CN115792898A - Floating ice detection method based on X-band target monitoring radar - Google Patents
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Abstract
The invention discloses a floating ice detection method based on an X-band target monitoring radar, which mainly comprises the following steps: firstly, collecting original video data of a radar, and processing signals; setting relevant parameters of floating ice; carrying out amplitude correction on the echo; accumulating images, dividing the accumulated radar data into a plurality of small lattices, and calculating correlation coefficients among the small lattices; identifying an ice image, and when the correlation coefficient of the two small lattices is greater than a set threshold value, indicating that the two small lattices are the data of the same ice floe; and outputting floating ice parameters including floating ice area, position, maximum floating ice horizontal dimension and moving speed direction. The invention observes the floating ice based on the traditional X-waveband target monitoring radar and adopts the modes of echo amplitude correction and correlation coefficient calculation, thereby meeting the requirements of monitoring range and observation precision.
Description
Technical Field
The invention relates to the fields of marine environment, natural disasters, ship management and other industries, in particular to a floating ice detection method based on an X-band target monitoring radar.
Background
The thrust and impact force of sea ice during movement are huge, and the Tatannik passenger ship which happens in 4 months in 1912 impacts the iceberg to be out of top disasters, which is one of the biggest disasters caused by the sea ice in the century. In 1969 in Bohai sea extra-large ice sealing period in China, the flowing ice destroys a 'sea two-well' oil platform which is made of 15 manganese steel plates with the thickness of 2.2 centimeters, has the diameter of 0.85 meter and the length of 41 meters and is driven into a hollow cylinder pile column with the depth of 28 meters in the sea bottom and has a full steel structure, and a 'sea one-well' platform support lacing wire weighing 500 tons is cut off by the sea ice, so that how serious the damage force of the sea ice causes disasters to ships and ocean engineering buildings can be seen.
At present, the reduction of the thickness and the area of large-scale sea ice, especially arctic sea ice, promotes climate warming, enhances climate disasters (such as strong wind and flood) and causes adverse effects on human beings. Sea ice also has a positive effect on humans, affecting the temperature of the sea and the atmosphere, and affecting the circulation of the atmosphere and climate changes, which may also be beneficial to humans.
At present, there are 3 methods of "visual method", "instrumental method" and "telemetric method" for monitoring sea ice. The visual observation method is a basic observation method for traditional sea ice monitoring, and the method is based on the sea ice observation specification and observation by means of eyes and experience of observers, such as ice amount, flow ice concentration, flow ice shape, fixed ice shape and the like. The content observed by the visual method cannot be completely replaced by other visual methods at present, and the visual result is also the analysis basis of the observation result of the telemetry method, so the visual method continues to be used. However, visual observation has a limited range. The telemetry method mainly adopts a satellite mode to observe, and the observation scale is wide, but the accuracy is insufficient.
Disclosure of Invention
The invention aims to solve the technical problem of the prior art, and provides a floating ice detection method based on an X-band target monitoring radar.
In order to solve the technical problems, the technical scheme adopted by the invention is as follows:
a floating ice detection method based on an X-band target monitoring radar comprises the following steps.
Step 1, setting floating ice parameters: the ice floe parameters include an ice floe detection range, an image accumulation number n and a correlation coefficient threshold Corrcoef.
Step 2, collecting radar original data: the X-band target monitoring radar acquires radar original data of the ocean to be monitored once in each observation period; covering the floating ice detection range set in the step 1 by each radar original data; and acquiring n radar original data in n observation periods.
Step 3, signal processing: preprocessing each radar original data acquired in the step 1 to obtain a radar image which is located in a floating ice detection range and only contains a water surface target signal; and after the n radar original data are subjected to signal preprocessing, n radar images are obtained.
Step 4, radar echo amplitude correction: for the radar image processed in the step 3, distance compensation correction is carried out on the amplitude of each pixel point; after the distance compensation correction is carried out on the n radar images, the n radar images are respectively marked as Map according to the acquisition time sequence 1 、Map 2 、Map 3 823060 \ 8230and Map n 。
Step 5, image accumulation: map is to be 2 、Map 3 823060 \ 8230and Map n Weighting all pixel point amplitudes to obtain weighted corrected radar image Map 2-n 。
Step 6, calculating a correlation coefficient: map is to be 1 And Map 2-n All divided into k × k cells; computing Map 2-n Middle ith cell and Map 1 Correlation coefficient correction of pixel points in the ith cell id (ii) a Wherein; i is more than or equal to 1 and less than or equal to k.
