direct Correction by using a tool in the Geometric Correction;
5) and outputting the geometrically corrected image.
In the step 2, the method specifically comprises the following steps:
1) opening the preprocessed remote sensing image by utilizing ENVI software, zooming to the region of the ocean internal wave in the image, and drawing an internal wave crest line by using a drawing tool;
2) after determining the crest line of the internal wave, drawing an internal wave direction line vertical to the crest line according to the wave direction;
3) drawing gray value distribution of the image along the inner wave direction line, determining the positions of the light stripes and the dark stripes according to the maximum value and the minimum value of the gray value, and measuring to obtain the distance l between the adjacent light stripes and the adjacent dark stripes;
4) and obtaining the half amplitude width delta of the internal wave according to the linear relation between the spacing l and the half amplitude width delta determined by a peak-to-peak method.
In step 3, the depth h of the upper ocean layer water1And the depth h of the ocean's lower water2The calculation specifically comprises the following steps:
1) converting the seawater temperature vertical profile into a buoyancy frequency vertical profile by using an oceans toolkit in an MATLAB program, and searching the water layer depth where the maximum buoyancy frequency is located by using the program, wherein the depth is the water depth h of the upper ocean layer1；
2) Total depth of water and depth of water in upper ocean layer h1Is the difference value of the ocean lower layer water depth h2。
In step 4, the calculation of the decision parameter specifically includes the following steps:
1) the expression of the decision parameter χ is
Figure RE-GDA0003119336960000061
2) The expressions of the dimensionless nonlinear coefficient A and the dimensionless frequency dispersion coefficient B are respectively
Figure RE-GDA0003119336960000062
Figure RE-GDA0003119336960000063
3) Substituting the expressions of A and B, and finally calculating to obtain a judgment parameter chi of
Figure RE-GDA0003119336960000064
In step 5, the method for inverting the amplitude of the internal wave based on the KdV equation specifically comprises the following steps:
1) in the KdV equation under the two-layer layered model, the internal wave amplitude η0Is expressed as
Figure RE-GDA0003119336960000065
Wherein, alpha and beta are respectively a nonlinear coefficient and a dispersion coefficient;
2) according to the depth h of the upper sea layer1And the depth h of the ocean's lower water2Calculating a nonlinear coefficient alpha and a dispersion coefficient beta;
3) extracting the half amplitude width delta of the internal wave from the remote sensing image, substituting the width delta into the expression to obtain the amplitude eta of the internal wave0。
In step 5, the inner wave amplitude inversion method based on the NLS equation specifically includes the following steps:
1) in NLS equation under two-layer layered model, internal wave amplitude eta0Is expressed as
Figure RE-GDA0003119336960000066
Wherein, alpha and beta are respectively a nonlinear coefficient and a dispersion coefficient;
2) according to the depth h of the upper sea layer1And the depth h of the ocean's lower water2Calculating a nonlinear coefficient alpha and a dispersion coefficient beta;
3) extracting the half amplitude width delta of the internal wave from the remote sensing image, substituting the width delta into the expression to obtain the amplitude eta of the internal wave0。
In step 6, the internal wave amplitude inversion method specifically comprises the following steps:
1) when the determination parameter χ is smaller than 10, the internal wave amplitude η0Calculated by the following formula
Figure RE-GDA0003119336960000071
2) When the determination parameter χ is greater than 10, the internal wave amplitude η0Calculated by the following formula
Figure RE-GDA0003119336960000072
Examples
The marine internal wave amplitude remote sensing inversion method based on dynamic condition constraint comprises the following steps:
step 1, the observation sea area of the embodiment of the invention is the sea area near the east sand island in the north of the south China sea, the observation time is 7 months in 2017 and 10 days to 13 days, 7 scenes (see table 1 below) of optical satellite images covered by ocean internal waves of the sea area are collected, and the optical satellite images are preprocessed by utilizing ENVI software.
The following table 1 is a detailed information table of 7 scene optical remote sensing images
Figure RE-GDA0003119336960000073
Step 2, according to the embodiment of the invention, the ENVI software is used for extracting the crest line of the ocean internal wave in the 7-scene remote sensing image and the distance l between the adjacent bright stripe and the dark stripe, and the half-amplitude width delta of the internal wave is obtained according to a peak-to-peak method, namely the distance l is 1.32 times of the half-amplitude width delta.
Step 3, the embodiment of the invention firstly determines the occurrence position of the internal wave in the 7-scene image according to the central position of the front wave crest line of the internal wave, and then respectively acquires the corresponding water depth h of the upper ocean layer by combining the ETOPO data and the CMEMS temperature field data1And the depth h of the ocean's lower water2。
Step 4, the embodiment of the invention takes the ratio of the dimensionless frequency dispersion coefficient to the dimensionless nonlinear coefficient square as a determination parameter chi, and the expression of the judgment parameter chi is
Figure RE-GDA0003119336960000081
Extracting half amplitude width delta of internal wave and water depth h of upper layer of ocean in 7-scene image1And the depth h of the ocean's lower water2And substituting, and calculating to obtain a corresponding determination parameter chi numerical value.
The following table 2 is a table of characteristic parameters and corresponding decision parameters of ocean internal waves in 7 scene optical remote sensing images
Figure RE-GDA0003119336960000082
Step 5, in the embodiment, by comparing the relation between the judgment parameter χ of the ocean internal wave in the 7-scene remote sensing image and the critical value 10, determining the corresponding internal wave amplitude remote sensing inversion method: when χ is less than 10, adopting an internal wave amplitude inversion method based on a Korteweg-de Vries (KdV) equation; and when the chi is larger than 10, adopting an inner wave amplitude inversion method based on a nonlinear Schrodinger (NLS) equation.
Step 6, in the embodiment of the invention, the amplitude eta of the ocean internal wave on the 7-scene remote sensing image is obtained by inversion through the inversion method determined by the judgment standard in the step 50。
Table 3 below shows the comparison of the results of other ocean internal wave amplitude inversion methods and the inversion method of the present embodiment
Figure RE-GDA0003119336960000083
From the above table, compared with the actual measurement amplitude observed by the subsurface buoy, the inversion method of the invention is generally applicable to the inversion of the internal wave amplitude on different remote sensing images compared with other methods in the prior art.
Although the present invention has been described with reference to the preferred embodiments, it should be understood that various changes and modifications can be made therein by those skilled in the art without departing from the spirit and scope of the invention as defined by the appended claims.

