CN107730582A - Wave 3 D displaying method based on ocean remote sensing data - Google Patents

Wave 3 D displaying method based on ocean remote sensing data Download PDF

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CN107730582A
CN107730582A CN201710856304.1A CN201710856304A CN107730582A CN 107730582 A CN107730582 A CN 107730582A CN 201710856304 A CN201710856304 A CN 201710856304A CN 107730582 A CN107730582 A CN 107730582A
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CN107730582B (en
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李自立
刘奥琦
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Guangxi Normal University
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    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T17/00—Three dimensional [3D] modelling, e.g. data description of 3D objects
    • G06T17/05—Geographic models
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S13/00—Systems using the reflection or reradiation of radio waves, e.g. radar systems; Analogous systems using reflection or reradiation of waves whose nature or wavelength is irrelevant or unspecified
    • G01S13/88—Radar or analogous systems specially adapted for specific applications
    • G01S13/89—Radar or analogous systems specially adapted for specific applications for mapping or imaging
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S7/00—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00
    • G01S7/02—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S13/00
    • G01S7/04—Display arrangements

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Abstract

The invention discloses a kind of wave 3 D displaying method based on ocean remote sensing data, by extracting second order spectrum inverting ocean wave parameter from RADOP spectrogram, using gram in the preliminary three-dimensional wave of golden spatial interpolation algorithm filling mesh node simulation traveling wave wave of going forward side by side it is smooth, interpolation processing is finally carried out for time series using cubic spline interpolation algorithm, time interval is continuously got up so as to realize Dynamic Announce, comprise the following steps that：（One）Second order spectrum is extracted from RADOP spectrogram；(two）Using gram in golden spatial interpolation algorithm filling mesh node, it is smooth to simulate preliminary three-dimensional wave traveling wave wave of going forward side by side；（Three）Interpolation processing is carried out for time series using cubic spline interpolation algorithm, makes time interval continuously get up to realize Dynamic Announce.Technical scheme is used to verify wave Three-dimensional Display with measured data, more suitable for the monitoring application of marine environment.

Description

Wave 3 D displaying method based on ocean remote sensing data
Technical field
The present invention relates to radar remote sensing technology field, more particularly to a kind of wave Three-dimensional Display based on ocean remote sensing data Method.
Background technology
With the development of radar remote sensing technology, large-scale Real-time Remote Sensing is carried out to ocean with bank base high-frequency ground wave radar Monitoring has been carried out.After the real time data that remote sensing receives is obtained, ocean table can be obtained by data analysis and feature extraction The motion state parameterses and its distribution situation in face, these data include the flow velocity and flow direction of ocean current, the height of wave and intensity, And the information such as wind speed of ocean surface.Because the marine context of monitoring is very wide, therefore the information content disposably obtained is very Big, if it is unpractical all to embody or show in digital form.
At present, it is all based on for the research of three-dimensional wave, conventional proposition method in the aspect of simulation, is more note Wave form is similar again, adds measured data to verify, therefore pure simulation is not enough to be applied to marine environment Monitoring.
The content of the invention
In view of the shortcomings of the prior art, problem solved by the invention, which is to provide one kind, to verify wave with measured data The remote-sensing monitoring method of Three-dimensional Display.
In order to solve the above technical problems, the technical solution adopted by the present invention is a kind of wave three based on ocean remote sensing data Tie up display methods, by extracting second order spectrum inverting ocean wave parameter from RADOP spectrogram, using gram in golden space insert The preliminary three-dimensional wave of value-based algorithm filling mesh node simulation goes forward side by side traveling wave wave smoothly, finally using cubic spline interpolation algorithm pair Interpolation processing is carried out in time series, time interval is continuously got up so as to realize Dynamic Announce, comprises the following steps that：
(1) second order spectrum is extracted from RADOP spectrogram, including as follows step by step：
(1) Doppler spectrum of a certain distance element is chosen from a measured data, according to the location estimation at single order peak The position of second order spectrum；
(2) four regions are selected in second order spectrum area, extreme point, i.e., the institute in this region is searched for by matlab programming simulations There are maximum and minimum point, the presence of no second order spectrum is then illustrated in the absence of extreme point, if it is present continuing search for out one The minimum point match point of rank peak both sides；
Further, for the border of accurate second order spectrum, minimum match point region is screened, carried out by matlab Data processing, calculate the signal to noise ratio of minimum point institute inclusion region.