Step 7, ice image identification: when in useCorrelation coefficient Correlation of two ith cells calculated in step 6 id When the correlation coefficient is larger than the correlation coefficient threshold Corrcoef set in the step 1, judging that the two ith cells are the same floating ice; and repeating the steps to finish the ice image recognition of the k × k cells.
Step 8, outputting floating ice information: connecting and condensing the small cells judged as the same floating ice in the step 7 to form a floating ice image, and outputting floating ice information of the floating ice image; the ice floe information includes an ice floe area.
In step 4, if the amplitude of any pixel point in each radar image after distance compensation correction is set to Amp _ Correct, the corresponding calculation formula is:
Amp_Correct＝AMP+Slope*log 10 (kDis/1000)+Lifting*a
wherein:
in the formula, AMP is the original amplitude of the pixel point to be corrected; slope is the set sea ice intensity correction Slope; kdsi is the distance between the pixel point to be corrected and the radar, and the unit is: m; lifting is corrected for the set sea ice strength by Lifting; the division is a set sea ice strength correction distance division point; a is a distance factor.
In step 5, map 2-n The calculation formula of (2) is as follows:
Map 2-n ＝(Map 2 +Map 3 +...+Map n )/(n-2)。
in step 6, map is set 1 And Map 2-n The pixel size of (1) is m, then the Correlation coefficient correction id The calculation formula of (c) is:
wherein:
in the formula, AVE X Is Map 1 And (4) averaging the corrected amplitudes of all the pixel points in the ith small cell.
lens is Map 1 Or Map 2-n And the number of pixel points in the ith cell.
AVE Y As Map 2-n And (5) averaging the corrected amplitudes of all the pixel points in the ith cell.
AVE XX Is Map 1 And (4) the mean square sum of the corrected amplitudes of all the pixel points in the ith cell.
AVE YY Is Map 2-n And (4) the mean square sum of the corrected amplitudes of all the pixel points in the ith cell.
AVE XY Is the mean square sum of Map1 and Map 2-n.
In step 7, correlation coefficient correction of the i-th cells calculated in step 6 is performed during ice image recognition id If the correlation coefficient is larger than the correlation coefficient threshold Corrcoef set in the step 1, judging that the two ith cells are the same floating ice, and marking the current ith cell as lattice id =1, otherwise, label id =0; and repeating the steps to finish the ice image recognition of the k × k cells.
In step 7, the correlation coefficient threshold Corrcoef is calculated by the following formula:
in the formula, ampPop and AmpLow are respectively a set upper limit and a set lower limit of the ice floation amplitude threshold value.
Valueset is an empirical constant value and is adjusted according to the rain and snow or sheltered environment of the scene.
In step 8, the method for calculating the floating ice area comprises the following steps:
step 8-1, condensation: all phases are identified by adopting an image edge identification function in Opencv id The cells of 1 are connected and coalesced to form a plurality of polygonal images.
Step 8-2, calculating longitude and latitude: and calculating the latitude and longitude of the edge point of each polygonal image.
Step 8-3, calculating the number of cells: calculating lattice contained in each polygonal image id The number of cells is 1.
8-4, drawing a minimum rectangle: and drawing a minimum rectangle at the periphery of each polygonal image.
8-5, calculating a rectangle parameter: the rectangle parameters include the longitude and latitude of the minimum rectangle center point, the length of the minimum rectangle long side, and lattice n ；lattice n Lattice contained within the smallest rectangle id The number of cells is 1.
And 8-6, calculating the area S of the single floating ice block, wherein the calculation formula is as follows:
s = area _ total · area represented by single pixel point
Wherein, area _ total is all the lattice in the minimum rectangle id The sum of pixel points of =1, the calculation formula is:
area_total＝lattice n *lengh。
in step 8, the floating ice information further comprises a floating ice position site and a floating ice maximum horizontal scale; wherein, the position of the floating ice is obtained through the longitude and latitude of the central point of the minimum rectangle in the step 8-5; the maximum horizontal dimension of the floating ice is the length of the long side of the minimum rectangle.
