CN115792898B - Floating ice detection method based on X-band target monitoring radar - Google Patents
Floating ice detection method based on X-band target monitoring radar Download PDFInfo
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Abstract
The invention discloses an ice float detection method based on an X-band target monitoring radar, which mainly comprises the following steps: firstly, collecting radar original video data, and performing signal processing; setting relevant parameters of floating ice; performing 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; the ice image identification, when the correlation coefficient of the two small lattices is larger than the set threshold value, the data of the same block of floating ice of the two small lattices are described; and outputting floating ice parameters, including floating ice area, position, floating ice maximum horizontal scale and moving speed. The invention observes the floating ice based on the traditional X-band target surveillance radar and adopts the mode of echo amplitude correction and correlation coefficient calculation, thereby meeting the requirements of the monitoring range and the requirement of the observation precision.
Description
Technical Field
The invention relates to the fields of marine environment, natural disasters, ship management and the like, 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 are huge, and the Tatank number passenger wheel in 1912 and 4 months impacts the iceberg and is subjected to top-extinguishing disaster, so that the Tatank number passenger wheel is one of the biggest disasters caused by the sea ice in this century. In 1969, during the extra-large ice sealing period of Bohai sea, the ice flow destroys a 'sea two-well' oil platform which is made of 15 2.2 cm thick manganese steel plates, has a hollow cylindrical pile full-steel structure with the diameter of 0.85 m and the length of 41 m and is driven into the sea floor to be 28 m deep, and the other 500 tons of 'sea one-well' platform support tie bars are all cut off by sea ice, so that the damage force of the sea ice can be seen to how serious the disasters brought by ships and ocean engineering buildings are.
The reduction of the thickness and the area of the sea ice in a large range at present, particularly the North sea ice, promotes the warming of the climate, enhances the climate disasters (such as strong wind and flood), and has adverse effects on human beings. Sea ice also has a positive effect on humans, it affects sea and atmospheric temperatures, and affects atmospheric flows and climate changes, which may also be beneficial to humans.
Currently, there are 3 methods of "visual method", "mechanical method" and "telemetry method" for sea ice monitoring. The visual observation method is a basic observation method for monitoring the traditional sea ice, and the method is based on eye and experience of an observer according to the regulation of sea ice observation standards, such as ice quantity, ice flow density, ice flow shape, fixed ice shape and the like. The visual observation method cannot be completely replaced by other visual observation methods at present, and the visual observation result is also the analysis basis of the telemetry observation result, so the visual observation method is continued. However, visual inspection is limited in scope. The telemetry method mainly adopts a satellite mode for observation, and has wide observation scale but insufficient precision.
Disclosure of Invention
The invention aims to solve the technical problems 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 invention adopts the following technical scheme:
an ice floc detection method based on an X-band target monitoring radar comprises the following steps.
Step 1, setting floating ice parameters: the floating ice parameters include a floating ice detection range, the number of image accumulation times n, and a correlation coefficient threshold Corrcoef.
Step 2, acquiring radar original data: the X-band target monitoring radar collects radar raw data of the ocean to be monitored once in each observation period; each radar original data needs to cover the floating ice detection range set in the step 1; and acquiring n radar original data in n observation periods.
Step 3, signal processing: preprocessing each radar raw data acquired in the step 1 to obtain a radar image which is positioned in the detection range of the floating ice and only contains a water surface target signal; after the signal preprocessing is carried out on the n radar original data, n radar images are obtained.
Step 4, radar echo amplitude correction: carrying out distance compensation correction on the amplitude of each pixel point on the radar image processed in the step 3; after the distance compensation correction, the n radar images are respectively marked as maps according to the acquisition time sequence 1 、Map 2 、Map 3 … … and Map n 。
Step 5, image accumulation: map (Map) 2 、Map 3 … … and Map n Weighting all pixel amplitudes to obtain a weighted corrected radar image Map 2-n 。
Step 6, calculating a correlation coefficient: map (Map) 1 And Map 2-n All divided into k x k cells; calculating Map 2-n The ith cell and Map of (a) 1 Correlation coefficient corelation of pixel points in ith cell of the medium id The method comprises the steps of carrying out a first treatment on the surface of the Wherein; 1.ltoreq.i.ltoreq.k.times.k.
