CN114463224B - Ocean target image restoration and identification method and system based on SAR technology - Google Patents
Ocean target image restoration and identification method and system based on SAR technology Download PDFInfo
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Abstract
The invention discloses a method and a system for restoring and identifying a marine target image based on an SAR (synthetic aperture radar), which are used for identifying a marine target through an AIS (automatic identification system) in real time, calculating a real-time drift index by combining GPS (global positioning system) positioning data of the marine target, then acquiring the marine target image by using a Synthetic Aperture Radar (SAR), calculating a drift region of the target image, and finally restoring the target image according to the drift region of the target image. By GPS positioning, the moving direction of the geographic marine target is accurate, the result that the real marine path is inconsistent with the course due to the fact that natural factors such as ocean current and wind are difficult to disappear in the modes of a compass and the like is avoided, redundant or repeated pixel gray values in the image are optimized and calculated, and a more accurate and objective marine target gray image is obtained.
Description
Technical Field
The invention belongs to the technical field of data acquisition, intelligent identification and graphic processing, and particularly relates to a method and a system for repairing and identifying an ocean target image based on an SAR technology.
Background
The SAR technology is used as an aerospace technology, the utilization rate of the SAR technology in the fields of navigation surveying and mapping and ship navigation is higher and higher, although the SAR technology is used for identifying a navigation target, the SAR technology is mature day by day, and the problems of low resolution and insufficient accuracy in the aspect of imaging of the SAR technology often exist; the image of the object under navigation is blurred or deviated due to the time span between the navigation of the marine object and the capturing of microwaves by the satellite or the airplane, which affects the accuracy of the image of the marine object. How to more accurately measure the motion direction of a navigation target through GPS positioning of the navigation target and weaken the effect of the blur or the deviation to repair the marine target image is a hot problem of the application research of the SAR technology at present.
Disclosure of Invention
The invention aims to provide a method and a system for restoring and identifying an ocean target image based on an SAR technology, which are used for solving one or more technical problems in the prior art and at least providing a beneficial selection or creation condition.
In order to achieve the above object, according to an aspect of the present invention, there is provided a method for restoring and identifying a marine target image based on SAR technology, the method comprising the steps of:
s100, calculating a real-time drift index through an AIS system;
s200, acquiring a target image by using a Synthetic Aperture Radar (SAR);
s300, combining the real-time drift index to obtain a drift region of the target image;
s400, repairing the target image according to the drift region of the target image.
Further, in step S100, the method for calculating the real-time drift index through the AIS system is as follows:
s101, identifying a marine target in real time through an AIS system;
s102, acquiring GPS positioning data of the identified marine target;
s103, establishing a step difference index through GPS positioning data;
and S104, calculating a real-time drift index according to the step difference index.
Further, in step S101, the method for identifying the marine target in real time through the AIS system is: the method comprises the steps of obtaining marine targets and positioning data thereof on a sea area through an AIS system, wherein the marine targets refer to all ships which can be identified by the AIS ship automatic identification system in the sea area, and one ship registration number is used as one marine target, and the AIS system is the ship automatic identification system.
Further, in step S102, the method for acquiring GPS positioning data of the identified marine target is: obtaining ship registration numbers of all marine targets and global positioning system data thereof from an AIS ship automatic identification system; the method comprises the steps of taking a ship registration number as a marine target, and taking GPS (global positioning system) data as GPS positioning data GLoc (X, Y), wherein X and Y respectively represent a longitude value and a latitude value.
Further, in step S103, the method for establishing the step difference index by the GPS positioning data is: acquiring GPS positioning data GLoc (X, Y) of a marine target in real time; constructing newly acquired NGL GPS positioning data GLoc (X, Y) into a newly positioned sequence RGLLs in reverse time sequence, wherein the newly positioned sequence RGLLs is [ GLoc [ ]i1(X,Y)]，i1∈[1，NGL]Wherein NGL is the length of RGLLs, and takes the value of [1,5 ]]，GLoci1(X, Y) is the i1 th GPS positioning data in RGLLs, a variable i2 is set, and the value of the initialization i2 is 1; setting an empty sequence as a step difference sequence DGLs; jumping to step A01; setting a variable with an initial value of 0 as a step difference index DGFlg of the current time;
a01, obtaining longitude step difference DGX ═ GLoc when i2 < NGLi2(X,Y)(X)－GLoci2+1(X, Y) (X), wherein GLoci2(X, Y) (X) represents GLoci2Longitude of (X, Y), GLoc as welli2+1(X,Y)(X)Represents GLoci2+1Longitude of (X, Y); obtaining the latitude step difference DGY = GLoci2(X,Y)(Y)－GLoci2+1(X, Y) (Y), wherein GLoci2(X, Y) (Y) represents GLoci2Latitude of (X, Y), GLoci2+1(X, Y) (Y) represents GLoci2+1(X, Y) latitude; forming a step difference pair DG (DGX, DGY) by the longitude step difference DGX and the latitude step difference DGY, inputting the DG (DGX, DGY) into the step difference sequence DGLs as the i2 th element of the step difference sequence DGLs, adding 1 to the value of i2, and jumping to the step A01;
when i2 is more than or equal to NGL, obtaining the step difference sequence DGLs at the current moment, wherein [ DGLs ] isi3(DGX,DGY)]，i3∈[1，NGD]Wherein i3 is the step pair sequence number, and NGD is the number of elements in the step sequence DGLs; taking the arithmetic mean of the longitude step differences of each element in the step difference sequence as a longitude step difference mean EDGX, and taking the arithmetic mean of the latitude step differences of each element in the step difference sequence as a latitude step difference mean EDGY, so as to obtain a step difference mean EDG of the current moment, wherein the step difference mean EDG comprises EDGX and EDGY; taking the standard deviation of longitude step differences of all elements in the step difference sequence DGLs as a longitude step difference threshold DDGX, and taking the standard deviation of latitude step differences of all elements in the step difference sequence DGLs as a latitude step difference threshold DDGY, so as to obtain a step difference threshold DDG of the current moment, wherein the step difference threshold DDG comprises DDGX and DDGY;
setting an interval as longitude step difference index DGFLgX, the interval of DGFLgX is [ EDGX-DDGX, EDGX + DDGX ], setting an interval as latitude step difference index DGFLgY, the interval of DGFLgY is [ EDGY-DDGY, EDGY + DDGY ]; if the DGX value in the DG (DGX, DGY) of the step difference pair at the current moment is within the longitude step difference index DGFlgX and the DGY value is within the latitude step difference index DGFlgY, the step difference index DGFlg is 1, otherwise, the step difference index DGFlg is 0;
jumping to step A02;
and A02, ending.
