CN112835039B - Planar aperture zoned nonlinear progressive phase iterative imaging method and device - Google Patents
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Abstract
The present disclosure relates to a method and apparatus for planar aperture zoned nonlinear progressive phase iterative imaging, the method comprising: the method comprises the steps that a planar aperture three-dimensional imaging radar is moved along an elevation direction to form a synthetic aperture or real aperture radar with sampling points located on the same plane; calculating based on a stepping distance compensation factor, and analyzing a distance error; based on the regional division of the sampling points of the planar aperture radar, the distance process from any point of the observation region to the sampling points is obtained through iterative calculation of a stepping distance compensation factor, so that the three-dimensional reconstruction of the observation region is completed. The device comprises: the error analysis module and the imaging module. According to the embodiment of the invention, the three-dimensional imaging efficiency can be greatly improved by constructing the regional nonlinear progressive Doppler compensation factor to replace a global point-by-point superposition imaging mode.
Description
Technical Field
The disclosure relates to the field of radar three-dimensional imaging, in particular to a planar aperture zoned nonlinear progressive phase iterative imaging method and device.
Background
Compared with other traditional micro-change monitoring means such as GPS, the micro-change monitoring radar has the advantages of all weather, large range, high precision and the like, and is widely applied to micro-deformation detection of high and steep slopes, bridge buildings and the like. The three-dimensional imaging of the micro-change monitoring radar can realize three-dimensional resolution imaging and three-dimensional deformation information extraction of an observation area, can effectively inhibit the phenomena of overlapping and covering, top-bottom inversion and the like caused by observation geometry, and has wide application prospects in the aspects of slope landslide and artificial building monitoring.
Because the observation area is large, the existing imaging algorithm is difficult to reconstruct the three-dimensional of the large scene area; the three-dimensional backward projection algorithm can reconstruct the region of interest in three dimensions by means of point-by-point reconstruction, and has certain advantages, but because the distance course is calculated point by point, the calculated amount is high, the imaging efficiency is affected, and the real-time monitoring requirement is difficult to meet. In summary, a fast and accurate reconstruction of a large field of view region is not possible.
Disclosure of Invention
The present disclosure is intended to provide a method and apparatus for planar aperture zonal nonlinear progressive phase iterative imaging, which greatly improves three-dimensional imaging efficiency by constructing zonal nonlinear progressive doppler compensation factors instead of a global point-by-point superposition imaging mode.
According to one aspect of the present disclosure, there is provided a method of planar aperture zoned nonlinear progressive phase iterative imaging, comprising:
the method comprises the steps that a planar aperture three-dimensional imaging radar is moved along an elevation direction to form a synthetic aperture or real aperture radar with sampling points located on the same plane;
calculating based on a stepping distance compensation factor, and analyzing a distance error;
based on the regional division of the sampling points of the planar aperture radar, the distance process from any point of the observation region to the sampling points is obtained through iterative calculation of a stepping distance compensation factor, so that the three-dimensional reconstruction of the observation region is completed.
In some embodiments, wherein the step-based distance compensation factor calculation performs a distance error analysis, comprising:
obtaining an azimuth distance compensation factor;
obtaining an elevation direction distance compensation factor;
and acquiring smaller azimuth stepping distance and elevation stepping distance according to the azimuth distance compensation factor and the elevation distance compensation factor so as to reduce distance errors.
In some embodiments, the method comprises, among other things,
the obtaining the azimuth distance compensation factor comprises the following steps:
setting the number of steps of a radar sampling point along the azimuth direction and the number of steps of the radar sampling point along the elevation direction relative to a radar initial sampling point to obtain a Maclalin expression of the radar sampling point;
Obtaining an approximate distance of Maclalin based on the processing of the Maclalin expression;
obtaining an azimuth distance compensation factor based on the Maclalin approximate distance;
the step of obtaining the elevation direction distance compensation factor comprises the following steps:
setting the number of steps of a radar sampling point along the azimuth direction and the number of steps of the radar sampling point along the elevation direction relative to a radar initial sampling point to obtain a Maclalin expression of the radar sampling point;
obtaining an approximate distance of Maclalin based on the processing of the Maclalin expression;
and obtaining an elevation direction distance compensation factor based on the Maclalin approximate distance.
In some embodiments, wherein performing the distance error analysis comprises:
combining the azimuth distance compensation factor and the elevation distance compensation factor, and solving the distance course from any point of the observation area to the radar sampling point in a stepping manner based on the distance from any point of the observation area to the radar initial sampling point;
and solving the distance error generated by the distance process from any point of the observation area to the radar sampling point in a stepping way.
In some embodiments, the method of planar aperture zoned nonlinear progressive phase iterative imaging comprises:
compressing echo signals at all sampling points of the radar along the distance direction;
Dividing an imaging area into a plurality of pixel areas, wherein each pixel area is provided with a plurality of pixels;
calculating the phase of each pixel point in an imaging area by adopting a zonal stepping phase iteration method;
calculating the size of a sampling point region according to the step-by-step distance solving error, and dividing the planar synthetic aperture into a plurality of sampling point regions;
the value of each pixel point of the observation area is calculated point by point.
In some embodiments, the dividing the imaging region into a plurality of pixel regions, each pixel region having a plurality of pixels, includes:
parameter setting, including the size of each pixel and selecting initial pixel point coordinates;
calculating a distance compensation factor coefficient;
and calculating the size of the pixel areas and the number of the pixel areas.
In some embodiments, the calculating the phase of each pixel point of the imaging area by using the area stepping phase iterative method includes:
calculating an initial phase and a phase compensation factor based on the number of pixel areas, the number of pixels contained in each pixel area, the radar center frequency, the distance compensation factor coefficient and an initial value;
iteratively calculating the phase of the pixel points along the azimuth direction comprises the following steps: distance iteration, elevation iteration and pixel point area iteration.
In some embodiments, the calculating the sampling point area size according to the step-by-step distance solving error and dividing the planar synthetic aperture into a plurality of sampling point areas includes:
selecting an observation area pixel point and a radar initial sampling point;
calculating the distance course from the pixel point of the observation area to the radar initial sampling point;
calculating an azimuth distance compensation factor coefficient and an elevation distance compensation factor coefficient;
solving maxwell Lin Jinshi of the distance history;
solving an actual distance course;
and calculating the size of the sampling point region and the number of the dividing regions, and calculating the sampling point region according to the phase error limiting condition.
In some embodiments, wherein calculating the value of each pixel of the observation region point by point comprises:
and reconstructing each pixel point of the observation area point by point based on an algorithm so as to realize three-dimensional resolution imaging of the observation area.
According to one of the schemes of the present disclosure, a device for planar aperture zoning nonlinear progressive phase iterative imaging is provided, and a synthetic aperture or real aperture radar configuration with sampling points located on the same plane is formed by moving a planar aperture three-dimensional imaging radar along an elevation direction; the device comprises:
an error analysis module configured to perform a distance error analysis based on the step-wise distance compensation factor calculation;
The imaging module is configured to be used for carrying out iterative calculation on the distance course from any point of the observation area to the sampling point through a stepping distance compensation factor based on the regional division of the sampling point of the planar aperture radar so as to finish the three-dimensional reconstruction of the observation area.