Step 7, ice image identification: when the Correlation coefficient corelation of the two ith cells calculated in the step 6 id When the correlation coefficient threshold value Corrcoef set in the step 1 is larger than the correlation coefficient threshold value Corrcoef, judging that the two ith cells are the same floating ice; and by analogy, the ice image identification of k x k cells is completed.
Step 8, outputting floating ice information: communicating and agglomerating the cells judged to be 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 includes a floating ice area.
In step 4, the amplitude of any pixel point in each radar image after the distance compensation correction is set as amp_correct, and the corresponding calculation formula is as follows:
Amp_Correct＝AMP+Slope*log 10 (kDis/1000)+Lifting*a
wherein:
wherein AMP is the original amplitude of the pixel point to be corrected; slope is the set sea ice intensity correction Slope; kDIs is the distance between the pixel to be corrected and the radar, and the unit is: m; the limiting is the set sea ice strength correction Lifting; disdivision is used for correcting the distance division points for the set sea ice intensity; 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 sizes of (a) are m x m, and the Correlation coefficient is Correlating id The calculation formula of (2) is as follows:
wherein:
in AVE of X Is Map 1 The average value of the corrected amplitude of all pixel points in the ith cell.
X 1 、X 2 、...、Map respectively 1 1 st, 2 nd and +.>Corrected magnitudes for individual pixels.
lengh is Map 1 Or Map 2-n The number of pixel points in the ith cell.
AVE Y Is Map 2-n The average value of the corrected amplitude of all pixel points in the ith cell.
Y 1 、Y 2 、...、Map respectively 2-n 1 st, 2 nd and +.>Corrected magnitudes for individual pixels.
AVE XX Is Map 1 The mean square sum of the corrected amplitudes of all pixel points in the ith cell.
AVE YY Is Map 2-n The mean square sum of the corrected amplitudes of all pixel points in the ith cell.
AVE XY Is the mean square sum of Map1 and Map 2-n.
In step 7, when the ice image is recognized, two calculated in step 6Correlation coefficient corelation of ith cell id When the correlation coefficient threshold value Corrcoef set in the step 1 is larger than the correlation coefficient threshold value Corrcoef, judging that the two ith cells are the same piece of floating ice, and marking the current ith cell as a lattice id =1, otherwise, marked as lattice id =0; and by analogy, the ice image identification of k x k cells is completed.
In step 7, the calculation formula of the correlation coefficient threshold Corrcoef is:
wherein, ampTop and AmpLow are respectively the upper limit of the set ice-floating amplitude threshold and the lower limit of the set ice-floating amplitude threshold.
ValueSet is an empirical constant value and is adjusted according to the rain and snow or shielding environment of the scene.
In step 8, the method for calculating the floating ice area comprises the following steps:
step 8-1, condensation: adopting an image edge recognition function in Opencv to perform all the labyrinths id The cells 1 are connected and aggregated to form a plurality of polygon images.
Step 8-2, calculating longitude and latitude: and calculating the longitude and latitude of the edge point of each polygon image.
Step 8-3, calculating the number of the cells: calculating the lattice contained in each polygon image id A number of cells of 1.
Step 8-4, drawing a minimum rectangle: a minimum rectangle is drawn around the periphery of each polygon image.
Step 8-5, calculating rectangular parameters: the rectangle parameters comprise longitude and latitude of the center point of the minimum rectangle, length of the long side of the minimum rectangle and lattice n ；lattice n Is the lattice contained within the smallest rectangle id A number of cells of 1.
Step 8-6, calculating the area S of the single floating ice, wherein the calculation formula is as follows:
s=area_total =area represented by a single pixel point
Wherein, area_totall is all tiles within the smallest rectangle id The sum of pixel points=1, the calculation formula is:
area_total＝lattice n *lengh。
in the step 8, the floating ice information also comprises a floating ice position site and a floating ice maximum horizontal scale; the floating ice position site is obtained through the longitude and latitude of the smallest rectangular center point in the step 8-5; the largest horizontal dimension of the floating ice is the side length of the long side of the smallest rectangle.