The course direction is accurate through GPS positioning, and if natural factors such as ocean current and wind are difficult to disappear through a compass and the like, the real navigation path and the course are inconsistent.
Further, in step S104, a real-time drift index is calculated according to the step difference indexThe method comprises the following steps: acquiring step difference indexes DGFlg of the latest NGL moments, calculating a real-time drift index if the value of the step difference indexes DGFlg of the latest NGL moments is 1, and otherwise, recalculating the step difference indexes DGFlg after waiting for next acquisition of GPS positioning data GLoc (X, Y) of the marine target; obtaining a step difference sequence DGLs at the current moment, and calculating a longitude drift index MX:
wherein i4 is a variable, DGLs (i4) (DGX) represent the longitude step difference DGX of the i4 th element in the step difference sequence DGLs, rsX is a longitude drift sensitive coefficient, and the calculation method is as follows:
(ii) a Wherein i5 is a variable, DGXi5Represents the longitude step difference at time i 5; EDGXi5Represents the mean value of the longitude step differences at the i5 th moment; DDGXi5A longitude step difference threshold representing time i 5; the ith 5 time point represents the ith 5 time point in the latest acquired NGL time points;
calculating a latitude drift index MY:
wherein i6 is variable, DGLs (i6) (DGY) represents the latitude step difference DGY of the i6 th element in the step difference sequence DGLs, rsY is latitude drift sensitive coefficient, and the calculation method is as follows:
(ii) a Wherein i7 is a variable, DGYi7Represents the latitude step difference at the i7 th moment; EDGY (electric double-edged fine grid)i5Represents the mean value of the latitude step difference at the i7 th moment; DDGY (digital data processing)i7A latitude step difference threshold representing time i 7; the ith 7 time point represents the ith 7 time point in the latest acquired NGL time points; a vector consisting of a longitude drift index MX and a latitude drift index MY is used as the real-time drift index CDM (MX, MY).
Further limiting the opportunity of the SAR to obtain the target image through the latitude step difference index DGFlgY, limiting the ambiguity of the target image in the motion direction to the maximum extent, and reducing the distortion in the direction vertical to the motion direction; and further refining and analyzing the motion direction of the target through the drift sensitivity coefficient and the drift index, and taking the obtained real-time drift index CDM (MX, MY) as the reference motion direction of the target.
Further, in step S200, the method for acquiring the target image by using the synthetic aperture radar SAR is: the method comprises the steps of sending and receiving microwaves through an SAR (synthetic aperture radar) with an imaging function, detecting an SAR image of a target sea area, identifying a marine target from the SAR image according to a ship target detection algorithm, and taking an image of the marine target in the SAR image as a target image; performing geometric correction and noise reduction on the target image, and adaptively rotating the target image by combining a geographic coordinate system; the ship target detection algorithm is as follows: any one of ship target detection based on background clutter statistical distribution, ship target detection based on polarization decomposition or ship target detection based on polarization characteristics.
Further, in step S300, the method for obtaining the drift region of the target image by combining the real-time drift index is: according to the resolution of the target image, the number of pixels in the vertical direction of the target image is taken as the image height ht, and the number of pixels in the horizontal direction of the target image is taken as the image length len; performing background extraction on the target image by using a maximum inter-class variance method, a maximum entropy automatic threshold method or a histogram segmentation method to divide each pixel in the target image into a target pixel tgpx and a background pixel bgpx; establishing a coordinate system Pix by taking the pixels at the lower left corner of the target image as an origin, and representing the origin of the coordinate system Pix by Pix (0, 0); in a coordinate system Pix, Pix (a, b) is used for representing pixels of an a-th column and a b-th row in a target image, wherein a is a column sequence number, the value range is [1, ht ], b is a row sequence number, and the value range is [1, len ]; taking a central point of a target image as a core pixel Pix (Ca, Cb), wherein Ca and Cb respectively represent a serial number of a column where the central point is located and a serial number of a row; the method comprises the steps that the time required for a synthetic aperture radar SAR to obtain a target image is taken as TM, the AIS system calculates and obtains the average navigation speed SSPD of an ocean target in the latest TM time, and the time for receiving or collecting microwaves in the process of obtaining the target image by the synthetic aperture radar SAR is taken as the collection time CLP; the azimuth resolution in the original image is ARs, the range resolution in the original image is DRs, the included angle between the straight line of the azimuth direction of the synthetic aperture radar and the straight line of the drift index CDM (MX, MY) is an azimuth angle AAg, the included angle between the straight line of the range direction of the synthetic aperture radar and the straight line of the drift index CDM (MX, MY) is a range angle DAg,
calculating course resolution SRs: SRs ═
；
Calculating and acquiring a navigation direction SCmps of the ocean target in the latest TM time from an AIS system, and calculating an average drift velocity CSPD (CSPD ═ SSPD ÷ cos (SCAg)) by taking an included angle between a straight line of the navigation direction SCmps and a straight line of a drift index CDM (MX, MY) as a deviation angle SCAg; and calculating a drift region rpxl of the target image through the average drift velocity, wherein the rpxl is int [0.5 × (CLP × CSPD + SRs) × pscl ] -1, int [ ] is a sign of an integer function, pscl is a scale (a scale of the target image on a corresponding line segment of the actual ground), and the scale is a ratio between the SAR image distance and an actual geographic coordinate corresponding to the SAR image, or the scale is 1: 40000.