According to one aspect of the present disclosure, there is provided a computer-readable storage medium having stored thereon computer-executable instructions that, when executed by a processor, implement:
according to the planar aperture zonal nonlinear progressive phase iterative imaging method.
According to the method and the device for planar aperture zoning nonlinear progressive phase iterative imaging, at least a planar aperture three-dimensional imaging radar is moved along an elevation direction to form a synthetic aperture or a real aperture radar with sampling points positioned on the same plane; calculating based on a stepping distance compensation factor, and analyzing a distance error; based on the region division of the sampling points of the planar aperture radar, the distance process from any point of the observation region to the sampling points is obtained through iterative calculation of a stepping distance compensation factor so as to finish the three-dimensional reconstruction of the observation region, so that the sampling points of the planar synthetic aperture radar can be divided into regions, and in each region, the distance from the pixel points of the observation region to the sampling points is calculated in a stepping iterative mode, so that root index operation in the process of distance calculation is reduced, and the algorithm efficiency is improved; the specific method steps for calculating the distance compensation factor are deduced in each embodiment of the disclosure, meanwhile, the distance error caused by the step-by-step distance iteration solving distance process is analyzed, and the maximum range of sampling point region division is calculated according to the phase error condition; meanwhile, the observation area is divided into areas, the pixel point phases of the observation area are solved by adopting a stepping phase iteration method, the phase compensation factors are adopted to replace the defect of solving the phases of the observation area point by point, the root index operation during phase solving is reduced, and the algorithm efficiency is further improved.
It is to be understood that both the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the disclosure, as claimed.
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In the drawings, which are not necessarily to scale, like reference numerals in different views may designate like components. Like reference numerals with letter suffixes or like reference numerals with different letter suffixes may represent different instances of similar components. The accompanying drawings generally illustrate various embodiments by way of example, and not by way of limitation, and are used in conjunction with the description and claims to explain the disclosed embodiments.
FIG. 1 is a schematic diagram of a planar aperture micro-variation monitoring radar according to an embodiment of the disclosure;
FIG. 2 is a schematic diagram of a step-wise distance solution according to an embodiment of the present disclosure;
FIG. 3 is a schematic diagram of solving a azimuthal distance compensation factor according to an embodiment of the disclosure;
FIG. 4 is a schematic diagram illustrating an elevation distance compensation factor solution according to an embodiment of the present disclosure;
FIG. 5 is a schematic diagram of an error analysis of an embodiment of the present disclosure;
FIG. 6 is a schematic view of a pixel division of an observation area according to an embodiment of the disclosure;
FIG. 7 is a phase matrix PHI of pixel points of an observation area according to an embodiment of the disclosure 3D ；
Fig. 8 is a schematic view of three-dimensional reconstruction of a pixel point of an observation area according to an embodiment of the disclosure;
FIG. 9 is a step-wise distance calculation flow chart of an embodiment of the present disclosure;
FIG. 10 is a block diagram illustrating a pixel division of an observation area according to an embodiment of the present disclosure;
FIG. 11 is a flow chart of phase calculation of a pixel point in an observation area according to an embodiment of the disclosure;
FIG. 12 is a sample point region division flow chart according to an embodiment of the present disclosure;
FIG. 13 is a flow chart of three-dimensional reconstruction of an observation region according to an embodiment of the present disclosure;
fig. 14 is a flow chart of an imaging method according to an embodiment of the present disclosure.
Detailed Description
In order to make the objects, technical solutions and advantages of the embodiments of the present disclosure more apparent, the technical solutions of the embodiments of the present disclosure will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present disclosure. It will be apparent that the described embodiments are some, but not all, of the embodiments of the present disclosure. All other embodiments, which can be made by one of ordinary skill in the art without the need for inventive faculty, are within the scope of the present disclosure, based on the described embodiments of the present disclosure.
Unless defined otherwise, technical or scientific terms used in this disclosure should be given the ordinary meaning as understood by one of ordinary skill in the art to which this disclosure belongs. The word "comprising" or "comprises", and the like, means that elements or items preceding the word are included in the element or item listed after the word and equivalents thereof, but does not exclude other elements or items.
In order to keep the following description of the embodiments of the present disclosure clear and concise, the present disclosure omits detailed description of known functions and known components.
As shown in fig. 1, the planar aperture three-dimensional imaging radar forms a synthetic aperture or real aperture radar with sampling points located on the same plane by, but not limited to, moving a horizontally placed linear array along elevation direction E. The radar can realize three-dimensional resolution of an observation areaImaging. In fig. 1, a radar sampling point P Radar (x, 0, z) lies in the XOZ plane, x representing the radar sampling point P Radar Is defined by the transverse axis of (c), z representing radar sampling point P Radar Is a vertical coordinate of (2); l (L) SynA Represents the radar azimuth direction (A) synthetic aperture length, L SynE Representing radar elevation direction (E) synthetic aperture length; Δx represents the radar azimuth (a) sampling interval and Δz represents the radar elevation (E) sampling interval. It should be noted that the radar azimuth direction (a) is the positive direction of the X-axis of the coordinate system, and the radar elevation direction (E) is the positive direction of the Z-axis of the coordinate system.
As one aspect, an embodiment of the present disclosure provides a method for planar aperture zoned nonlinear progressive phase iterative imaging, including:
the method comprises the steps that a planar aperture three-dimensional imaging radar is moved along an elevation direction to form a synthetic aperture or real aperture radar with sampling points located on the same plane;
Calculating based on a stepping distance compensation factor, and analyzing a distance error;
based on the regional division of the sampling points of the planar aperture radar, the distance process from any point of the observation region to the sampling points is obtained through iterative calculation of a stepping distance compensation factor, so that the three-dimensional reconstruction of the observation region is completed.
One of the inventive concepts of the present disclosure aims to realize region division of sampling points of a planar synthetic aperture radar, and in each region, a stepping iteration mode is adopted to calculate the distance from a pixel point of an observation region to the sampling point, so that root index operation during distance calculation is reduced, and algorithm efficiency is improved.
The present disclosure is directed to two main aspects, a step-wise distance compensation factor calculation and a distance error analysis, and a planar aperture zoned nonlinear progressive phase iterative imaging method performed on the basis of the two aspects. The subject of execution of the present disclosure is not limited as long as a device, apparatus, or particular imaging system is satisfied that enables planar aperture zoned nonlinear progressive phase iterative imaging.
In some embodiments, the step-based distance compensation factor calculation of the present disclosure, performing a distance error analysis, includes:
obtaining an azimuth distance compensation factor;
Obtaining an elevation direction distance compensation factor;
and acquiring smaller azimuth stepping distance and elevation stepping distance according to the azimuth distance compensation factor and the elevation distance compensation factor so as to reduce distance errors.