In step 8, the floating ice information further includes a floating ice moving speed V, and a calculation formula of the floating ice moving speed V is:
V＝(site2-site1)/(T2-T1)
where site1 and site2 are the positions of the ice floe at times T1 and T2, respectively.
The invention has the following beneficial effects: the invention observes the floating ice based on the traditional X-band target surveillance radar and adopts the mode of echo amplitude correction and correlation coefficient calculation, thereby meeting the requirements of the monitoring range and the requirement of the observation precision.
Drawings
FIG. 1 shows a flow chart of an ice flossing detection method based on an X-band target surveillance radar of the present invention.
FIG. 2 shows a schematic diagram of a configuration interface for floating ice parameters according to the present invention.
FIG. 3 shows a schematic diagram of ice floe profile recognition in the present invention.
Fig. 4 shows a schematic diagram of the calculation principle of the floating ice moving speed in the invention.
Detailed Description
The invention will be described in further detail with reference to the accompanying drawings and specific preferred embodiments.
In the description of the present invention, it should be understood that the terms "left", "right", "upper", "lower", etc. indicate orientations or positional relationships based on the orientations or positional relationships shown in the drawings, are merely for convenience in describing the present invention and simplifying the description, and do not indicate or imply that the apparatus or element being referred to must have a specific orientation, be configured and operated in a specific orientation, and "first", "second", etc. do not indicate the importance of the components, and thus are not to be construed as limiting the present invention. The specific dimensions adopted in the present embodiment are only for illustrating the technical solution, and do not limit the protection scope of the present invention.
As shown in FIG. 1, the method for detecting the floating ice 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 value Corrcoef, a floating ice amplitude threshold value upper limit Amptop, a floating ice amplitude threshold value lower limit AmpLow, a contour range, a sea ice intensity correction Slope, sea ice intensity correction Lifting Listing, sea ice intensity correction long-distance and short-distance division points Disdivision and the like.
The floating ice detection range comprises azimuth start and distance start from the radar; in this embodiment, as shown in FIG. 2, the azimuth starts 220 and the azimuth ends 15; the distance was initially 0Nm and the distance was terminated at 5.5Nm.
The number of image accumulation times n, that is, the inter-field accumulation in fig. 2, is preferably n=32.
The value range of the correlation coefficient threshold Corrcoef is preferably 80-100%, as shown in fig. 2, and in this embodiment, 81 is preferable.
The upper limit AmpTop of the ice floc amplitude threshold is preferably 80-90dB, as shown in fig. 2, and in this embodiment, 83dB is preferable.
The value range of the ice floe amplitude threshold lower limit AmpLow is preferably 30-40dB, as shown in fig. 2, and in this embodiment, is preferably 40dB.
The number of the contour ranges, that is, the minimum number of contour points that can be identified, is preferably 0 to 200, as shown in fig. 2, and in this embodiment, 74.
The sea ice strength correction can solve the problem of mismatching of far and near strengths caused by sea ice distance attenuation; the sea ice strength correction Slope is the Slope of the original data relative to the corrected data, and is a uniform set value. In this embodiment, slope=20 is preferable.
The sea ice strength correction Lifting and lowering limiting is Lifting and lowering of the corrected curve relative to the zero point; the zero-point coordinate axis y=0 is a uniform set value. In this embodiment, the preferred is Lifting= -12.
In the present embodiment, the sea ice intensity correction long-distance and short-distance division point preference value is distivision=8000 m.
Step 2, acquiring radar original data: the X-band target monitoring radar collects radar raw data of the ocean to be monitored once in each observation period; each radar original data needs to cover the floating ice detection range set in the step 1; and acquiring n radar original data in n observation periods. In the present embodiment, each observation period, that is, the time of observation at timing as shown in fig. 2, is preferably 10 minutes.
Step 3, signal processing: and (3) preprocessing each radar original data acquired in the step (1), removing ground objects, removing noise, resisting 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. After the signal preprocessing is carried out on the n radar original data, n radar images are obtained.