Further, in step S400, the method for repairing the target image according to the drift region of the target image is: adding pixels with the gray value of 0 in rpxl +1 columns to the left side and the right side of the target image respectively, setting 2 variables with the initial value of 0 as a first gray value FGry and a gray loss Dgry for all the pixels, wherein the added pixels are background pixels; setting a variable j1, and initializing the value of j1 to be 1; jumping to step B01;
b01, when j1 is not more than ht-1, setting a variable j2, initializing the value of j2 to be 1, and jumping to the step B02; when j1 is greater than ht-1, calculating the arithmetic mean value of all gray level loss Dgry in the target image as the average gray level loss EDgry; jumping to step B05;
b02, when j2 is not more than len-1, jumping to the step B03; when j2 is larger than len-1, adding 1 to the value of j1, and jumping to step B01;
b03, if Pix (j1, j2) is the background pixel bgpx, adding 1 to the value of j2, jumping to step B02; if Pix (j1, j2) is the target pixel tgpx, taking the set of pixels from Pix (j 1-rpxl, j2) to Pix (j 1-1, j2) as a tail set Ttl, and taking the ratio of all target pixels tgpx in the tail set Ttl to the number of elements in the tail set Ttl as a target tail ratio TtlRt; a set of pixels from Pix (j1+1, j2) to Pix (j1+ rpxl, j2) is used as a header set Thd, and the ratio of the number of elements in the header set Thd to the number of target pixels tgpx in the header set Thd is used as a target header ratio ThdRt; jumping to step B04;
b04, if TtlRt is less than or equal to ThdRt, calculating the first gray value FGry as: FGry ═ TtlRt × EtlGr, where EtlGr represents the arithmetic average of the grayscale values of the individual pixels in the tail set Ttl and the grayscale values of Pix (j1, j 2); calculating a gray loss Dgry, which is an Ogry-FGry, wherein the Ogry is a gray value of a Pix (j1, j2) pixel; then add 1 to the value of j2 and jump to step B02; if TtlRt > ThdRt, the first gray value FGry is calculated as: FGry — ThdRt × EhdGr, where EhdGr represents an arithmetic average of the set of grayscale values of the respective pixels in the header set Thd and the grayscale value of Pix (j1, j 2); calculating a gray loss Dgry, which is an Ogry-FGry, wherein the Ogry is a gray value of a Pix (j1, j2) pixel; adding 1 to the value of j2, and jumping to step B02;
b05, traversing all target pixels in the target image, and if the gray loss Dgry of the target pixels is larger than or equal to EDgry, updating the gray value of the pixels to be the value of the first gray value FGry; jumping to step B06; if the gray loss Dgry of the target pixel is less than EDgry, the gray value of the target pixel is not changed; jumping to step B06;
and B06, finishing.
And (4) carrying out picture restoration on the distortion of the obtained target pixel in the motion direction, and modifying the misinformed target pixel to obtain a picture with more authenticity.
The invention also provides an ocean target image restoration recognition system based on the SAR technology, which comprises the following components: the processor executes the computer program to implement the steps in the method for identifying and repairing the marine target image based on the SAR technology, the system for identifying and repairing the marine target image based on the SAR technology can be run in computing devices such as a desktop computer, a notebook computer, a palm computer, a cloud data center and the like, and the system that can run can include, but is not limited to, the processor, the memory and a server cluster, and the processor executes the computer program to run in units of the following systems:
the drift quantifying unit is used for calculating a real-time drift index through the AIS system;
the image shooting unit is used for obtaining a target image by utilizing a Synthetic Aperture Radar (SAR);
the drift region metering unit is used for obtaining a drift region of the target image by combining the real-time drift index;
the graph repairing unit is used for repairing the target image according to the drift region of the target image;
the beneficial effects of the invention are as follows: the invention provides a method and a system for repairing and identifying an ocean target image based on an SAR technology, which are used for accurately positioning a course through a GPS (global positioning system), and if natural factors such as ocean current and wind are difficult to disappear in a compass mode, the result that a real navigation path is inconsistent with the course is obtained; the navigation state of the synthetic aperture radar SAR during shooting of the ocean target is accurately measured, redundant or repeated pixel gray values in the image are optimized and calculated, and a more accurate and objective ocean target gray image is obtained.
Drawings
The above and other features of the invention will be more apparent from the detailed description of the embodiments shown in the accompanying drawings in which like reference characters designate the same or similar elements, and it will be apparent that the drawings in the following description are merely exemplary of the invention and that other drawings may be derived by those skilled in the art without inventive effort, wherein:
FIG. 1 is a flow chart of a method for repairing and identifying an ocean target image based on SAR technology;
fig. 2 is a structural diagram of a marine target image restoration recognition system based on the SAR technology.
Detailed Description
The conception, the specific structure and the technical effects of the present invention will be clearly and completely described in conjunction with the embodiments and the accompanying drawings to fully understand the objects, the schemes and the effects of the present invention. It should be noted that the embodiments and features of the embodiments in the present application may be combined with each other without conflict.