Claims (8)

1. A dynamic condition constrained ocean internal wave amplitude remote sensing inversion method is characterized by comprising the following steps: the method comprises the following steps:
step 1, collecting and preprocessing ocean internal wave satellite remote sensing image data;
step 2, extracting an internal wave crest line in the remote sensing image, and measuring to obtain an internal wave half-amplitude width delta according to a distance l between adjacent bright stripes and adjacent dark stripes;
step 3, taking the longitude and latitude value of the center of the front wave crest line of the internal wave in the remote sensing image as the occurrence position of the internal wave at the imaging moment, obtaining the total water depth and the seawater temperature vertical profile of the position, and calculating to obtain the water depth h of the upper ocean layer1And the depth h of the ocean's lower water2；
Step 4, taking the ratio of the dimensionless frequency dispersion coefficient to the dimensionless nonlinear coefficient square as a judgment parameter, and taking the extracted half amplitude width delta of the internal wave and the depth h of the upper layer of the ocean1And the depth h of the ocean's lower water2Substituting, and calculating to obtain the value of the judgment parameter x;
step 5, determining an internal wave amplitude remote sensing inversion method: when the decision parameter χ is smaller than 10, adopting an inner wave amplitude inversion method based on a Korteweg-de Vries equation, and when the decision parameter χ is larger than 10, adopting an inner wave amplitude inversion method based on a nonlinear Schrodinger equation;
step 6, utilizing the internal wave remote sensing inversion method determined in the step 5 to obtain the amplitude eta of the internal wave on the remote sensing image through inversion0。
2. The marine internal wave amplitude remote sensing inversion method based on dynamic condition constraint is characterized by comprising the following steps of: in the step 1, the pretreatment specifically comprises the following steps:
1) opening original image data by utilizing ENVI software, and carrying out Radiometric Calibration on an image in a Radiometric Calibration module;
2) performing Atmospheric Correction on the image subjected to radiation calibration in an Atmospheric Correction Module;
3) performing Orthorectification on the image after atmospheric rectification by using a tool in the ortho rectification;
4) performing Geometric Correction on the image subjected to the direct Correction by using a tool in the Geometric Correction;
5) and outputting the geometrically corrected image.
3. The marine internal wave amplitude remote sensing inversion method based on dynamic condition constraint is characterized by comprising the following steps of: the step 2 specifically comprises the following steps:
1) opening the preprocessed remote sensing image by utilizing ENVI software, zooming to the region of the ocean internal wave in the image, and drawing an internal wave crest line by using a drawing tool;
2) after determining the crest line of the internal wave, drawing an internal wave direction line vertical to the crest line according to the wave direction;
3) drawing gray value distribution of the image along the inner wave direction line, determining the positions of the light stripes and the dark stripes according to the maximum value and the minimum value of the gray value, and measuring to obtain the distance l between the adjacent light stripes and the adjacent dark stripes;
4) and obtaining the half amplitude width delta of the internal wave according to the linear relation between the spacing l and the half amplitude width delta determined by a peak-to-peak method.
4. The remote sensing inversion method of marine internal wave amplitude constrained by dynamic conditions as claimed in claim 3, characterized in that: in the step 3, the depth h of the water at the upper layer of the ocean1And the depth h of the ocean's lower water2The calculation specifically comprises the following steps:
1) converting the seawater temperature vertical profile into a buoyancy frequency vertical profile by using an oceans toolkit in an MATLAB program, and searching the water layer depth where the maximum buoyancy frequency is located by using the program, wherein the depth is the water depth h of the upper ocean layer1；