Step 4, radar echo amplitude correction
The amplitude of the ice echo measured by the wave radar gradually attenuates along with the distance, so that the phenomenon displayed on the radar echo is that the amplitude of the ice echo near the radar is particularly strong, the amplitude of the ice echo near the radar is particularly weak, the characteristic of an ice image cannot be effectively reflected, and therefore, the intensity of the ice echo needs to be subjected to distance compensation correction.
Carrying out distance compensation correction on the amplitude of each pixel point on the radar image processed in the step 3; after the distance compensation correction, the n radar images are respectively marked as maps according to the acquisition time sequence 1 、Map 2 、Map 3 … … and Map n 。
Let the amplitude of any pixel point in each radar image after the distance compensation correction be amp_correct, the corresponding calculation formula is:
Amp_Correct＝AMP+Slope*log 10 (kDis/1000)+Lifting*a
wherein:
wherein AMP is the original amplitude of the pixel point to be corrected; slope is the set sea ice intensity correction Slope; kDIs is the distance between the pixel to be corrected and the radar, and the unit is: m; the limiting is the set sea ice strength correction Lifting; disdivision is used for correcting the distance division points for the set sea ice intensity; a is a distance factor.
Step 5, image accumulation: map (Map) 2 、Map 3 … … and Map n Weighting all pixel amplitudes to obtain a 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 (Map) 1 And Map 2-n All divided into k x k cells; calculating Map 2-n The ith cell and Map of (a) 1 Correlation coefficient corelation of pixel points in ith cell of the medium id The method comprises the steps of carrying out a first treatment on the surface of the Wherein; 1.ltoreq.i.ltoreq.k.times.k.
Map is set up 1 And Map 2-n The pixel sizes of (a) are m x m, and the Correlation coefficient is Correlating id The calculation formula of (2) is as follows:
wherein:
in AVE of X Is Map 1 The average value of the corrected amplitude of all pixel points in the ith cell.
X 1 、X 2 、...、Map respectively 1 1 st, 2 nd and +.>Corrected magnitudes for individual pixels.
lengh is Map 1 Or Map 2-n The number of pixel points in the ith cell.
AVE Y Is Map 2-n The average value of the corrected amplitude of all pixel points in the ith cell.
Y 1 、Y 2 、...、Map respectively 2-n 1 st, 2 nd and +.>Corrected magnitudes for individual pixels.
AVE XX Is Map 1 The mean square sum of the corrected amplitudes of all pixel points in the ith cell.
AVE YY Is Map 2-n The mean square sum of the corrected amplitudes of all pixel points in the ith cell.
AVE XY Is the mean square sum of Map1 and Map 2-n.
Step 7, ice image identification: when the Correlation coefficient corelation of the two ith cells calculated in the step 6 id When the correlation coefficient threshold value Corrcoef set in the step 1 is larger than the correlation coefficient threshold value Corrcoef, judging that the two ith cells are the same floating ice; and by analogy, the ice image identification of k x k cells is completed.
When the ice image is identified, the Correlation coefficient corelation of the two ith cells calculated in the step 6 id When the correlation coefficient threshold value Corrcoef set in the step 1 is larger than the correlation coefficient threshold value Corrcoef, judging that the two ith cells are the same piece of floating ice, and marking the current ith cell as a lattice id =1, otherwise, marked as lattice id =0; and by analogy, the ice image identification of k x k cells is completed.
In step 7, the calculation formula of the correlation coefficient threshold Corrcoef is:
wherein, ampTop and AmpLow are respectively the upper limit of the set ice-floating amplitude threshold and the lower limit of the set ice-floating amplitude threshold.
ValueSet is an empirical constant value and is adjusted according to the rain and snow or shielding environment of the scene.
Due to the AVE in each cell X And AVE Y Different, each bin thus corresponds to a correlation coefficient threshold.
Step 8, outputting floating ice information: and (3) communicating and agglomerating the cells judged to be 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 scale, a floating ice moving speed V, a floating ice moving direction and the like.