Fig. 1 is a flowchart of a method for repairing and identifying a marine target image based on an SAR technology, and the method for repairing and identifying a marine target image based on an SAR technology according to an embodiment of the present invention is described below with reference to fig. 1, and includes the following steps:
s100, calculating a real-time drift index through an AIS system;
s200, acquiring a target image by using a Synthetic Aperture Radar (SAR);
s300, combining the real-time drift index to obtain a drift region of the target image;
s400, repairing the target image according to the drift region of the target image.
Further, in step S100, the method for calculating the real-time drift index through the AIS system is as follows:
s101, identifying a marine target in real time through an AIS system;
s102, acquiring GPS positioning data of the identified marine target;
s103, establishing a step difference index through GPS positioning data;
and S104, calculating a real-time drift index according to the step difference index.
Further, in step S101, the method for identifying the marine target in real time through the AIS system is: the method comprises the steps of obtaining marine targets and positioning data thereof on a sea area through an AIS system, wherein the marine targets refer to all ships which can be identified by the AIS ship automatic identification system in the sea area, and one ship registration number is used as one marine target, and the AIS system is the ship automatic identification system.
Further, in step S102, the method for acquiring GPS positioning data of the identified marine target is: obtaining ship registration numbers of all marine targets and global positioning system data thereof from an AIS ship automatic identification system; the method comprises the steps of taking a ship registration number as a marine target, and taking GPS (global positioning system) data as GPS positioning data GLoc (X, Y), wherein X and Y respectively represent a longitude value and a latitude value.
Further, in step S103, the method for establishing the step difference index by using the GPS positioning data is: acquiring GPS positioning data GLoc (X, Y) of a marine target in real time; constructing newly acquired NGL GPS positioning data GLoc (X, Y) into a newly positioned sequence RGLLs in reverse time sequence, wherein the newly positioned sequence RGLLs is [ GLoc [ ]i1(X,Y)]，i1∈[1，NGL]Wherein NGL is the length of RGLLs, and takes the value of [1,5 ]]，GLoci1(X, Y) setting a variable i2 for the i1 th GPS positioning data in RGLLs, and initializing the value of i2 to be 1; setting an empty sequence as a step difference sequence DGLs; jumping to step A01; setting a variable with an initial value of 0 as a step difference index DGFlg of the current time;
a01, obtaining longitude step difference DGX ═ GLoc when i2 < NGLi2(X,Y)(X)－GLoci2+1(X, Y) (X), wherein GLoci2(X, Y) (X) represents GLoci2Longitude of (X, Y), GLoc as welli2+1(X, Y) (X) represents GLoci2+1Longitude of (X, Y); obtaining the latitude step difference DGY = GLoci2(X,Y)(Y)－GLoci2+1(X, Y) (Y), wherein GLoci2(X, Y) (Y) represents GLoci2(X, Y) latitude, GLoci2+1(X, Y) (Y) represents GLoci2+1(X, Y) latitude; forming a step difference pair DG (DGX, DGY) by the longitude step difference DGX and the latitude step difference DGY, inputting the DG (DGX, DGY) into the step difference sequence DGLs as the i2 th element of the step difference sequence DGLs, adding 1 to the value of i2, and jumping to the step A01;
when i2 is more than or equal to NGL, obtaining the step difference sequence DGLs at the current moment, wherein [ DGLs ] isi3(DGX,DGY)]，i3∈[1，NGD]Wherein i3 is the step pair sequence number, and NGD is the number of elements in the step sequence DGLs; taking the arithmetic mean of the longitude step differences of each element in the step difference sequence as a longitude step difference mean EDGX, and taking the arithmetic mean of the latitude step differences of each element in the step difference sequence as a latitude step difference mean EDGY, thereby obtaining the step difference of the current momentThe mean value EDG comprises EDGX and EDGY; taking the standard deviation of the longitude step differences of all elements in the step difference sequence DGLs as a longitude step difference threshold DDGX, and taking the standard deviation of the latitude step differences of all elements in the step difference sequence DGLs as a latitude step difference threshold DDGY, so as to obtain a step difference threshold DDG of the current moment, wherein the step difference threshold DDG comprises the DDGX and the DDGY;
setting an interval as longitude step difference index DGFlgX, wherein the interval of DGFlgX is [ EDGX-DDGX, EDGX + DDGX ], setting an interval as latitude step difference index DGFlgY, and the interval of DGFlgY is [ EDGY-DDGY, EDGY + DDGY ]; if the DGX value in the DG (DGX, DGY) of the step difference pair at the current moment is within the longitude step difference index DGFlgX and the DGY value is within the latitude step difference index DGFlgY, the step difference index DGFlg is 1, otherwise, the step difference index DGFlg is 0;
jumping to step A02;
and A02, ending.
The course direction is accurate through GPS positioning, and if natural factors such as ocean current and wind are difficult to disappear through a compass and the like, the real navigation path and the course are inconsistent.
Further, in step S104, the method for calculating the real-time drift index according to the step difference index is: acquiring step difference indexes DGFlg of the latest NGL moments, calculating a real-time drift index if the value of the step difference indexes DGFlg of the latest NGL moments is 1, and otherwise, recalculating the step difference indexes DGFlg after waiting for next acquisition of GPS positioning data GLoc (X, Y) of the marine target; obtaining a step difference sequence DGLs at the current moment, and calculating a longitude drift index MX:
wherein i4 is a variable, DGLs (i4) (DGX) represent the longitude step difference DGX of the i4 th element in the step difference sequence DGLs, rsX is a longitude drift sensitive coefficient, and the calculation method is as follows:
(ii) a Wherein i5 is a variable, DGXi5Represents the longitude step difference at time i 5; EDGXi5Represents the mean value of the longitude steps at time i 5;DDGXi5a longitude step difference threshold representing time i 5; the i5 th time represents the i5 th time of the latest acquired NGL times;
calculating a latitude drift index MY:
wherein i6 is variable, DGLs (i6) (DGY) represents the latitude step difference DGY of the i6 th element in the step difference sequence DGLs, rsY is latitude drift sensitive coefficient, and the calculation method is as follows:
(ii) a Wherein i7 is a variable, DGYi7Represents the latitude step difference at the i7 th moment; EDGY (electric double-edged fine grid)i5Represents the mean value of the latitude step difference at the i7 th moment; DDGY (digital DDGY)i7A latitude step difference threshold representing time i 7; the i7 th time represents the i7 th time of the latest acquired NGL times; a vector consisting of a longitude drift index MX and a latitude drift index MY is used as the real-time drift index CDM (MX, MY).