(3) comprehensive analysis is carried out according to the marine site sea situation of the different fields of selection, suitable threshold value is set, when signal to noise ratio is more than During taken threshold value, second order spectrum extraction is completed.
Under normal circumstances, threshold value is chosen as 5dB, and further, it is anti-that the threshold value value of signal to noise ratio for 15dB can improve ocean wave spectrum Drill precision.
(2) using gram in golden spatial interpolation algorithm filling mesh node, it is flat to simulate preliminary three-dimensional wave traveling wave wave of going forward side by side It is sliding, it is specifically as follows step by step：
(1) original, deposit array is inputted；
(2) according to the distribution of data, it is determined that the regional extent and sizing grid of wanted interpolation, are carried out at gridding to region Reason, simulate preliminary three-dimensional wave grid surface so that each mesh node is measured data；
(3) to data detection and analysis, the distance between given data point set size is calculated, if it is especially small distance value to be present Situation, or two data point coordinates particularly near situation, then to reject these data points；
(4) understand the space structure of variable, verify whether selected variation function meets reality；In each eyeball, root The average minimum of the square-error of the Kriging estimation value and the actual measurement point value that are calculated according to surrounding point, come judge between data point whether In the presence of certain binding character, binding character be present and carry out next step operation again；
(5) by gram in golden equation group draw weight coefficient λi；
(6) obtained by the relation of weight coefficient and sampled point and be estimated point value Z (x0), wherein n is interpolation number；
(7) repeat step 3) to step 6) estimation point value is obtained, it is interpolated on all mesh points, golden space is inserted in completing gram Value.
Golden spatial interpolation algorithm in described gram, its method are as follows：
For regional change amount Z (x), if it is in a series of sampled point xi(i=1,2,,, n) observation at place is Z (xi) (i=1,2,,, n), then some mesh node X in regionnEstimate Z (the x at place0) can there is a linear combination to estimate Meter, i.e.,：
λ in formulaiIt is weight coefficient, premised on Z (x) obeys intrinsic hypothesis, there is golden equation group in following gram：
In formula, γ (xi, xj) it is sampled point xiAnd xjBetween variation function value, μ is Lagrangian constant.
(3) interpolation processing is carried out for time series using cubic spline interpolation algorithm, time interval is continuously got up reality Existing Dynamic Announce, including as follows step by step：
(1) definition of cubic spline function is set：
If f (x) is a continuously differentiable function on section [a, b], one group of basic point is given on section [a, b]：
A=x0＜ x1＜ x2＜ ... ＜ xn=b
Function s (x) meets condition：
1) s (x) is in each subinterval [xi, xi+1] it is that number is no more than three times multinomial on (i=0,1,2 ..., n-1) Formula；
2) s (x) has Second Order Continuous derivative on section [a, b]；
Then s (x) is claimed to be defined in the cubic spline functions on [a, b], x0, x1, x2... it is referred to as batten node, its Middle x1..., xn-1Referred to as interior knot, x0, xnReferred to as boundary node；
(2) cubic spline function is solved：
If cubic spline function S (x) is in each subinterval [xj-1, xj] on have expression formula：
S (x)=Sj(x)=ajx3+bjx2+cjx+dj x∈(xj-1, xj), j=1,2...n；
Wherein aj, bj, cj, djFor undetermined constant, interpolation condition is：
1)S(xj)=f (xj) j=0,1,2...n；
2) continuous and slickness condition at (n-1) interior knot：
S(xj- 0)=S (xj+ 0), S ' (xj- 0)=s (xj+ 0), S " (xj- 0)=S (xj+0)；J=1,2...n；
For undetermined coefficient aj, bj, cj, dj, j=1,2...n；That is 4n unknowm coefficient, and interpolation condition is 4n-2, Also lack two, it is therefore necessary to provide two conditions and be referred to as boundary condition, there is following three class：
The first kind：The first derivative of known two-end-point
Second class：Known two-end-point second dervative
Work as M0=MnIt is natural boundary conditions when=0
3rd class：Periodic boundary condition
(3) interpolation of cubic spline function is used：
In each subinterval [xj-1, xj] on, determine the cubic polynomial S for meeting above-mentioned interpolation conditionj(x) S is obtained (x),
More interpolation points are obtained between the time of data, make time interval continuously, so as to realize three-dimensional wave Dynamic Announce.