Specifically, firstly, distance compensation factors delta Azi and delta Ele of azimuth and elevation directions are calculated; then analyze the error E of the step distance calculation r A calculation method of the maximum value of the sampling point region error is provided.
As shown in fig. 2, P n (x n ,y n ,z n ) To observe any point of the area, P Radar (x, 0, z) is the sampling point of the radar; x is x n For observing the region point P n Is y n For observing the region point P n Is z n For observing the region point P n Is a vertical coordinate of (2); x is the radar sampling point P Radar Z is the sampling point P Radar Is a vertical coordinate of (c).
Radar slave x=x 0 、z＝z 0 I.e. the start sampling point P Radar-Start (x 0 ,0,z 0 ) The position is started, sampling is carried out along azimuth and elevation directions at intervals, and the azimuth and elevation directions are respectively at intervals of deltax and deltaz; then the radar sampling point coordinates P Radar In (x, 0, z), x, z can be expressed as:
x＝x 0 +n x ·Δx (1)
z＝z 0 +n z ·Δz (2)
wherein n is x Representing radar sampling point P Radar Relative to the radar start sampling point P Radar-Start Number of steps in azimuth, n x ＝0,1,…,(N x -1)；n z Representing radar sampling point P Radar Relative to the radar start sampling point P Radar-Start Number of steps along height Cheng Xiang, n z ＝0,1,…,(N z -1)；N x Represents the radar azimuth sampling point number, N z Representing the number of radar elevation direction sampling points; arbitraryRadar sampling point P Radar Represented as
Solving any point P of the observation area in a stepping mode n To radar sampling pointDistance compensation factors delta Azi and delta Ele of the azimuth direction and the elevation direction are calculated respectively; and further solving the distance course step by a distance compensation factor.
In some embodiments, the deriving the azimuthal distance compensation factor of the present disclosure comprises:
setting the number of steps of a radar sampling point along the azimuth direction and the number of steps of the radar sampling point along the elevation direction relative to a radar initial sampling point to obtain a Maclalin expression of the radar sampling point;
obtaining an approximate distance of Maclalin based on the processing of the Maclalin expression;
obtaining an azimuth distance compensation factor based on the Maclalin approximate distance;
the step of obtaining the elevation direction distance compensation factor comprises the following steps:
setting the number of steps of a radar sampling point along the azimuth direction and the number of steps of the radar sampling point along the elevation direction relative to a radar initial sampling point to obtain a Maclalin expression of the radar sampling point;
obtaining an approximate distance of Maclalin based on the processing of the Maclalin expression;
and obtaining an elevation direction distance compensation factor based on the Maclalin approximate distance.
Regarding the azimuthal distance compensation factor Δ Azi:
FIG. 3 shows an observation area at an arbitrary point P n (x n ,y n ,z n ) To the radar start sampling point P Radar-Start (x 0 ,0,z 0 ) The distance of (2) is:
when calculating azimuth distance compensation factor, radar sampling pointRelative to the radar start sampling point P Radar-Start Number of steps in azimuth is n x The step number along the elevation direction is 0; the coordinates of the sampling points are expressed asWherein n is x ＝0,1,…,(N x -1). Any point P of the observation area n (x n ,y n ,z n ) To radar sampling point->The distance of (2) is:
wherein x is n For observing the region point P n Is y n For observing the region point P n Is z n For observing the region point P n Is a vertical coordinate of (2); x is x 0 For the radar start sampling point P Radar-Start Is z 0 For the radar start sampling point P Radar-Start Is a vertical coordinate of (2); n is n x For radar sampling pointsRelative to the initial sampling point P Radar-Start Number of steps in azimuth; Δx is the radar azimuth sampling interval.
Substituting formula (3) into formula (4) to obtain:
formula (5) is represented by n x Taylor expansion at Δx=0, resulting in its majulin (Maclaurin) expression:
where o is called Peano (Peano) remainder.
The peano remainder o in equation (6) was ignored, and the distance calculation error due to the omission of the peano remainder was analyzed.
Ignoring the peaunox remainder o (x) in equation (6), any point P in the observation region can be obtained n (x n ,y n ,z n ) To radar sampling pointThe majuline approximation distance is:
wherein,,
the formula (7) is opposite to n x The derivation is carried out, and the obtained azimuth distance compensation factors are as follows:
ΔAzi(n x )＝2A x ·Δx 2 ·n x +B x ·Δx (10)
wherein x is n For observing the region point P n Is y n For observing the region point P n Is z n For observing the region point P n Is a vertical coordinate of (2); x is x 0 For the radar start sampling point P Radar-Start Is z 0 For the radar start sampling point P Radar-Start Is a vertical coordinate of (2); n is n x For radar sampling pointsNumber of steps in azimuth; Δx is the radar azimuth sampling interval.For any point P of the observation area n (x n ,y n ,z n ) To radar sampling point->Is a Maclalin approximation distance; />For any point P of the observation area n (x n ,y n ,z n ) To the radar start sampling point P Radar-Start (x 0 ,0,z 0 ) Is a distance of (2); a is that x 、B x Is the azimuth distance compensation factor coefficient.
With respect to the elevation distance compensation factor deltaele
As shown in fig. 4, the observation area is at an arbitrary point P n (x n ,y n ,z n ) To the radar start sampling point P Radar-Start (x 0 ,0,z 0 ) The distance of (2) is:
when calculating elevation direction distance compensation factor, radar sampling pointRelative to the radar start sampling point P Radar-Start The number of steps in the azimuth direction is 0, and the number of steps in the elevation direction is n z The method comprises the steps of carrying out a first treatment on the surface of the The coordinates of the sampling points are expressed asWherein n is z ＝0,1,…,(N z -1). Any point P of the observation area n (x n ,y n ,z n ) To radar sampling point->The distance of (2) is:
wherein x is n For observing the region point P n Is y n For observing the region point P n Is z n For observing the region point P n Is a vertical coordinate of (2); x is x 0 For the radar start sampling point P Radar-Start Is z 0 For the radar start sampling point P Radar-Start Is a vertical coordinate of (2); n is n z For radar sampling pointsRelative to the initial sampling point P Radar-Start Number of steps along height Cheng Xiang; Δz is the radar elevation-wise sampling interval.
Substituting formula (11) into formula (12) to obtain:
formula (13) is n z Taylor expansion at Δz=0, resulting in its majulin (Maclaurin) formula expressed as:
where o is called Peano (Peano) remainder.
The peano remainder o in equation (14) was ignored and the distance calculation error due to the omission of the peano remainder was analyzed.