Further limiting the opportunity of the SAR to obtain the target image through the latitude step difference index DGFlgY, limiting the ambiguity of the target image in the motion direction to the maximum extent, and reducing the distortion in the direction vertical to the motion direction; and further finely analyzing the motion direction of the target by using the drift sensitivity coefficient and the drift index, and taking the obtained real-time drift index CDM (MX, MY) as the reference motion direction of the target.
Further, in step S200, the method for acquiring the target image by using the synthetic aperture radar SAR is: the method comprises the steps of sending and receiving microwaves through an SAR (synthetic aperture radar) with an imaging function, detecting an SAR image of a target sea area, identifying a marine target from the SAR image according to a ship target detection algorithm, and taking an image of the marine target in the SAR image as a target image; performing geometric correction and noise reduction on the target image, and adaptively rotating the target image by combining a geographic coordinate system; the ship target detection algorithm is as follows: any one of ship target detection based on background clutter statistical distribution, ship target detection based on polarization decomposition or ship target detection based on polarization characteristics.
Further, in step S300, the method for obtaining the drift region of the target image by combining the real-time drift index is: according to the resolution of the target image, the number of pixels in the vertical direction of the target image is taken as the image height ht, and the number of pixels in the horizontal direction of the target image is taken as the image length len; performing background extraction on the target image by using a maximum inter-class variance method, a maximum entropy automatic threshold method or a histogram segmentation method to divide each pixel in the target image into a target pixel tgpx and a background pixel bgpx; establishing a coordinate system Pix by taking the pixel at the lower left corner of the target image as an origin, and representing the origin of the coordinate system Pix by Pix (0, 0); in a coordinate system Pix, Pix (a, b) represents pixels of an a-th row and a b-th row in a target image, wherein a is a row sequence number and has a value range of [1, ht ], b is a row sequence number and has a value range of [1, len ]; taking a central point of a target image as a core pixel Pix (Ca, Cb), wherein Ca and Cb respectively represent a serial number of a column where the central point is located and a serial number of a row; the method comprises the steps that the time required for a Synthetic Aperture Radar (SAR) to obtain an ocean target image is taken as TM, the AIS system calculates and obtains the average navigation speed SSPD of the ocean target in the latest TM time, and the time for receiving or collecting microwaves in the process of obtaining the ocean target image by the Synthetic Aperture Radar (SAR) is taken as the collection time CLP; the azimuth resolution in the original image is ARs, the range resolution in the original image is DRs, the included angle between the straight line of the azimuth direction of the synthetic aperture radar and the straight line of the drift index CDM (MX, MY) is an azimuth angle AAg, the included angle between the straight line of the range direction of the synthetic aperture radar and the straight line of the drift index CDM (MX, MY) is a range angle DAg,
calculating course resolution SRs: SRs ═
；
Calculating and obtaining a navigation direction SCmps of the ocean target in the latest TM time from the AIS system, taking an included angle between a straight line where the navigation direction SCmps is located and a straight line where the drift index CDM (MX, MY) is located as a deviation angle SCAg, and calculating an average drift velocity CSPD: CSPD ═ SSPD ÷ cos (scag); the drift region rpxl of the target image can be calculated through the average drift velocity, wherein the rpxl is int [0.5 × (CLP × CSPD + SRs) × pscl ] -1, int [ ] is the sign of the integer function, and pscl is the scale (the scale of the target image on the corresponding line segment of the actual ground).
Further, in step S400, the method for repairing the target image according to the drift region of the target image is: adding pixels with the gray value of 0 in rpxl +1 columns to the left side and the right side of the target image respectively, wherein the added pixels are background pixels, and setting 2 variables with the initial value of 0 as a first gray value FGry and a gray loss Dgry for all the pixels respectively; setting a variable j1, and initializing the value of j1 to be 1; jumping to step B01;
b01, when j1 is not more than ht-1, setting a variable j2, initializing the value of j2 to be 1, and jumping to the step B02; when j1 is larger than ht-1, calculating the arithmetic average value of all gray scale loss Dgry in the target image as gray scale average loss EDgry; jumping to step B05;
b02, when j2 is not more than len-1, jumping to step B03; when j2 is larger than len-1, adding 1 to the value of j1, and jumping to step B01;
b03, if Pix (j1, j2) is the background pixel bgpx, adding 1 to the value of j2, jumping to step B02; if Pix (j1, j2) is the target pixel tgpx, a set of pixels from Pix (j 1-rpxl, j2) to Pix (j 1-1, j2) is used as a tail set Ttl, and the ratio of all target pixels tgpx in the tail set Ttl to the number of elements in the tail set Ttl is used as a target tail ratio TtlRt; a set of pixels from Pix (j1+1, j2) to Pix (j1+ rpxl, j2) is used as a header set Thd, and the ratio of the number of elements in the header set Thd to the number of target pixels tgpx in the header set Thd is used as a target header ratio ThdRt; jumping to step B04;
b04, if TtlRt is less than or equal to ThdRt, calculating the first gray value FGry as: FGry ═ TtlRt × EtlGr, where EtlGr represents the arithmetic average of the grayscale values of the individual pixels in the tail set Ttl and the grayscale values of Pix (j1, j 2); calculating a gray loss Dgry, which is an Ogry-FGry, wherein the Ogry is a gray value of a Pix (j1, j2) pixel; then add 1 to the value of j2 and jump to step B02; if TtlRt > ThdRt, the first gray value FGry is calculated as: FGry — ThdRt × EhdGr, where EhdGr represents an arithmetic average of the set of grayscale values of the respective pixels in the header set Thd and the grayscale value of Pix (j1, j 2); calculating a gray loss Dgry, which is an Ogry-FGry, wherein the Ogry is a gray value of a Pix (j1, j2) pixel; adding 1 to the value of j2, and jumping to step B02;
b05, traversing all target pixels in the target image, and if the gray loss Dgry of the target pixels is larger than or equal to EDgry, updating the gray value of the pixels to be the value of the first gray value FGry; jumping to step B06; if the gray loss Dgry of the target pixel is less than EDgry, the gray value of the target pixel is not changed; jumping to step B06;
and B06, finishing.