Technical scheme is used to verify wave Three-dimensional Display with measured data, more suitable for marine environment Monitoring application.
Brief description of the drawings
Fig. 1 is schematic flow sheet of the present invention；
Fig. 2 is second order spectrum region division schematic diagram；
Fig. 3 is the extracting method of second order spectrum；
Fig. 4 is the three-dimensional wave figure for not using interpolation algorithm；
Fig. 5 is to use the three-dimensional wave figure after interpolation algorithm.
Embodiment
The embodiment of the present invention is further described below in conjunction with the accompanying drawings, but is not the limit to the present invention It is fixed.
Fig. 1 shows a kind of wave 3 D displaying method based on ocean remote sensing data, by from RADOP frequency spectrum Second order spectrum inverting ocean wave parameter is extracted in figure, using gram in golden spatial interpolation algorithm filling mesh node simulate preliminary three-dimensional Wave traveling wave wave of going forward side by side is smooth, finally carries out interpolation processing for time series using cubic spline interpolation algorithm, makes between the time Get up to realize Dynamic Announce every continuously；Comprise the following steps that：
(1) extract second order spectrum from RADOP spectrogram, as shown in figure 3, including it is following step by step：
(1) Doppler spectrum of a certain distance element is chosen from a measured data, according to the location estimation at single order peak The position of second order spectrum；
The peak that simultaneous two symmetrical on zero frequency in spectrogram and amplitude is substantially dominant is single order peak, with Single order peak close to region be second order spectrum area, in the region select second order spectrum four approximate regions, system of selection such as Fig. 2 It is shown.
2) four regions are selected in second order spectrum area, extreme point, i.e., the institute in this region is searched for by matlab programming simulations There are maximum and minimum point, the presence of no second order spectrum is then illustrated in the absence of extreme point, if it is present continuing search for out one The minimum point match point of rank peak both sides.
Further, for the border of accurate second order spectrum, minimum match point region is screened, carried out by matlab Data processing, calculate the signal to noise ratio of minimum point institute inclusion region.
3) comprehensive analysis is carried out according to the marine site sea situation of the different fields of selection, suitable threshold value is set, when signal to noise ratio is more than During taken threshold value, second order spectrum extraction is completed.
Threshold value under normal circumstances, is chosen as 5dB；Further, threshold value value is that 15dB can improve ocean wave spectrum inversion accuracy.
(2) using gram in golden spatial interpolation algorithm filling mesh node, it is flat to simulate preliminary three-dimensional wave traveling wave wave of going forward side by side It is sliding, it is specifically as follows step by step：
(1) original, deposit array is inputted；
(2) according to the distribution of data, it is determined that the regional extent and sizing grid of wanted interpolation, are carried out at gridding to region Reason, simulate preliminary three-dimensional wave grid surface so that each mesh node is measured data；
(3) to data detection and analysis, the distance between given data point set size is calculated, if it is especially small distance value to be present Situation, or two data point coordinates particularly near situation, then to reject these data points；
(4) understand the space structure of variable, verify whether selected variation function meets reality；In each eyeball, root The average minimum of the square-error of the Kriging estimation value and the actual measurement point value that are calculated according to surrounding point, come judge between data point whether In the presence of certain binding character, binding character be present and carry out next step operation again；
(5) by gram in golden equation group draw weight coefficient λi；
(6) obtained by the relation of weight coefficient and sampled point and be estimated point value Z (x0), wherein n is interpolation number；
(7) repeat step 3) to step 6) estimation point value is obtained, it is interpolated on all mesh points, golden space is inserted in completing gram Value.