Ignoring the peaunox remainder o (x) in equation (14), any point P in the observation region can be obtained n (x n ,y n ,z n ) To the sampling pointThe majuline approximation distance is:
wherein,,
the formula (15) is opposite to n z Deriving to obtain the elevation direction distance compensation factors as follows:
ΔEle(n z )＝2A z ·Δz 2 ·n z +B z ·Δz (18)
wherein x is n For observing the region point P n Is y n For observing the region point P n Is z n For observing the region point P n Is a vertical coordinate of (2); x is x 0 For the radar start sampling point P Radar-Start Is z 0 For the radar start sampling point P Radar-Start Is a vertical coordinate of (2); n is n z For radar sampling pointsRelative to the initial sampling point P Radar-Start Number of steps along height Cheng Xiang; Δz is the radar elevation-wise sampling interval. / >For any point P of the observation area n (x n ,y n ,z n ) To radar sampling pointIs a Maclalin approximation distance; />For any point P of the observation area n (x n ,y n ,z n ) To the radar start sampling point P Radar-Start (x 0 ,0,z 0 ) Is a distance of (2); a is that z 、B z Is an elevation direction distance compensation factor coefficient.
The flow chart of the algorithm for stepwise calculating the distance history by adopting the azimuth and elevation distance compensation factors is shown in fig. 9, and any point P in the observation area is observed n (x n ,y n ,z n ) Radar start sampling point P Radar-Start (x 0 ,0,z 0 ) The radar azimuth and elevation sampling intervals delta x and delta z are respectively N in the azimuth and elevation of the sampling points of the region SubAzi 、N SubEle 。
In some implementations, the performing distance error analysis of the present disclosure includes:
combining the azimuth distance compensation factor and the elevation distance compensation factor, and solving the distance course from any point of the observation area to the radar sampling point in a stepping manner based on the distance from any point of the observation area to the radar initial sampling point;
and solving the distance error generated by the distance process from any point of the observation area to the radar sampling point in a stepping way.
Specifically, in the step-wise distance calculation process, the distance compensation factor Δ Azi (n x )、ΔEle(n z ) Derived from equations (7) and (15), respectively, after ignoring the peano remainder o (x), i.e. the remaining finite term, the azimuth step distance (n x Δx) and elevation-to-step distance (n z Δz) is smaller, the smaller the obtained distance error is.
The following analysis shows the distance error of the step-wise distance calculation after ignoring the peano remainder o (x) as shown in equations (7), (15).
As shown in fig. 5, P n (x n ,y n ,z n ) To observe any point of the area, P Radar-Start (x 0 ,0,z 0 ) For the radar start sampling point,for the radar to step n along azimuth and elevation directions respectively x 、n z Sub-sampling points.
Any point P of the observation area n (x n ,y n ,z n ) To the radar start sampling point P Radar-Start (x 0 ,0,z 0 ) Is expressed as the distance of (2)Any point P of the observation area n (x n ,y n ,z n ) To radar sampling point->Is expressed as the actual distance history ofWhile step-wise solving for any point P in the observation area n (x n ,y n ,z n ) To radar sampling point->The distance history of (2) is:
wherein A is x 、B x For the azimuth distance compensation factor coefficient, A z 、B z Is an elevation direction distance compensation factor coefficient; n is n x 、n z Respectively radar sampling pointsRelative to the initial sampling point P Radar-Start The number of steps in azimuth and elevation; Δx and Δz are radar azimuth and elevation sampling intervals, respectively.
Solving any point P of an observation area by adopting stepping n (x n ,y n ,z n ) To radar sampling pointThe distance error Er generated by the distance history of (2) is expressed as:
wherein,,for any point P of the observation area n To the radar start sampling point P Radar-Start Distance history of (2);for any point P of the observation area n To the sampling point->Is a real distance history of (1); n is n x 、n z Radar sampling points +.>Relative to the initial sampling point P Radar-Start The number of steps in azimuth and elevation; Δx and Δz are sampling intervals in the radar azimuth and elevation directions, respectively.
The geometric relationship is as follows:
wherein,,for any point P of the observation area n To the radar start sampling point P Radar-Start And sample point->Is a distance history of (2); />For the radar start sampling point P Radar-Start To the sampling point->Is a distance of (3).
To sum up, when observing the region point P n Is positioned at a radar initial sampling point P Radar-Start And sampling pointWhen the extension line of the distance process is extended, the error Er of the step-by-step solving distance process is maximum.
In some embodiments, referring to fig. 14, a planar aperture zoned nonlinear progressive phase iteration method of the present disclosure includes:
compressing echo signals at all sampling points of the radar along the distance direction;
dividing an imaging area into a plurality of pixel areas, wherein each pixel area is provided with a plurality of pixels;
calculating the phase of each pixel point in an imaging area by adopting a zonal stepping phase iteration method;
calculating the size of a sampling point region according to the step-by-step distance solving error, and dividing the planar synthetic aperture into a plurality of sampling point regions;
the value of each pixel point of the observation area is calculated point by point.
According to the embodiment of the disclosure, the sampling points of the planar aperture radar are divided into areas, so that the distance process from any point of an observation area to the sampling points can be solved iteratively through the step compensation factors, and root index operation is reduced.
As shown in fig. 2, the radar is from x=x 0 、z＝z 0 I.e. point P Radar-Start (x 0 ,0,z 0 ) The position is started, sampling is carried out along azimuth and elevation directions at intervals, and the azimuth and elevation directions are respectively at intervals of deltax and deltaz; sampling pointIs radar along azimuth and elevationRespectively step in the direction of travel n x 、n z Sub-sampling points. Radar at sampling point +.>The echo equation is expressed as:
f＝{f min ,…,f max } (23)
wherein f is the step frequency of the radar echo, f min For the lowest frequency of radar stepping, f max For the highest frequency of radar stepping, C is the speed of light,for radar sampling points +.>Distance to the imaging region pixel point.
Specifically, the imaging method of the present embodiment includes:
step S1: distance compression, which compresses echo signals at each sampling point of the radar along the distance direction, can adopt an inverse Fourier transform (IFFT) mode, and the distance compressed signals are
Wherein f c For the center frequency of the radar echo, one can take (f min +f max )/2；
Step S2: dividing the pixel points of the observation area and dividing the imaging area M x ×M y ×M z The pixels are divided into K pixel areas, and each pixel area comprises M pixels Sub ×M Sub ×M Sub The method comprises the steps of carrying out a first treatment on the surface of the In the kth pixel region, the pixel coordinates are expressed asWherein m is x ＝1,2,…,M Sub 、m y ＝1,2,…,M Sub 、m z ＝1,2,…,M Sub ；M x 、M y 、M z The number of pixels in the azimuth direction, the distance direction and the elevation direction of the observation area are respectively represented by +.>Is pixel dot +.>Is defined by the transverse axis of (c),is pixel dot +.>Ordinate of >Is pixel dot +.>Is a vertical coordinate of (2);
step S3: calculating the phase of each pixel point, and calculating the phase PHI of each pixel point in an imaging area by adopting a stepped phase iteration method in a partitioned mode 3D ；
Step S4: dividing a plane sampling point region, calculating the size of the sampling point region according to a stepping distance solving error Er, and dividing a plane synthetic aperture into I sampling point regions;
step S5: and (3) carrying out three-dimensional reconstruction on the observation area, calculating the value of each pixel point of the observation area point by point, and completing the three-dimensional reconstruction on the observation area.