2) Total depth of water and depth of water in upper ocean layer h1Is the difference value of the ocean lower layer water depth h2。
5. The dynamic condition constrained ocean internal wave amplitude remote sensing inversion method according to claim 4, characterized in that: in the step 4, the calculation of the determination parameter specifically includes the following steps:
1) the expression of the decision parameter χ is
Figure FDA0002963700020000021
2) The expressions of the dimensionless nonlinear coefficient A and the dimensionless frequency dispersion coefficient B are respectively
Figure FDA0002963700020000022
Figure FDA0002963700020000023
3) Substituting the expressions of A and B, and finally calculating to obtain a judgment parameter chi of
Figure FDA0002963700020000024
6. The dynamic condition constrained ocean internal wave amplitude remote sensing inversion method according to claim 5, characterized in that: in the step 5, the method for inverting the amplitude of the internal wave based on the Korteweg-de Vries equation specifically comprises the following steps:
1) in the KdV equation under the two-layer layered model, the internal wave amplitude η0Is expressed as
Figure FDA0002963700020000025
Wherein, alpha and beta are respectively a nonlinear coefficient and a dispersion coefficient;
2) according to the depth h of the upper sea layer1And the depth h of the ocean's lower water2Calculating a nonlinear coefficient alpha and a dispersion coefficient beta;
3) extracting the half amplitude width delta of the internal wave from the remote sensing image, substituting the half amplitude width delta into the expression to obtain the amplitude eta of the internal wave0。
7. The marine internal wave amplitude remote sensing inversion method based on dynamic condition constraint as claimed in claim 6, characterized in that: in the step 5, the inner wave amplitude inversion method based on the nonlinear schrodinger (NLS) equation specifically comprises the following steps:
1) in NLS equation under two-layer layered model, internal wave amplitude eta0Is expressed as
Figure FDA0002963700020000031
Wherein, alpha and beta are respectively a nonlinear coefficient and a dispersion coefficient;
2) according to the depth h of the upper sea layer1And the depth h of the ocean's lower water2Calculating a nonlinear coefficient alpha and a dispersion coefficient beta;
3) extracting the half amplitude width delta of the internal wave from the remote sensing image, substituting the half amplitude width delta into the expression to obtain the amplitude eta of the internal wave0。
8. The remote sensing inversion method of marine internal wave amplitude constrained by dynamic conditions as claimed in claim 7, characterized in that: in step 6, the internal wave amplitude inversion method specifically includes the following steps:
1) when in useWhen the determination parameter χ is smaller than 10, the internal wave amplitude η0Calculated by the following formula
Figure FDA0002963700020000032
2) When the determination parameter χ is greater than 10, the internal wave amplitude η0Calculated by the following formula
Figure FDA0002963700020000033
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CN114282574A (en) * 2021-12-16 2022-04-05 中国人民解放军海军潜艇学院 Inversion method and system for ocean internal wave characteristic parameters

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CN112099110A (en) * 2020-09-17 2020-12-18 中国科学院海洋研究所 Ocean internal wave forecasting method based on machine learning and remote sensing data
CN112113545A (en) * 2020-09-17 2020-12-22 中国科学院海洋研究所 Inner wave amplitude inversion method based on multi-dimensional sea surface information

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Publication number Priority date Publication date Assignee Title
CN112099110A (en) * 2020-09-17 2020-12-18 中国科学院海洋研究所 Ocean internal wave forecasting method based on machine learning and remote sensing data
CN112113545A (en) * 2020-09-17 2020-12-22 中国科学院海洋研究所 Inner wave amplitude inversion method based on multi-dimensional sea surface information

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* Cited by examiner, † Cited by third party
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CN114282574A (en) * 2021-12-16 2022-04-05 中国人民解放军海军潜艇学院 Inversion method and system for ocean internal wave characteristic parameters

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