The above-mentioned method for calculating the ice floe area preferably includes the following steps, as shown in fig. 3:
step 8-1, condensation: adopting an image edge recognition function in Opencv to perform all the labyrinths id The cells 1 are connected and aggregated to form a plurality of polygon images.
Step 8-2, calculating longitude and latitude: and calculating the longitude and latitude of the edge point of each polygon image.
Step 8-3, calculating the number of the cells: calculating the lattice contained in each polygon image id A number of cells of 1.
Step 8-4, drawing a minimum rectangle: a minimum rectangle is drawn around the periphery of each polygon image. Each smallest rectangle corresponds to a block of ice floe.
Step 8-5, calculating rectangular parameters: the rectangle parameters comprise longitude and latitude of the center point of the minimum rectangle, length of the long side of the minimum rectangle and lattice n ；lattice n Is the lattice contained within the smallest rectangle id A number of cells of 1.
Step 8-6, calculating the area S of the single floating ice, wherein the calculation formula is as follows:
s=area_total =area represented by a single pixel point
Wherein, area_total is all the tiles within the minimum rectangle id The sum of pixel points=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 smallest rectangular center point in the step 8-5; the largest horizontal dimension of the floating ice is the side length of the long side of the smallest rectangle.
As shown in fig. 4, the calculation formula of the moving speed V of the above-mentioned floating ice (i.e. floating ice No. 1) is preferably:
V＝(site2-site1)/(T2-T1)
where site1 and site2 are the positions of the ice floe at times T1 and T2, respectively.
The above-mentioned movement is the direction pointed by the connection line of two points from site1 to site 2.
The preferred embodiments of the present invention have been described in detail above, but the present invention is not limited to the specific details of the above embodiments, and various equivalent changes can be made to the technical solution of the present invention within the scope of the technical concept of the present invention, and all the equivalent changes belong to the protection scope of the present invention.
Claims (8)
1. An ice floc detection method based on an X-band target monitoring radar is characterized by comprising the following steps of: 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 number n and a correlation coefficient threshold value Corrcoef;
step 2, acquiring radar original data: the X-band target monitoring radar collects radar raw data of the ocean to be monitored once in each observation period; each radar original data needs to cover the floating ice detection range set in the step 1; acquiring n radar original data in n observation periods;
step 3, signal processing: preprocessing each radar original data acquired in the step 2 to obtain a radar image which is positioned in the detection range of the floating ice and only contains a water surface target signal; after preprocessing the signals, n radar original data obtain n radar images;
step 4, radar echo amplitude correction: carrying out distance compensation correction on the amplitude of each pixel point on the radar image processed in the step 3; let the amplitude of any pixel point in each radar image after the distance compensation correction be amp_correct, the corresponding calculation formula is:
Amp_Correct＝AMP+Slope*log 10 (kDis/1000)+Lifting*a
wherein:
wherein AMP is the original amplitude of the pixel point to be corrected; slope is the set sea ice intensity correction Slope; kDIs is the distance between the pixel to be corrected and the radar, and the unit is: m; the limiting is the set sea ice strength correction Lifting; disdivision is used for correcting the distance division points for the set sea ice intensity; a is a distance factor;
distance compensation repair of n radar imagesAfter that, according to the acquisition time sequence, respectively marking as maps 1 、Map 2 、Map 3 … … and Map n ；
Step 5, image accumulation: map (Map) 2 、Map 3 … … and Map n Weighting all pixel amplitudes to obtain a weighted corrected radar image Map 2-n ；
Step 6, calculating a correlation coefficient: map (Map) 1 And Map 2-n All divided into k x k cells; calculating Map 2-n The ith cell and Map of (a) 1 Correlation coefficient corelation of pixel points in ith cell of the medium id The method comprises the steps of carrying out a first treatment on the surface of the Wherein; 1.ltoreq.i.ltoreq.k.times.k;
step 7, ice image identification: when the Correlation coefficient corelation of the two ith cells calculated in the step 6 id When the correlation coefficient threshold value Corrcoef set in the step 1 is larger than the correlation coefficient threshold value Corrcoef, judging that the two ith cells are the same floating ice; and so on, completing the ice image identification of k x k cells;
step 8, outputting floating ice information: communicating and agglomerating the cells judged to be 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 includes a floating ice area.