Parameter settings in various embodiments of the present disclosure are for example: minimum frequency f of radar stepping min At 77GHz, the highest frequency f max 77.25GHz, the radar bandwidth B is 250M, and the frequency point gamma is 5001; the coordinate of the radar initial sampling point is P Radar-Start (-0.8, 0, -0.8) sampling interval of radar in azimuth and elevationΔx and Δz are both 0.008m, and the number of sampling points N in azimuth and elevation directions x 、N z All are 201, and the radar azimuth direction and pitching direction synthetic aperture length L SynA 、L SynE Are all 1.6m; observation area pixel pointThe starting abscissa x of (2) 1 -50m, termination abscissa +.>50m, observation area pixel point +.>Is the initial ordinate y of (2) 1 950m, termination ordinate +.>1050m, observation region pixel point +.>The initial vertical coordinate z of (2) 1 -50m, termination vertical +.>50m.
Regarding observation area pixel division: the division of an imaging region into a plurality of pixel regions, each pixel region having a plurality of pixels, includes:
parameter setting, including the size of each pixel and selecting initial pixel point coordinates;
calculating a distance compensation factor coefficient;
and calculating the size of the pixel areas and the number of the pixel areas.
Specifically, in step S2, M in the imaging region x ×M y ×M z The pixels are divided into K pixel areas, and each pixel area comprises M pixels Sub ×M Sub ×M Sub The method flow chart is shown in FIG. 10, the imaging area pixel point division is shown in FIG. 6, the steps are as followsThe following are provided:
step S21: parameter setting, each pixel size is delta m x ×Δm y ×Δm z Selecting the initial pixel point coordinate as m 111 (x 1 ,y 1 ,z 1 )；
Step S22: calculating a distance compensation factor coefficient, wherein the azimuth distance compensation factor coefficient is as follows:
/>
the distance-to-distance compensation factor coefficients are:
the elevation direction distance compensation factor coefficient is:
step S23: calculating the pixel point area size M Sub And the number of areas K, the progressive phase error is:
let E PHI Less than or equal to pi/4, obtain M Sub The number K of the divided pixel point areas is as follows:
regarding the calculation of each pixel phase: the disclosed method for calculating the phase of each pixel point in an imaging area by adopting a stepped phase iteration method in a divided area comprises the following steps:
Calculating an initial phase and a phase compensation factor based on the number of pixel areas, the number of pixels contained in each pixel area, the radar center frequency, the distance compensation factor coefficient and an initial value;
iterating the phase of each pixel, including repeating: distance iteration, elevation iteration and pixel point area iteration.
Specifically, in step S3, a step-by-step phase iterative method is used to calculate the phase of each pixel, and the flowchart is shown in fig. 11. The method comprises the following specific steps:
step S31: parameter setting, namely the number K of pixel areas, wherein each pixel area comprises the number M of pixel areas Sub ×M Sub ×M Sub Radar center frequency f c Distance compensation factor coefficient a x 、b x 、a y 、b y 、a z 、b z Initial value m x ＝1、m y ＝1、m z ＝1、k＝1；
Step S32: calculating initial phase and phase compensation factor, wherein the initial pixel point coordinate of the kth pixel point area is m k-111 (x k-1 ,y k-1 ,z k-1 ) The phase PHI of the initial pixel of the kth pixel region k-111 Is that
The pixel azimuth phase compensation factor is:
/>
the pixel point distance phase compensation factor is:
the pixel elevation direction phase compensation factor is:
step S33: iterative calculation of phase, m of pixel points along azimuth direction x ＝m x +1, if m x ≤M Sub The phase of the azimuth pixel point is calculated iteratively:
otherwise, step S34 is performed;
Step S34: distance direction iteration, let m x ＝1，m y ＝m y +1, if m y ≤M Sub And (3) calculating:
and repeating the step S33, otherwise, executing the step S35;
step S35: iteration of elevation direction, let m y ＝1，m z ＝m z +1, if m z ≤M Sub And (3) calculating:
repeating steps S33 and S44, otherwise, executing step S36;
step S36: iterating pixel point areas to make m z If K is equal to or less than K, repeating steps S33, S34 and S35, if not, ending the routine.
At this time, the phase PHI of each pixel point of the three-dimensional observation area is obtained 3D As shown in fig. 7.
Area division with respect to planar sampling points: the disclosed method for calculating the size of sampling point areas according to step-by-step distance solving errors and dividing a planar synthetic aperture into a plurality of sampling point areas comprises the following steps:
selecting an observation area pixel point and a radar initial sampling point;
calculating the distance course from the pixel point of the observation area to the radar initial sampling point;
calculating an azimuth distance compensation factor coefficient and an elevation distance compensation factor coefficient;
solving maxwell Lin Jinshi of the distance history;
solving an actual distance course;
and calculating the size of the sampling point region and the number of the dividing regions, and calculating the sampling point region according to the phase error limiting condition.
From the first partial step-wise distance error analysis, when observing the region point P n Is positioned at a radar initial sampling point P Radar-Start And sampling pointSince the error Er of the step-wise solving distance history is the largest when the extension line of (a) is extended, the maximum sampling point region in which the planar synthetic aperture can be divided is calculated based on the phase constraint condition when the error is the largest.
For the convenience of calculation, sampling point P is started from radar when sampling point region is divided Radar-Start (x 0 ,0,z 0 ) Initially, the number N of azimuth sampling points is selected SubAzi And elevation direction sampling point number N SubEle The same sampling point area; and selecting the pixel point of the observation areaThe partitionable maximum sampling point area is calculated, and the flowchart is shown in fig. 12. The specific steps are as follows:
step S41: selecting pixel points of an observation areaWith the radar start sampling point P Radar-Start (x 0 ,0,z 0 ) Radar sampling point coordinates->/>
Step S42: calculating pixel points of observation areaTo the radar start sampling point P Radar-Start (x 0 ,0,z 0 ) I.e. P in equation (3) n (x n ,y n ,z n ) Replaced by->Expressed as:
wherein x is 0 For the radar start sampling point P Radar-Start Is z 0 For the radar start sampling point P Radar-Start Is a vertical coordinate of (2);for observation area pixel->Is y 1 For observation area pixel->Ordinate of>For observation area pixel->Is a vertical coordinate of (c).
Step S43: calculating an azimuth distance compensation factor coefficient A x 、B x P in formula (8) and formula (9) n (x n ,y n ,z n ) Replaced byCan be written separately as:
step S44: calculating an elevation distance compensation factor coefficient A z 、B z P in formula (16) and formula (17) n (x n ,y n ,z n ) Replaced byCan be written separately as:
wherein A is x 、B x 、A z 、B z As the distance compensation factor coefficient, x 0 For the radar start sampling point P Radar-Start Is z 0 For the radar start sampling point P Radar-Start Is a vertical coordinate of (2);for observation area pixel->Is y 1 For observation area pixel->Ordinate of>For observation area pixel->Is a vertical coordinate of (c).