And (4) carrying out picture restoration on the distortion of the obtained target pixel in the motion direction, and modifying the misinformed target pixel to obtain a picture with more authenticity.
An embodiment of the present invention provides an ocean target image restoration recognition system based on an SAR technology, and as shown in fig. 2, the present invention is a structure diagram of an ocean target image restoration recognition system based on an SAR technology, and an ocean target image restoration recognition system based on an SAR technology of the embodiment includes: the system comprises a processor, a memory and a computer program stored in the memory and capable of running on the processor, wherein the processor executes the computer program to realize the steps in the embodiment of the ocean target image restoration recognition system based on SAR technology.
The system comprises: a memory, a processor, and a computer program stored in the memory and executable on the processor, the processor executing the computer program to run in the units of the following system:
the drift quantifying unit is used for calculating a real-time drift index through the AIS system;
the image shooting unit is used for obtaining a target image by utilizing a Synthetic Aperture Radar (SAR);
the drift region metering unit is used for obtaining a drift region of the target image by combining the real-time drift index;
and the graph repairing unit is used for repairing the target image according to the drift domain of the target image.
The ocean target image restoration and identification system based on the SAR technology can be operated in computing equipment such as a desktop computer, a notebook computer, a palm computer and a cloud server. The marine target image restoration and identification system based on the SAR technology can be operated by a system comprising, but not limited to, a processor and a memory. It will be understood by those skilled in the art that the example is merely an example of a SAR technology-based marine target image restoration recognition system, and does not constitute a limitation of a SAR technology-based marine target image restoration recognition system, and may include more or less components than the other, or some components in combination, or different components, for example, the SAR technology-based marine target image restoration recognition system may further include an input-output device, a network access device, a bus, etc.
The Processor may be a Central Processing Unit (CPU), other general purpose Processor, a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), a Field Programmable Gate Array (FPGA) or other Programmable logic device, discrete Gate or transistor logic device, discrete hardware component, or the like. The general processor can be a microprocessor or the processor can be any conventional processor and the like, the processor is a control center of the operating system of the ocean target image restoration recognition system based on the SAR technology, and various interfaces and lines are utilized to connect various parts of the operable system of the ocean target image restoration recognition system based on the SAR technology.
The memory may be used for storing the computer program and/or the module, and the processor may implement various functions of the sea target image restoration recognition system based on the SAR technology by operating or executing the computer program and/or the module stored in the memory and calling the data stored in the memory. The memory may mainly include a storage program area and a storage data area, wherein the storage program area may store an operating system, an application program required by at least one function (such as a sound playing function, an image playing function, etc.), and the like; the storage data area may store data (such as audio data, a phonebook, etc.) created according to the use of the cellular phone, and the like. In addition, the memory may include high speed random access memory, and may also include non-volatile memory, such as a hard disk, a memory, a plug-in hard disk, a Smart Media Card (SMC), a Secure Digital (SD) Card, a Flash memory Card (Flash Card), at least one magnetic disk storage device, a Flash memory device, or other volatile solid state storage device.
Although the present invention has been described in considerable detail and with reference to certain illustrated embodiments, it is not intended to be limited to any such details or embodiments or any particular embodiment, so as to effectively encompass the intended scope of the invention. Furthermore, the foregoing describes the invention in terms of embodiments foreseen by the inventor for which an enabling description was available, notwithstanding that insubstantial modifications of the invention, not presently foreseen, may nonetheless represent equivalent modifications thereto.