Golden spatial interpolation algorithm in described gram, its method are as follows：
For regional change amount Z (x), if it is in a series of sampled point xi(i=1,2,,, n) observation at place is Z (xi) (i=1,2,,, n), then some mesh node X in regionnEstimate Z (the x at place0) can there is a linear combination to estimate Meter, i.e.,：
λ in formulaiWeight coefficient, premised on Z (x) obeys intrinsic hypothesis, have it is following common gram in golden equation group：
In formula, γ (xi, xj) it is sampled point xiAnd xjBetween variation function value, μ is Lagrangian constant.
(3) interpolation processing is carried out for time series using cubic spline interpolation algorithm, time interval is continuously got up reality Existing Dynamic Announce, including as follows step by step：
(1) definition of cubic spline function is set：
If f (x) is a continuously differentiable function on section [a, b], one group of basic point is given on section [a, b]：
A=x0＜ x1＜ x2＜ ... ＜ xn=b
Function s (x) meets condition：
1) s (x) is in each subinterval [xi, xi+1] it is that number is no more than three times multinomial on (i=0,1,2 ..., n-1) Formula；
2) s (x) has Second Order Continuous derivative on section [a, b]；
Then s (x) is claimed to be defined in the cubic spline functions on [a, b], x0, x1, x2... it is referred to as batten node, its Middle x1..., xn-1Referred to as interior knot, x0, xnReferred to as boundary node；
(2) cubic spline function is solved：
If cubic spline function S (x) is in each subinterval [xj-1, xj] on have expression formula：
S (x)=Sj(x)=ajx3+bjx2+cjx+dj x∈(xj-1, xj), j=1,2...n；
Wherein aj, bj, cj, djFor undetermined constant, interpolation condition is：
1)S(xj)=f (xj) j=0,1,2...n；
2) continuous and slickness condition at (n-1) interior knot：
S(xj- 0)=S (xj+ 0), S ' (xj- 0)=s (xj+ 0), S " (xj- 0)=S (xj+0)；J=1,2...n；
For undetermined coefficient aj, bj, cj, dj, j=1,2...n；That is 4n unknowm coefficient, and interpolation condition is 4n-2, Also lack two, it is therefore necessary to provide two conditions and be referred to as boundary condition, there is following three class：
The first kind：The first derivative of known two-end-point
Second class：Known two-end-point second dervative
Work as M0=MnIt is natural boundary conditions when=0
3rd class：Periodic boundary condition
(3) interpolation of cubic spline function is used：
In each subinterval [xj-1, xj] on, determine the cubic polynomial S for meeting above-mentioned interpolation conditionj(x) S is obtained (x),
More interpolation points are obtained between the time of data, make time interval continuously, so as to realize three-dimensional wave Dynamic Announce.
Fig. 4 shows the three-dimensional wave figure for not using interpolation algorithm, and Fig. 5 is shown using the three-dimensional wave after interpolation algorithm Figure, understand not use the three-dimensional wave figure of interpolation algorithm from Fig. 4 and Fig. 5 contrasts, coarser scale is low.Figure after interpolation algorithm As smoothened, dynamic wave image is also more directly perceived, proper reality, improves visual effect.
Technical scheme is used to verify wave Three-dimensional Display with measured data, more suitable for marine environment Monitoring application.
Embodiments of the present invention are made that with detailed description above in association with accompanying drawing, but the present invention be not limited to it is described Embodiment.To those skilled in the art, without departing from the principles and spirit of the present invention, these are implemented Mode carries out various change, modification, replacement and modification and still fallen within protection scope of the present invention.