Step S45: maxwell Lin Jinshi for solving the distance history is obtained by adding P in formula (19) n (x n ,y n ,z n ) Replaced byResolvable region pixel>To radar sampling point->The distance history of (2) is:
wherein n is x 、n z Respectively radar sampling pointsRelative to the initial sampling point P Radar-Start The step times along the azimuth direction and the elevation direction, delta x and delta z are respectively the radar azimuth direction and the elevation direction sampling intervals; a is that x 、B x For the azimuth distance compensation factor coefficient, A z 、B z Is an elevation direction distance compensation factor coefficient.
Step S46: solving for realityInterval course, pixel pointTo radar sampling point->The actual distance of (2) is:
/>
step S47: calculating the size of the sampling point region and the number of the divided regions, and calculating the sampling point region according to the phase error limiting condition, namely
Wherein f c For the center frequency of the radar echo, To solve pixel point step by stepTo radar sampling point->Distance history of>Is a pixel pointTo radar sampling point->Is the actual distance of (3); bringing formula (45) and formula (46) into formula (47), when n x ＝n z When n is calculated x Has a maximum value of N Sub The method comprises the steps of carrying out a first treatment on the surface of the Thus, the radar sampling points are divided into edgesOrientation I Azi ＝N x /N Sub Areas along the elevation direction I Ele ＝N z /N Sub The number of the areas is as follows:
I＝I Azi ·I Ele (48)
the starting point coordinate of the ith sampling point area is P i-Radar-Start (x i-0 ,0,z i-0 )，i＝1,2,…,I。
Three-dimensional reconstruction of the observation region: the point-by-point calculation of the value of each pixel point of the observation area of the present disclosure includes:
and reconstructing each pixel point of the observation area point by point based on an algorithm so as to realize three-dimensional resolution imaging of the observation area.
Specifically, in step S5, as shown in fig. 8, the algorithm performs point-by-point reconstruction on each pixel point of the observation area to implement three-dimensional resolution imaging of the observation area, and the flowchart is shown in fig. 13. The method comprises the following steps:
step S501, parameter setting, radar echo distance compressed signal Sr and number M of pixel points in observation area x ×M y ×M z The number I of radar sampling point areas and the size N of each sampling point area Sub ×N Sub I-th sampling point region radar sampling pointRadar azimuth sampling interval deltax, radar elevation sampling interval deltaz, pixel point phase PHI 3D The number Q of pixel points of the observation area is equal to the initial value q=1, i=1 and n x ＝0，n z ＝0；
Step S502: calculating the initial distance and distance compensation factor of the ith sampling point area and the coordinate of the qth pixel pointThe starting point coordinate of the ith sampling point area is P i-Radar-00 (x i-o ,0,z i-0 ) Calculating a pixel point m according to formula (3) q To sampling point P i-Radar-00 Is>Then respectively calculating compensation factor coefficient A according to (8), (9), (16) and (17) i-x 、B i-x 、A i-z 、B i-z The method comprises the steps of carrying out a first treatment on the surface of the Further, a distance compensation factor Delta Azi is calculated from the components (10), (18) i (n x )、ΔEle i (n z )；
Step S503: iterative calculation of the q-th pixel point m q Distance history to the ith sampling point region;
step S5031: iteratively calculating the distance history of azimuth sampling points, n x ＝n x +1, if n x ＜N Sub Calculate the q-th pixel point m q To the sampling pointThe distance history of (2) is:
otherwise, step S5032 is entered;
step S5032: iterating along the elevation direction to let n x ＝0，n z ＝n z +1, if n z ＜N Sub Calculation of
And repeats step S5031; otherwise n z =0, step S504 is performed;
step S504: iterating the sampling point region, wherein the sampling point region number i=i+1, repeating the steps S502 to S503 if I is less than or equal to I, otherwise, entering the step S505, and obtaining the q-th pixel point m at the moment q Distance history to all radar sampling points;
wherein N is x 、N z The radar azimuth and elevation sampling points are respectively represented;
step S505: calculating pixel pointsThe peak position in the compressed signal is at each sample point distance,
Wherein B is the radar signal bandwidth, in this example (f) max -f min )，f min To step the lowest frequency, f max To step the highest frequency τ q Is N z ×N x Is a matrix of (a);
step S506: calculating the sampling points in pixelsThe phase at which the phase is at is,
wherein f c Is the radar center frequency, in this example denoted (f) max -f min )/2，φ q Is N z ×N x Is a matrix of (a);
step S507: taking out the corresponding peak value of the compressed signal from each sampling point according to the peak frequency point position of the compressed signal from each sampling point calculated in the formula (52),
wherein r is q Represents the q-th pixel point m q Range history to all radar sampling points, sr q Is N z ×N x Is a matrix of (a);
step S508: calculating pixel pointsThe values of (2) are:
m q ＝∑Sr q .*exp{jφ q } (55)
wherein "..x" represents multiplication of matrix element corresponding positions and "Σ" represents addition of matrix elements;
step S509: observing regional pixel iteration, wherein the regional pixel number q=q+1, and if q is less than or equal to M x ×M y ×M z Step S502 to step S508 are repeated, i=1, otherwise, step S510 is performed, and the values of all the pixel points in the area are obtained as follows:
m＝{m q } (56)
wherein m is q Representing the value of the q-th pixel point of the observation area, M is M x ×M y ×M z Is a three-dimensional matrix of (2);
step S510: reconstructing the region, namely combining the observed region pixel point value m with the observed region pixel point phase PHI 3D Corresponding multiplication, the reconstruction of the pixel of the observation area is completed,
m complex ＝m.*exp{-j·PHI 3D } (57)
Wherein m is the value of the pixel point of the observation area, PHI 3D For the observation area pixel phase, "..x" represents the multiplication of matrix corresponding elements.
As one of the schemes of the present disclosure, the present disclosure also provides a device for planar aperture zoning nonlinear progressive phase iterative imaging, which is based on moving a planar aperture three-dimensional imaging radar along an elevation direction to form a synthetic aperture or real aperture radar configuration with sampling points located on the same plane; the device comprises:
an error analysis module configured to perform a distance error analysis based on the step-wise distance compensation factor calculation;
the imaging module is configured to be used for carrying out iterative calculation on the distance course from any point of the observation area to the sampling point through a stepping distance compensation factor based on the regional division of the sampling point of the planar aperture radar so as to finish the three-dimensional reconstruction of the observation area.
In combination with the foregoing examples, in some implementations, the error analysis module of the present disclosure may be further configured to:
obtaining an azimuth distance compensation factor;
obtaining an elevation direction distance compensation factor;
and acquiring smaller azimuth stepping distance and elevation stepping distance according to the azimuth distance compensation factor and the elevation distance compensation factor so as to reduce distance errors.