In step 8, the floating ice information further includes a floating ice moving speed V, and the calculation formula of the floating ice moving speed V is as follows:
V＝(site2-site1)/(T2-T1)
in the formula, site1 and site2 are positions of the ice floes at time T1 and time T2, respectively.
The invention has the following beneficial effects: the invention observes the floating ice based on the traditional X-waveband target monitoring radar and adopts the modes of echo amplitude correction and correlation coefficient calculation, thereby meeting the requirements of monitoring range and observation precision.
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FIG. 1 shows a flow chart of a floating ice detection method based on an X-band target surveillance radar of the present invention.
FIG. 2 is a schematic diagram of a setting interface of ice floe parameters in the present invention.
FIG. 3 shows a schematic diagram of the identification of ice floe profile in the present invention.
FIG. 4 is a schematic diagram showing the principle of calculation of the floating ice moving speed in the present invention.
Detailed Description
The present invention will be described in further detail with reference to the drawings and specific preferred embodiments.
In the description of the present invention, it is to be understood that the terms "left side", "right side", "upper part", "lower part", etc., indicate orientations or positional relationships based on those shown in the drawings, and are only for convenience of describing the present invention and simplifying the description, but do not indicate or imply that the referred device or element must have a specific orientation, be constructed in a specific orientation, and be operated, and that "first", "second", etc., do not represent an important degree of the component parts, and thus are not to be construed as limiting the present invention. The specific dimensions used in the present example are only for illustrating the technical solution and do not limit the scope of protection of the present invention.
As shown in FIG. 1, the floating ice detection method based on the X-band target monitoring radar comprises the following steps.
Step 1, setting floating ice parameters
The floating ice parameters comprise a floating ice detection range, an image accumulation frequency n, a correlation coefficient threshold Corrcoef, a floating ice amplitude threshold upper limit AmpTop, a floating ice amplitude threshold lower limit AmpLow, a contour range, a sea ice intensity correction Slope, a sea ice intensity correction Lifting and lowering Lifting, a sea ice intensity correction long-distance and short-distance division point DisDivision and the like.
The floating ice detection range comprises an azimuth start and a distance start from the radar; in this embodiment, as shown in FIG. 2, the azimuth starts at 220 ° and ends at 15 °; the distance starts at 0Nm and ends at 5.5Nm.
The number of image accumulations n, i.e., inter-field accumulation in fig. 2, is preferably n =32.
As shown in fig. 2, the value range of the correlation coefficient threshold Corrcoef is preferably 80 to 100%, and in this embodiment, the value range of the correlation coefficient threshold Corrcoef is preferably 81.
The upper limit AmpTop of the ice floe amplitude threshold value is preferably 80-90dB, and is preferably 83dB in the embodiment, as shown in fig. 2.
The value range of the lower limit AmpLow of the ice floation amplitude threshold is, as shown in fig. 2, preferably 30-40dB, and in this embodiment, preferably 40dB.
The value range of the above-mentioned contour range, that is, the minimum number of contour points that can be identified, as shown in fig. 2, is preferably 0-200, and in this embodiment, is preferably 74.
The sea ice intensity correction can solve the problem of unmatched far and near intensities caused by the attenuation of the sea ice distance; the sea ice intensity correction Slope is the Slope of the original data relative to the corrected data, and is a uniform set value. In the present embodiment, slope =20 is preferable.
The sea ice intensity correction Lifting is the Lifting of the corrected curve relative to a zero point; the zero-point coordinate axis y =0 is a uniform set value. In the present embodiment, lifting = -12 is preferable.
In the present embodiment, the sea ice strength correction remote and near division point is preferably set to a value of dispision =8000m.
Step 2, collecting radar original data: the X-band target monitoring radar acquires radar original data of the ocean to be monitored once in each observation period; covering the floating ice detection range set in the step 1 by each radar original data; and acquiring n radar original data in n observation periods. In the present embodiment, each observation period, i.e., the timing observation time as shown in fig. 2, is preferably 10 minutes.