Claims (5)

  1. A kind of 1. wave 3 D displaying method based on ocean remote sensing data, it is characterised in that：By from RADOP frequency spectrum Second order spectrum inverting wave high parameter is extracted in figure, using gram in golden spatial interpolation algorithm filling mesh node simulate preliminary three-dimensional Wave traveling wave wave of going forward side by side is smooth, finally carries out interpolation processing for time series using cubic spline interpolation algorithm, makes between the time Every continuously get up so as to realize Dynamic Announce, comprise the following steps that：
    (1) second order spectrum is extracted from RADOP spectrogram, including as follows step by step：
    (1) Doppler spectrum of a certain distance element is chosen from a measured data, according to the location estimation second order at single order peak The position of spectrum；
    (2) four regions are selected in second order spectrum area, extreme point, i.e., all poles in this region is searched for by matlab programming simulations Big value and minimum point, the presence of no second order spectrum are then illustrated in the absence of extreme point, if it is present continuing search for out single order peak The minimum point match point of both sides；
    (3) comprehensive analysis is carried out according to the marine site sea situation of the different fields of selection, sets suitable threshold value, taken when signal to noise ratio is more than During threshold value, second order spectrum extraction is completed；
    (2) golden spatial interpolation algorithm filling mesh node in utilization gram, simulate preliminary three-dimensional wave and go forward side by side traveling wave wave smoothly, It is specific as follows step by step：
    (1) original, deposit array is inputted；
    (2) according to the distribution of data, it is determined that the regional extent and sizing grid of wanted interpolation, gridding processing is carried out to region, Simulate preliminary three-dimensional wave grid surface so that each mesh node is measured data；
    (3) to data detection and analysis, the distance between given data point set size is calculated, if the especially small feelings of distance value be present Condition, or two data point coordinates particularly near situation, then to reject these data points；
    (4) understand the space structure of variable, verify whether selected variation function meets reality；In each eyeball, according to week A Kriging estimation value calculated and the average minimum of square-error of the actual measurement point value are enclosed, to judge to whether there is between data point Certain binding character, binding character be present and carry out next step operation again；
    (5) by gram in golden equation group draw weight coefficient λi；
    (6) obtained by the relation of weight coefficient and sampled point and be estimated point value Z (x0), wherein n is interpolation number；
    (7) repeat step 3) to step 6) estimation point value is obtained, it is interpolated on all mesh points, golden space interpolation in completing gram；
    (3) interpolation processing is carried out for time series using cubic spline interpolation algorithm, make time interval continuously get up to realize it is dynamic State shows, including as follows step by step：
    (1) definition of cubic spline function is set：
    If f (x) is a continuously differentiable function on section [a, b], one group of basic point is given on section [a, b]：
    A=x0＜ x1＜ x2＜ ... ＜ xn=b
    Function s (x) meets condition：
    1) s (x) is in each subinterval [xi, xi+1] it is that number is no more than multinomial three times on (i=0,1,2 ..., n-1)；
    2) s (x) has Second Order Continuous derivative on section [a, b]；
    Then s (x) is claimed to be defined in the cubic spline functions on [a, b], x0, x1, x2... it is referred to as batten node, wherein x1..., xn-1Referred to as interior knot, x0, xnReferred to as boundary node；
    (2) cubic spline function is solved：
    If cubic spline function S (x) is in each subinterval [xj-1, xj] on have expression formula：
    S (x)=Sj(x)=ajx3+bjx2+cjx+dj x∈(xj-1, xj), j=1,2...n；
    Wherein aj, bj, cj, djFor undetermined constant, interpolation condition is：
    1)S(xj)=f (xj) j=0,1,2...n；
    2) continuous and slickness condition at (n-1) interior knot：
    S(xj- 0)=S (xj+ 0), S ' (xj- 0)=s (xj+ 0), S " (xj- 0)=S (xj+0)；J=1,2...n；
    For undetermined coefficient aj, bj, cj, dj, j=1,2...n；That is 4n unknowm coefficient, and interpolation condition is 4n-2, also lacks two It is individual, it is therefore necessary to provide two conditions and be referred to as boundary condition, there is following three class：
    The first kind：The first derivative of known two-end-point
    Second class：Known two-end-point second dervative
    Work as M0=MnIt is natural boundary conditions when=0
    3rd class：Periodic boundary condition
    (3) interpolation of cubic spline function is used：
    In each subinterval [xj-1, xj] on, determine the cubic polynomial S for meeting above-mentioned interpolation conditionj(x) S (x) is obtained,
    More interpolation points are obtained between the time of data, make time interval continuously, so as to realize the dynamic of three-dimensional wave State is shown.
  2. 2. the wave 3 D displaying method according to claim 1 based on ocean remote sensing data, it is characterised in that：Step (1) (2) step by step in, for the border of accurate second order spectrum, minimum match point region can be screened, passed through Matlab carries out data processing, calculates the signal to noise ratio of minimum point institute inclusion region.