In combination with the foregoing examples, in some implementations, the error analysis module of the present disclosure may be further configured to:
setting the number of steps of a radar sampling point along the azimuth direction and the number of steps of the radar sampling point along the elevation direction relative to a radar initial sampling point to obtain a Maclalin expression of the radar sampling point;
obtaining an approximate distance of Maclalin based on the processing of the Maclalin expression;
obtaining an azimuth distance compensation factor based on the Maclalin approximate distance;
setting the number of steps of a radar sampling point along the azimuth direction and the number of steps of the radar sampling point along the elevation direction relative to a radar initial sampling point to obtain a Maclalin expression of the radar sampling point;
obtaining an approximate distance of Maclalin based on the processing of the Maclalin expression;
and obtaining an elevation direction distance compensation factor based on the Maclalin approximate distance.
In combination with the foregoing examples, in some implementations, the error analysis module of the present disclosure may be further configured to:
combining the azimuth distance compensation factor and the elevation distance compensation factor, and solving the distance course from any point of the observation area to the radar sampling point in a stepping manner based on the distance from any point of the observation area to the radar initial sampling point;
and solving the distance error generated by the distance process from any point of the observation area to the radar sampling point in a stepping way.
In combination with the foregoing examples, in some implementations, the imaging module of the present disclosure may be further configured to:
compressing echo signals at all sampling points of the radar along the distance direction;
dividing the imaging region into a plurality of pixel regions, each pixel region having a plurality of pixels, comprising: parameter setting, including the size of each pixel and selecting initial pixel point coordinates; calculating a distance compensation factor coefficient; calculating the size of the pixel areas and the number of the pixel areas;
the method for calculating the phase of each pixel point in an imaging area by adopting a zonal stepping phase iterative method comprises the following steps: calculating an initial phase and a phase compensation factor based on the number of pixel areas, the number of pixels contained in each pixel area, the radar center frequency, the distance compensation factor coefficient and an initial value; iteratively calculating the phase of the pixel points along the azimuth direction comprises the following steps: distance iteration, elevation iteration and pixel point area iteration;
calculating the size of a sampling point area according to the step-by-step distance solving error, and dividing the planar synthetic aperture into a plurality of sampling point areas, wherein the method comprises the following steps: selecting an observation area pixel point and a radar initial sampling point; calculating the distance course from the pixel point of the observation area to the radar initial sampling point; calculating an azimuth distance compensation factor coefficient and an elevation distance compensation factor coefficient; solving maxwell Lin Jinshi of the distance history; solving an actual distance course; calculating the size of the sampling point region and the number of the divided regions, and calculating the sampling point region according to the phase error limiting condition;
Calculating the value of each pixel point of the observation area point by point comprises the following steps: and reconstructing each pixel point of the observation area point by point based on an algorithm so as to realize three-dimensional resolution imaging of the observation area.
Specifically, one of the inventive concepts of the present disclosure aims at forming a synthetic aperture or real aperture radar with sampling points located on the same plane by moving at least a planar aperture three-dimensional imaging radar in an elevation direction; calculating based on a stepping distance compensation factor, and analyzing a distance error; based on the region division of the sampling points of the planar aperture radar, the distance process from any point of the observation region to the sampling points is obtained through iterative calculation of a stepping distance compensation factor so as to finish the three-dimensional reconstruction of the observation region, so that the sampling points of the planar synthetic aperture radar can be divided into regions, and in each region, the distance from the pixel points of the observation region to the sampling points is calculated in a stepping iterative mode, so that root index operation in the process of distance calculation is reduced, and the algorithm efficiency is improved; the specific method steps for calculating the distance compensation factor are deduced in each embodiment of the disclosure, meanwhile, the distance error caused by the step-by-step distance iteration solving distance process is analyzed, and the maximum range of sampling point region division is calculated according to the phase error condition; meanwhile, the observation area is divided into areas, the pixel point phases of the observation area are solved by adopting a stepping phase iteration method, the phase compensation factors are adopted to replace the defect of solving the phases of the observation area point by point, the root index operation during phase solving is reduced, and the algorithm efficiency is further improved.
As one aspect of the disclosure, the disclosure further provides a computer-readable storage medium having stored thereon computer-executable instructions that, when executed by a processor, implement a method for planar aperture zonal nonlinear progressive phase iterative imaging according to the above, at least comprising:
the method comprises the steps that a planar aperture three-dimensional imaging radar is moved along an elevation direction to form a synthetic aperture or real aperture radar with sampling points located on the same plane;
calculating based on a stepping distance compensation factor, and analyzing a distance error;
based on the regional division of the sampling points of the planar aperture radar, the distance process from any point of the observation region to the sampling points is obtained through iterative calculation of a stepping distance compensation factor, so that the three-dimensional reconstruction of the observation region is completed.
In some embodiments, the executing computer-executable instructions processor can be a processing device including more than one general purpose processing device, such as a microprocessor, central Processing Unit (CPU), graphics Processing Unit (GPU), or the like. More specifically, the processor may be a Complex Instruction Set Computing (CISC) microprocessor, a Reduced Instruction Set Computing (RISC) microprocessor, a Very Long Instruction Word (VLIW) microprocessor, a processor running other instruction sets, or a processor running a combination of instruction sets. The processor may also be one or more special purpose processing devices such as an Application Specific Integrated Circuit (ASIC), a Field Programmable Gate Array (FPGA), a Digital Signal Processor (DSP), a system on a chip (SoC), or the like.
In some embodiments, the computer readable storage medium may be memory, such as read-only memory (ROM), random-access memory (RAM), phase-change random-access memory (PRAM), static random-access memory (SRAM), dynamic random-access memory (DRAM), electrically erasable programmable read-only memory (EEPROM), other types of random-access memory (RAM), flash memory disk or other forms of flash memory, cache, registers, static memory, compact disk read-only memory (CD-ROM), digital Versatile Disk (DVD) or other optical storage, magnetic cassettes or other magnetic storage devices, or any other possible non-transitory medium which can be used to store information or instructions that can be accessed by a computer device, and the like.
In some embodiments, computer-executable instructions may be implemented as a plurality of program modules which collectively implement a method of planar aperture zoned nonlinear progressive phase iterative imaging in accordance with any of the present disclosure.
The present disclosure describes various operations or functions that may be implemented or defined as software code or instructions. The display unit may be implemented as software code or instruction modules stored on a memory that when executed by a processor may implement the corresponding steps and methods.
Such content may be source code or differential code ("delta" or "patch" code) that may be executed directly ("object" or "executable" form). The software implementations of the embodiments described herein may be provided by an article of manufacture having code or instructions stored thereon or by a method of operating a communication interface to transmit data over the communication interface. The machine or computer-readable storage medium may cause a machine to perform the described functions or operations and includes any mechanism for storing information in a form accessible by the machine (e.g., computing display device, electronic system, etc.), such as recordable/non-recordable media (e.g., read Only Memory (ROM), random Access Memory (RAM), magnetic disk storage media, optical storage media, flash memory display device, etc.). The communication interface includes any mechanism for interfacing with any of a hard-wired, wireless, optical, etc. media to communicate with other display devices, such as a memory bus interface, a processor bus interface, an internet connection, a disk controller, etc. The communication interface may be configured by providing configuration parameters and/or sending signals to prepare the communication interface to provide data signals describing the software content. The communication interface may be accessed by sending one or more commands or signals to the communication interface.