Step 3, signal processing: and (2) preprocessing each radar original data acquired in the step (1), removing ground objects, noise, interference and the like to obtain a radar image which is positioned in the floating ice detection range and only contains a water surface target signal. And after the n radar original data are subjected to signal preprocessing, n radar images are obtained.
Step 4, radar echo amplitude correction
The ice echo amplitude measured by the wave radar can be gradually attenuated along with the distance change, so that the ice echo amplitude at the near part of the radar is very strong, the ice echo amplitude at the far part is very weak, the characteristics of an ice image cannot be effectively reflected, and the ice echo intensity needs to be subjected to distance compensation correction.
For the radar image processed in the step 3, distance compensation correction is carried out on the amplitude of each pixel point; after the distance compensation correction, the n radar images are respectively marked as Map according to the acquisition time sequence 1 、Map 2 、Map 3 823060 \ 8230and Map n 。
If the amplitude of any pixel point in each radar image after distance compensation correction is set as Amp _ Correct, the corresponding calculation formula is as follows:
Amp_Correct＝AMP+Slope*log 10 (kDis/1000)+Lifting*a
wherein:
in the formula, AMP is the original amplitude of the pixel point to be corrected; SLope is the set sea ice intensity correction SLope; kdiss is the distance between the pixel point to be corrected and the radar, unit: m; lifting is corrected for the set sea ice strength by Lifting; disdivision corrects a far and near distance division point for the set sea ice strength; a is a distance factor.
And step 5, image accumulation: map is obtained 2 、Map 3 823060 \ 8230and Map n Weighting all pixel point amplitudes to obtain weighted corrected radar image Map 2-n The calculation formula is as follows:
Map 2-n ＝(Map 2 +Map 3 +...+Map n )/(n-2)。
step 6, calculating a correlation coefficient: map is to be 1 And Map 2-n All divided into k × k cells; computing Map 2-n Middle ith cell and Map 1 Correlation coefficient correction of pixel points in the ith cell id (ii) a Wherein; i is more than or equal to 1 and less than or equal to k.
Let Map 1 And Map 2-n All the pixel sizes of (1) are m x m, then Correlation coefficient Correlation id The calculation formula of (2) is as follows:
wherein:
in the formula, AVE X As Map 1 And (5) averaging the corrected amplitudes of all the pixel points in the ith cell.
lens is Map 1 Or Map 2-n And the number of pixel points in the ith cell.
AVE Y Is Map 2-n And (5) averaging the corrected amplitudes of all the pixel points in the ith cell.
AVE XX Is Map 1 And (4) the mean square sum of the corrected amplitudes of all the pixel points in the ith cell.
AVE YY Is Map 2-n And (4) the mean square sum of the corrected amplitudes of all the pixel points in the ith cell.
AVE XY Is the mean square sum of Map1 and Map 2-n.
Step 7, ice image identification: correlation coefficient Correlation of the two ith cells calculated in step 6 id When the correlation coefficient is larger than the correlation coefficient threshold Corrcoef set in the step 1, judging that the two ith cells are the same floating ice; and repeating the steps to finish the ice image recognition of the k × k cells.
In the ice image recognition, the Correlation coefficient correction of the two i-th cells calculated in step 6 id If the correlation coefficient is larger than the correlation coefficient threshold Corrcoef set in the step 1, judging that the two ith small grids are the same floating ice block, and marking the current ith small grid as lattice id =1, otherwise, label latice id =0; and repeating the steps to finish the ice image recognition of the k × k cells.
In step 7, the correlation coefficient threshold Corrcoef is calculated by the following formula:
in the formula, amptop and AmpLow are respectively a set upper limit and a set lower limit of the ice floe amplitude threshold.
Valueset is an empirical constant value and is adjusted according to the rain and snow or sheltered environment of the scene.
Due to the AVE in each cell X And AVE Y Differently, each cell thus corresponds to a correlation coefficient threshold.
Step 8, outputting floating ice information: and (4) communicating and condensing the cells judged as the same floating ice in the step (7) to form a floating ice image, and outputting floating ice information of the floating ice image. The floating ice information comprises a floating ice area, a floating ice position site, a floating ice maximum horizontal dimension, a floating ice moving speed V, a floating ice moving direction and the like.