  3. 3. the wave 3 D displaying method according to claim 1 or 2 based on ocean remote sensing data, it is characterised in that：Step Suddenly (3) step by step in (one), threshold value is chosen as 5dB.
  4. 4. the wave 3 D displaying method according to claim 3 based on ocean remote sensing data, it is characterised in that：Step (1) (3) step by step in, threshold value value are that 15dB can improve ocean wave spectrum inversion accuracy.
  5. 5. the wave 3 D displaying method according to claim 1 or 2 based on ocean remote sensing data, it is characterised in that：Step Suddenly described in (two) gram in golden spatial interpolation algorithm, its method is as follows：
    For regional change amount Z (x), if it is in a series of sampled point xi(i=1,2,,, n) observation at place is Z (xi)(i =1,2,,, n), then some mesh node X in regionnEstimate Z (the x at place0) can there is a linear combination to estimate, i.e.,：
    <mrow> <mi>Z</mi> <mrow> <mo>(</mo> <msub> <mi>x</mi> <mn>0</mn> </msub> <mo>)</mo> </mrow> <mo>=</mo> <munderover> <mo>&amp;Sigma;</mo> <mrow> <mi>i</mi> <mo>=</mo> <mn>1</mn> </mrow> <mi>n</mi> </munderover> <msub> <mi>&amp;lambda;</mi> <mi>i</mi> </msub> <mi>Z</mi> <mrow> <mo>(</mo> <msub> <mi>x</mi> <mi>i</mi> </msub> <mo>)</mo> </mrow> </mrow>
    λ in formulaiIt is weight coefficient, premised on Z (x) obeys intrinsic hypothesis, there is golden equation group in following gram：
    <mfenced open = "{" close = ""> <mtable> <mtr> <mtd> <mrow> <munderover> <mo>&amp;Sigma;</mo> <mrow> <mi>j</mi> <mo>=</mo> <mn>1</mn> </mrow> <mi>n</mi> </munderover> <msub> <mi>&amp;lambda;</mi> <mi>i</mi> </msub> <mi>&amp;gamma;</mi> <mrow> <mo>(</mo> <msub> <mi>x</mi> <mi>i</mi> </msub> <mo>,</mo> <msub> <mi>x</mi> <mi>j</mi> </msub> <mo>)</mo> </mrow> <mo>+</mo> <mi>&amp;mu;</mi> <mo>=</mo> <mi>&amp;gamma;</mi> <mrow> <mo>(</mo> <msub> <mi>x</mi> <mi>i</mi> </msub> <mo>,</mo> <msub> <mi>x</mi> <mn>0</mn> </msub> <mo>)</mo> </mrow> <mo>,</mo> <mrow> <mo>(</mo> <mi>i</mi> <mo>=</mo> <mn>1</mn> <mo>,</mo> <mn>2</mn> <mo>,</mo> <mn>...</mn> <mo>,</mo> <mi>n</mi> <mo>)</mo> </mrow> </mrow> </mtd> </mtr> <mtr> <mtd> <mrow> <munderover> <mo>&amp;Sigma;</mo> <mrow> <mi>i</mi> <mo>=</mo> <mn>1</mn> </mrow> <mi>n</mi> </munderover> <msub> <mi>&amp;lambda;</mi> <mi>i</mi> </msub> <mo>=</mo> <mn>1</mn> </mrow> </mtd> </mtr> </mtable> </mfenced>
    In formula, γ (xi, xj) it is sampled point xiAnd xjBetween variation function value, μ is Lagrangian constant.
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CN110097637A (en) * 2019-05-09 2019-08-06 正元地理信息集团股份有限公司 A kind of three-dimensional geological attribute model temporal-spatial interpolating method and system
CN113064129A (en) * 2021-03-03 2021-07-02 湖北中南鹏力海洋探测系统工程有限公司 High-frequency ground wave radar ocean current synthesis method
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CN110097637A (en) * 2019-05-09 2019-08-06 正元地理信息集团股份有限公司 A kind of three-dimensional geological attribute model temporal-spatial interpolating method and system
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CN116402953A (en) * 2023-04-26 2023-07-07 华中科技大学 Wave surface reconstruction method and device based on binocular data on floating platform
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