Claims (7)
1. A marine target image restoration and identification method based on SAR technology is characterized by comprising the following steps:
s100, calculating a real-time drift index through an AIS system;
s200, acquiring a target image by using a Synthetic Aperture Radar (SAR);
s300, combining the real-time drift index to obtain a drift region of the target image;
s400, repairing the target image according to the drift region of the target image;
the method for calculating the real-time drift index through the AIS system comprises the following steps:
s101, identifying a marine target in real time through an AIS system;
s102, acquiring GPS positioning data of the identified marine target;
s103, establishing a step difference index through GPS positioning data;
s104, calculating a real-time drift index according to the step difference index;
in step S300, the method for obtaining the drift region of the target image by combining the real-time drift index includes: according to the resolution of the target image, the number of pixels in the vertical direction of the target image is taken as the image height ht, and the number of pixels in the horizontal direction of the target image is taken as the image length len; performing background extraction on the target image by using a maximum inter-class variance method, a maximum entropy automatic threshold method or a histogram segmentation method to divide each pixel in the target image into a target pixel tgpx and a background pixel bgpx; establishing a coordinate system Pix by taking the pixel at the lower left corner of the target image as an origin, and representing the origin of the coordinate system Pix by Pix (0, 0); in a coordinate system Pix, Pix (a, b) represents pixels of an a-th row and a b-th row in a target image, wherein a is a row sequence number and has a value range of [1, ht ], b is a row sequence number and has a value range of [1, len ]; taking a central point of a target image as a core pixel Pix (Ca, Cb), wherein Ca and Cb respectively represent a serial number of a column where the central point is located and a serial number of a row; the method comprises the steps that the time required for a synthetic aperture radar SAR to obtain a target image is taken as TM, the AIS system calculates and obtains the average navigation speed SSPD of an ocean target in the latest TM time, and the time for receiving or collecting microwaves in the process of obtaining the target image by the synthetic aperture radar SAR is taken as the collection time CLP; the azimuth resolution in the original image is ARs, the distance resolution in the original image is DRs, the included angle between the straight line of the azimuth direction of the synthetic aperture radar and the straight line of the drift index CDM (MX, MY) is an azimuth angle AAg, the included angle between the straight line of the distance direction of the synthetic aperture radar and the straight line of the drift index CDM (MX, MY) is a distance angle DAg, and the course resolution SRs is calculated:
SRs＝
；
calculating and obtaining a navigation direction SCmps of the ocean target in the latest TM time from the AIS system, taking an included angle between a straight line where the navigation direction SCmps is located and a straight line where the drift index CDM (MX, MY) is located as a deviation angle SCAg, and calculating an average drift velocity CSPD: CSPD ═ SSPD ÷ cos (scag); calculating a drift region rpxl of the target image through the average drift velocity, wherein the rpxl is int [0.5 × (CLP × CSPD + SRs) × pscl ] -1, int [ ] is a sign of a rounding function, and pscl is a scale;
in step S400, the method for repairing the target image according to the drift region of the target image is: adding pixels with the gray value of 0 in rpxl +1 columns to the left side and the right side of the target image respectively, setting 2 variables with the initial value of 0 as a first gray value FGry and a gray loss Dgry for all the pixels, wherein the added pixels are background pixels; setting a variable j1, and initializing the value of j1 to be 1; jumping to step B01, wherein rpxl is a drift domain;
b01, when j1 is not more than ht-1, setting a variable j2, initializing the value of j2 to be 1, and jumping to the step B02; when j1 is greater than ht-1, calculating the arithmetic mean value of all gray level loss Dgry in the target image as the average gray level loss EDgry; jumping to step B05;
b02, when j2 is not more than len-1, jumping to the step B03; when j2 is larger than len-1, adding 1 to the value of j1, and jumping to step B01;
b03, if Pix (j1, j2) is the background pixel bgpx, adding 1 to the value of j2, and jumping to step B02; if Pix (j1, j2) is the target pixel tgpx, taking the set of pixels from Pix (j 1-rpxl, j2) to Pix (j 1-1, j2) as a tail set Ttl, and taking the ratio of all target pixels tgpx in the tail set Ttl to the number of elements in the tail set Ttl as a target tail ratio TtlRt; a set of pixels from Pix (j1+1, j2) to Pix (j1+ rpxl, j2) is used as a header set Thd, and the ratio of the number of elements in the header set Thd to the number of target pixels tgpx in the header set Thd is used as a target header ratio ThdRt; jumping to step B04;
b04, if TtlRt is less than or equal to ThdRt, calculating the first gray value FGry as: FGry ═ TtlRt × EtlGr, where EtlGr represents the arithmetic average of the grayscale values of the individual pixels in the tail set Ttl and the grayscale values of Pix (j1, j 2); calculating a gray loss Dgry, which is an Ogry-FGry, wherein the Ogry is a gray value of a Pix (j1, j2) pixel; then add 1 to the value of j2 and jump to step B02; if TtlRt > ThdRt, the first gray-level value FGry is calculated as: FGry — ThdRt × EhdGr, where EhdGr represents an arithmetic average of the set of the gradation values of the respective pixels in the header set Thd and the gradation value of Pix (j1, j 2); calculating a gray loss Dgry, which is an Ogry-FGry, wherein the Ogry is a gray value of a Pix (j1, j2) pixel; adding 1 to the value of j2, and jumping to step B02;
b05, traversing all target pixels in the target image, and if the gray loss Dgry of the target pixels is larger than or equal to EDgry, updating the gray value of the pixels to be the value of the first gray value FGry; jumping to step B06; if the gray loss Dgry of the target pixel is less than EDgry, the gray value of the target pixel is not changed; jumping to step B06;
and B06, finishing.
2. The method for repairing and identifying the image of the marine target based on the SAR technology as claimed in claim 1, wherein in step S101, the method for identifying the marine target in real time through the AIS system is: the method comprises the steps of obtaining marine targets and positioning data thereof on a sea area through an AIS system, wherein the marine targets refer to all ships which can be identified by the AIS ship automatic identification system in the sea area, and one ship registration number is used as one marine target, and the AIS system is the ship automatic identification system.
3. The method for repairing and identifying marine target images based on SAR technology as claimed in claim 1, wherein in step S102, the method for acquiring GPS positioning data of the identified marine target is: obtaining ship registration numbers of all marine targets and global positioning system data thereof from an AIS ship automatic identification system; the method comprises the steps of taking a ship registration number as a marine target, and taking GPS (global positioning system) data as GPS positioning data GLoc (X, Y), wherein X and Y respectively represent a longitude value and a latitude value.