The method for calculating the ice floe area, as shown in fig. 3, preferably includes the following steps:
step 8-1, condensation: all lattices are subjected to image edge recognition function in Opencv id The cells of 1 are connected and coalesced to form a plurality of polygonal images.
Step 8-2, calculating longitude and latitude: and calculating the latitude and longitude of the edge point of each polygonal image.
Step 8-3, calculating the number of the small lattices: calculating lattice contained in each polygonal image id The number of cells is 1.
8-4, drawing a minimum rectangle: a minimum rectangle is drawn around the periphery of each polygon image. Each minimum rectangle corresponds to a floating ice.
8-5, calculating a rectangle parameter: the rectangle parameters include the longitude and latitude of the minimum rectangle center point, the length of the minimum rectangle long side, and lattice n ；lattice n Lattice contained within the smallest rectangle id The number of cells is 1.
And 8-6, calculating the area S of the single floating ice block, wherein the calculation formula is as follows:
s = area _ total area represented by a single pixel
Wherein, area _ total is all the lattice in the minimum rectangle id The sum of pixel points of =1, the calculation formula is:
area_total＝lattice n *lengh
the floating ice position site is preferably obtained through the longitude and latitude of the central point of the minimum rectangle in the step 8-5; the maximum horizontal dimension of the floating ice is the length of the long side of the minimum rectangle.
As shown in fig. 4, the formula for calculating the moving speed V of the floating ice (i.e., floating ice No. 1) is preferably:
V＝(site2-site1)/(T2-T1)
in the formula, site1 and site2 are positions of the ice floes at time T1 and time T2, respectively.
The movement is in the direction indicated by the two-point connecting line of site1 to site 2.
Although the preferred embodiments of the present invention have been described in detail, the present invention is not limited to the details of the embodiments, and various equivalent modifications can be made within the technical spirit of the present invention, and the scope of the present invention is also within the scope of the present invention.
Claims (9)
1. A floating ice detection method based on an X-band target monitoring radar is characterized by comprising the following steps: the method comprises the following steps:
step 1, setting floating ice parameters: the floating ice parameters comprise a floating ice detection range, an image accumulation frequency n and a correlation coefficient threshold Corrcoef;
step 2, collecting radar original data: the X-band target monitoring radar acquires radar original data of the ocean to be monitored once in each observation period; covering the floating ice detection range set in the step 1 by each radar original data; acquiring n radar original data in n observation periods;
step 3, signal processing: preprocessing each radar original data acquired in the step 1 to obtain a radar image which is located in a floating ice detection range and only contains a water surface target signal; after the n radar original data are subjected to signal preprocessing, n radar images are obtained;
step 4, radar echo amplitude correction: for the radar image processed in the step 3, the breadth of each pixel point is obtainedDistance compensation correction is carried out on the distance values; after the distance compensation correction, the n radar images are respectively marked as Map according to the acquisition time sequence 1 、Map 2 、Map 3 823060 \ 8230and Map n ；
And step 5, image accumulation: map is to be 2 、Map 3 823060 \ 8230and Map n Weighting all pixel point amplitudes to obtain weighted corrected radar image Map 2-n ；
Step 6, calculating a correlation coefficient: map is to be 1 And Map 2-n All divided into k × k cells; computing Map 2-n Middle ith cell and Map 1 Correlation coefficient correction of pixel points in the ith cell id (ii) a Wherein; i is more than or equal to 1 and less than or equal to k;
step 7, ice image identification: correlation coefficient Correlation of the two ith cells calculated in step 6 id When the correlation coefficient is larger than the correlation coefficient threshold Corrcoef set in the step 1, judging that the two ith cells are the same floating ice; repeating the steps in sequence to finish the ice image recognition of k-by-k cells;
step 8, outputting floating ice information: connecting and condensing the small cells of the same floating ice judged in the step 7 to form a floating ice image, and outputting floating ice information of the floating ice image; the ice floe information includes an ice floe area.