2. The method for detecting floating ice 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)。
3. the method for detecting floating ice based on the X-band target surveillance radar according to claim 1, wherein: in step 6, map is set 1 And Map 2-n The pixel sizes of (a) are m x m, and the Correlation coefficient is Correlating id The calculation formula of (2) is as follows:
wherein:
in AVE of X Is Map 1 The average value of the corrected amplitude of all pixel points in the ith cell;
map respectively 1 1 st, 2 nd and +.>After correction of each pixel pointAmplitude; lengh is Map 1 Or Map 2-n The number of pixel points in the ith cell;
AVE Y is Map 2-n The average value of the corrected amplitude of all pixel points in the ith cell;
Y 1 、Y 2 、...、map respectively 2-n 1 st, 2 nd and +.>Corrected magnitudes for individual pixels;
AVE XX is Map 1 The mean square sum of the corrected amplitude of all pixel points in the ith cell;
AVE YY is Map 2-n The mean square sum of the corrected amplitude of all pixel points in the ith cell;
AVE XY is Map 1 And Map 2-n Is the mean square sum of (c).
4. The method for detecting floating ice based on the X-band target surveillance radar according to claim 3, wherein: in step 7, when the ice image is identified, the Correlation coefficient corelation of the two ith cells calculated in step 6 id When the correlation coefficient threshold value Corrcoef set in the step 1 is larger than the correlation coefficient threshold value Corrcoef, judging that the two ith cells are the same piece of floating ice, and marking the current ith cell as a lattice id =1, otherwise, marked as lattice id =0; and by analogy, the ice image identification of k x k cells is completed.
5. The method for detecting floating ice based on the X-band target surveillance radar according to claim 4, wherein: in step 7, the calculation formula of the correlation coefficient threshold Corrcoef is:
wherein, amptop and AmpLow are respectively the upper limit of the set ice-floating amplitude threshold and the lower limit of the set ice-floating amplitude threshold;
ValueSet is an empirical constant value and is adjusted according to the rain and snow or shielding environment of the scene.
6. The method for detecting floating ice based on the X-band target surveillance radar according to claim 4, wherein: in step 8, the method for calculating the floating ice area comprises the following steps:
step 8-1, condensation: adopting an image edge recognition function in Opencv to perform all the labyrinths id The small lattices 1 are communicated and condensed to form a plurality of polygon images;
step 8-2, calculating longitude and latitude: calculating the longitude and latitude of the edge point of each polygon image;
step 8-3, calculating the number of the cells: calculating the lattice contained in each polygon image id A number of cells of 1;
step 8-4, drawing a minimum rectangle: drawing a minimum rectangle on the periphery of each polygon image;
step 8-5, calculating rectangular parameters: the rectangle parameters comprise longitude and latitude of the center point of the minimum rectangle, length of the long side of the minimum rectangle and lattice n ；lattice n Is the lattice contained within the smallest rectangle id A number of cells of 1;
step 8-6, calculating the area S of the single floating ice, wherein the calculation formula is as follows:
s=area_total =area represented by a single pixel point
Wherein, area_total is all the tiles within the minimum rectangle id The sum of pixel points=1, the calculation formula is:
area_total＝lattice n *lengh。
7. the method for detecting floating ice based on the X-band target surveillance radar according to claim 6, wherein: in the step 8, the floating ice information also comprises a floating ice position site and a floating ice maximum horizontal scale; the floating ice position site is obtained through the longitude and latitude of the smallest rectangular center point in the step 8-5; the largest horizontal dimension of the floating ice is the side length of the long side of the smallest rectangle.
8. The method for detecting floating ice based on the X-band target surveillance radar according to claim 7, wherein: in step 8, the floating ice information further includes a floating ice moving speed V, and a calculation formula of the floating ice moving speed V is:
V＝(site2-site1)/(T2-T1)
where site1 and site2 are the positions of the ice floe at times T1 and T2, respectively.
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