4. The method for repairing and identifying the marine target image based on the SAR technology as claimed in claim 1, wherein in step S103, the step index is established by GPS positioning data by: acquiring GPS positioning data GLoc (X, Y) of a marine target in real time; constructing newly acquired NGL GPS positioning data GLoc (X, Y) into a newly positioned sequence RGLLs in reverse time sequence, wherein the newly positioned sequence RGLLs is [ GLoc [ ]i1(X,Y)]，i1∈[1，NGL]Wherein NGL is the length of RGLLs, and takes the value of [1,5 ]]，GLoci1(X, Y) is the i1 th GPS positioning data in RGLLs, a variable i2 is set, and the value of the initialization i2 is 1; setting an empty sequence as a step difference sequence DGLs; jumping to step A01; setting a variable with an initial value of 0The step difference index DGFlg at the current moment;
a01, obtaining longitude step difference DGX ═ GLoc when i2 < NGLi2(X,Y)(X)－GLoci2+1(X, Y) (X), wherein GLoci2(X, Y) (X) represents GLoci2Longitude of (X, Y), GLoc as welli2+1(X, Y) (X) represents GLoci2+1Longitude of (X, Y); obtaining latitude step difference DGY = GLoci2(X,Y)(Y)－GLoci2+1(X, Y) (Y), wherein GLoci2(X, Y) (Y) represents GLoci2(X, Y) latitude, GLoci2+1(X, Y) (Y) represents GLoci2+1(X, Y) latitude; forming a step difference pair DG (DGX, DGY) by the longitude step difference DGX and the latitude step difference DGY, inputting the DG (DGX, DGY) into the step difference sequence DGLs as the i2 th element of the step difference sequence DGLs, adding 1 to the value of i2, and jumping to the step A01;
when i2 is more than or equal to NGL, obtaining the step difference sequence DGLs at the current moment, wherein [ DGLs ] isi3(DGX,DGY)]，i3∈[1，NGD]Wherein i3 is the step pair sequence number, and NGD is the number of elements in the step sequence DGLs; taking the arithmetic mean of the longitude step differences of each element in the step difference sequence as a longitude step difference mean EDGX, and taking the arithmetic mean of the latitude step differences of each element in the step difference sequence as a latitude step difference mean EDGY, so as to obtain a step difference mean EDG of the current moment, wherein the step difference mean EDG comprises EDGX and EDGY; taking the standard deviation of the longitude step differences of all elements in the step difference sequence DGLs as a longitude step difference threshold DDGX, and taking the standard deviation of the latitude step differences of all elements in the step difference sequence DGLs as a latitude step difference threshold DDGY, so as to obtain a step difference threshold DDG of the current moment, wherein the step difference threshold DDG comprises the DDGX and the DDGY;
setting an interval as longitude step difference index DGFlgX, setting the interval of DGFlgX as [ EDGX-DDGX, EDGX + DDGX ], setting an interval as latitude step difference index DGFlgY, and setting the interval of DGFlgY as [ EDGY-DDGY, EDGY + DDGY ]; if the DGX value in the DG (DGX, DGY) of the step difference pair at the current moment is within the longitude step difference index DGFlgX and the DGY value is within the latitude step difference index DGFlgY, the step difference index DGFlg is 1, otherwise, the step difference index DGFlg is 0;
jumping to step A02;
and A02, ending.
5. The method for repairing and identifying the marine target image based on the SAR technology as claimed in claim 4, wherein in step S104, the method for calculating the real-time drift index according to the step index is as follows: acquiring step difference indexes DGFlg of the latest NGL moments, calculating a real-time drift index if the value of the step difference indexes DGFlg of the latest NGL moments is 1, and otherwise, recalculating the step difference indexes DGFlg after waiting for next acquisition of GPS positioning data GLoc (X, Y) of the marine target; obtaining a step difference sequence DGLs at the current moment, and calculating a longitude drift index MX:
wherein i4 is a variable, DGLs (i4) (DGX) represent the longitude step difference DGX of the i4 th element in the step difference sequence DGLs, rsX is a longitude drift sensitive coefficient, and the calculation method is as follows:
(ii) a Wherein i5 is a variable, DGXi5Represents the longitude step difference at time i 5; EDGXi5Represents the mean value of the longitude step differences at the i5 th moment; DDGXi5A longitude step difference threshold representing time i 5; the ith 5 time point represents the ith 5 time point in the latest acquired NGL time points;
calculating a latitude drifting index MY:
wherein i6 is variable, DGLs (i6) (DGY) represents the latitude step difference DGY of the i6 th element in the step difference sequence DGLs, rsY is latitude drift sensitive coefficient, and the calculation method is as follows:
(ii) a Wherein i7 is a variable, DGYi7Represents the latitude step difference at the i7 th time; EDGY (electric double-edged fine grid)i5Represents the mean value of the latitude step difference at the i7 th moment; DDGY (digital data processing)i7A latitude step difference threshold representing time i 7; the ith 7 time point represents the ith 7 time point in the latest acquired NGL time points; by longitude drift index MX and latitude driftThe vector formed by the shift index MY is used as the real-time shift index CDM (MX, MY).
6. The method for repairing and identifying marine target images based on SAR technology as claimed in claim 1, wherein in step S200, the method for acquiring target images by using SAR is: the method comprises the steps of sending and receiving microwaves through an SAR (synthetic aperture radar) with an imaging function, detecting an SAR image of a target sea area, identifying a marine target from the SAR image according to a ship target detection algorithm, and taking an image of the marine target in the SAR image as a target image; and performing geometric correction and noise reduction on the target image, and adaptively rotating the target image.
7. A marine target image restoration recognition system based on SAR technology is characterized by comprising: the processor, the memory and the computer program stored in the memory and running on the processor, when the processor executes the computer program, the steps of the method for repairing and identifying a marine target image based on SAR technology in any one of claims 1-6 are realized, and the system for repairing and identifying the marine target image based on SAR technology is run in a computing device of a desktop computer, a notebook computer, a palm computer or a cloud data center.
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