2. The floating ice detection method based on the X-band target surveillance radar according to claim 1, wherein: in step 4, if the amplitude of any pixel point in each radar image after distance compensation correction is set to Amp _ Correct, the corresponding calculation formula is as follows: amp _ Correct = Amp + Slope log 10 (kDis/1000)+Lifting*a
Wherein:
in the formula, AMP is the original amplitude of the pixel point to be corrected; slope is the correction Slope of the set sea ice intensity; kdsi is the distance between the pixel point to be corrected and the radar, and the unit is: m; lifting is corrected for the set sea ice intensity by Lifting; disdivision corrects a far and near distance division point for the set sea ice strength; a is a distance factor.
3. The floating ice detection method based on the X-band target surveillance radar according to claim 1, wherein: in step 5, map 2-n The calculation formula of (2) is as follows:
Map 2-n ＝(Map 2 +Map 3 +…+Map n )/(n-2)。
4. the floating ice detection method based on the X-band target surveillance radar according to claim 1, wherein: in step 6, map is set 1 And Map 2-n All the pixel sizes of (1) are m x m, then Correlation coefficient Correlation id The calculation formula of (2) is as follows:
wherein:
in the formula, AVE X Is Map 1 The mean value of the corrected amplitudes of all the pixel points in the ith cell;
AVE Y as Map 2-n The mean value of the corrected amplitudes of all the pixel points in the ith cell;
AVE XX as Map 1 The mean square sum of the corrected amplitudes of all the pixel points in the ith cell;
AVE YY is Map 2-n The mean square sum of the corrected amplitudes of all the pixel points in the ith cell;
AVE XY is the mean square sum of Map1 and Map 2-n.
5. The floating ice detection method based on the X-band target surveillance radar according to claim 4, wherein: in step 7, when the ice image is identified, the two ith cells calculated in step 6 areCorrelation coefficient Correlation id If the correlation coefficient is larger than the correlation coefficient threshold Corrcoef set in the step 1, judging that the two ith cells are the same floating ice, and marking the current ith cell as lattice id =1, otherwise, label id =0; and repeating the steps to finish the ice image recognition of the k × k cells.
6. The method for detecting floating ice based on X-band target surveillance radar according to claim 1 or 5, wherein: in step 7, the correlation coefficient threshold Corrcoef is calculated by the following formula:
in the formula, ampPop and AmpLow are respectively a set upper limit and a set lower limit of an ice floation amplitude threshold;
valueset is an empirical constant value and is adjusted according to the rain and snow or sheltered environment of the scene.
7. The floating ice detection method based on the X-band target surveillance radar according to claim 5, wherein: in step 8, the method for calculating the floating ice area comprises the following steps:
step 8-1, condensation: all phases are identified by adopting an image edge identification function in Opencv id The cells of 1 are communicated and condensed to form a plurality of polygonal images;
step 8-2, calculating longitude and latitude: calculating the latitude and longitude of the edge point of each polygonal image;
step 8-3, calculating the number of the small lattices: calculating lattice contained in each polygonal image id The number of cells is 1;
8-4, drawing a minimum rectangle: drawing a minimum rectangle at the periphery of each polygonal image;
8-5, calculating a rectangle parameter: the rectangle parameters include longitude and latitude of the central point of the minimum rectangle, the length of the long side of the minimum rectangle, and lattice n ；lattice n To a minimumLattice contained within a rectangle id The number of cells is 1;
and 8-6, calculating the area S of the single floating ice block, wherein the calculation formula is as follows:
s = area _ total area represented by a single pixel
Wherein, area _ total is all lattice in the minimum rectangle id The sum of pixel points of =1, the calculation formula is:
area_total＝lattice n *lengh。
8. the method of claim 7, wherein the method comprises: in step 8, the floating ice information further comprises a floating ice position site and a floating ice maximum horizontal scale; wherein, the position of the floating ice is obtained through the longitude and latitude of the central point of the minimum rectangle in the step 8-5; the maximum horizontal dimension of the floating ice is the length of the long side of the minimum rectangle.
9. The floating ice detection method based on the X-band target surveillance radar according to claim 8, wherein: in step 8, the floating ice information further includes a floating ice moving speed V, and the calculation formula of the floating ice moving speed V is:
V＝(site2-site1)/(T2-T1)
in the formula, site1 and site2 are positions of the ice floes at time T1 and time T2, respectively.
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