The computer-executable instructions of embodiments of the present disclosure may be organized into one or more computer-executable components or modules. Aspects of the disclosure may be implemented with any number and combination of such components or modules. For example, aspects of the present disclosure are not limited to the specific computer-executable instructions or the specific components or modules illustrated in the figures and described herein. Other embodiments may include different computer-executable instructions or components having more or less functionality than illustrated and described herein.
The above description is intended to be illustrative and not restrictive. For example, the above-described examples (or one or more aspects thereof) may be used in combination with each other. For example, other embodiments may be used by those of ordinary skill in the art upon reading the above description. In addition, in the above detailed description, various features may be grouped together to streamline the disclosure. This is not to be interpreted as an intention that the disclosed features not being claimed are essential to any claim. Rather, the disclosed subject matter may include less than all of the features of a particular disclosed embodiment. Thus, the following claims are hereby incorporated into the detailed description as examples or embodiments, with each claim standing on its own as a separate embodiment, and it is contemplated that these embodiments may be combined with one another in various combinations or permutations. The scope of the disclosure should be determined with reference to the appended claims, along with the full scope of equivalents to which such claims are entitled.
The above embodiments are merely exemplary embodiments of the present disclosure, which are not intended to limit the present disclosure, the scope of which is defined by the claims. Various modifications and equivalent arrangements of parts may be made by those skilled in the art, which modifications and equivalents are intended to be within the spirit and scope of the present disclosure.
Claims (7)
1. The planar aperture zonal nonlinear progressive phase iterative imaging method comprises the following steps:
the method comprises the steps that a planar aperture three-dimensional imaging radar is moved along an elevation direction to form a synthetic aperture or real aperture radar with sampling points located on the same plane;
based on the step-by-step distance compensation factor calculation, the distance error analysis is performed, specifically including:
obtaining an azimuth distance compensation factor, wherein the number of steps of a radar sampling point along the azimuth direction and the number of steps of the radar sampling point along the elevation direction relative to a radar initial sampling point are set, and a Maclalin expression of the radar sampling point is obtained; obtaining an approximate distance of Maclalin based on the processing of the Maclalin expression; obtaining an azimuth distance compensation factor based on the Maclalin approximate distance;
obtaining an elevation distance compensation factor, wherein the number of steps of a radar sampling point relative to a radar initial sampling point along the azimuth direction and the number of steps along the elevation direction are set, and a Maclalin expression of the radar sampling point is obtained; obtaining an approximate distance of Maclalin based on the processing of the Maclalin expression; obtaining an elevation direction distance compensation factor based on the Maclalin approximate distance;
Acquiring smaller azimuth stepping distance and elevation stepping distance according to the azimuth distance compensation factor and the elevation distance compensation factor so as to reduce distance errors;
combining the azimuth distance compensation factor and the elevation distance compensation factor, and solving the distance course from any point of the observation area to the radar sampling point in a stepping manner based on the distance from any point of the observation area to the radar initial sampling point; step-by-step solving a distance error generated by the distance process from any point of the observation area to the radar sampling point;
based on the regional division of the sampling points of the planar aperture radar, the distance process from any point of the observation region to the sampling points is obtained through iterative calculation of a stepping distance compensation factor, so that the three-dimensional reconstruction of the observation region is completed.
2. The method according to claim 1, wherein the area division based on the sampling points of the planar aperture radar, so that the distance process from any point of the observation area to the sampling points is obtained by iterative calculation of a step-type distance compensation factor, comprises:
compressing echo signals at all sampling points of the radar along the distance direction;
dividing an imaging area into a plurality of pixel areas, wherein each pixel area is provided with a plurality of pixels;
Calculating the phase of each pixel point in an imaging area by adopting a zonal stepping phase iteration method;
calculating the size of a sampling point region according to the step-by-step distance solving error, and dividing the planar synthetic aperture into a plurality of sampling point regions;
the value of each pixel point of the observation area is calculated point by point.
3. The method of claim 2, wherein the dividing the imaging region into a number of pixel regions, each pixel region having a number of pixels, comprises:
parameter setting, including the size of each pixel and selecting initial pixel point coordinates;
calculating a distance compensation factor coefficient;
and calculating the size of the pixel areas and the number of the pixel areas.
4. A method according to claim 3, wherein the calculating the phase of each pixel point in the imaging region by using a split-region step-and-step phase iterative method comprises:
calculating an initial phase and a phase compensation factor based on the number of pixel areas, the number of pixels contained in each pixel area, the radar center frequency, the distance compensation factor coefficient and an initial value;
iteratively calculating the phase of the pixel points along the azimuth direction comprises the following steps: distance iteration, elevation iteration and pixel point area iteration.
5. The method of claim 4, wherein the planar aperture zoned nonlinear progressive phase iterative imaging method comprises:
Selecting an observation area pixel point and a radar initial sampling point;
calculating the distance course from the pixel point of the observation area to the radar initial sampling point;
calculating an azimuth distance compensation factor coefficient and an elevation distance compensation factor coefficient;
solving maxwell Lin Jinshi of the distance history;
solving an actual distance course;
and calculating the size of the sampling point region and the number of the dividing regions, and calculating the sampling point region according to the phase error limiting condition.
6. The method of claim 5, wherein calculating the value of each pixel of the observation region point by point comprises:
and reconstructing each pixel point of the observation area point by point based on an algorithm so as to realize three-dimensional resolution imaging of the observation area.
7. The planar aperture zoned nonlinear progressive phase iterative imaging device is based on the fact that a planar aperture three-dimensional imaging radar is moved along the elevation direction to form a synthetic aperture or real aperture radar configuration with sampling points located on the same plane; the device comprises:
the error analysis module is configured to be used for carrying out distance error analysis based on step-by-step distance compensation factor calculation, and specifically comprises the following steps:
obtaining an azimuth distance compensation factor, wherein the number of steps of a radar sampling point along the azimuth direction and the number of steps of the radar sampling point along the elevation direction relative to a radar initial sampling point are set, and a Maclalin expression of the radar sampling point is obtained; obtaining an approximate distance of Maclalin based on the processing of the Maclalin expression; obtaining an azimuth distance compensation factor based on the Maclalin approximate distance;
Obtaining an elevation distance compensation factor, wherein the number of steps of a radar sampling point relative to a radar initial sampling point along the azimuth direction and the number of steps along the elevation direction are set, and a Maclalin expression of the radar sampling point is obtained; obtaining an approximate distance of Maclalin based on the processing of the Maclalin expression; obtaining an elevation direction distance compensation factor based on the Maclalin approximate distance;
acquiring smaller azimuth stepping distance and elevation stepping distance according to the azimuth distance compensation factor and the elevation distance compensation factor so as to reduce distance errors;
combining the azimuth distance compensation factor and the elevation distance compensation factor, and solving the distance course from any point of the observation area to the radar sampling point in a stepping manner based on the distance from any point of the observation area to the radar initial sampling point; step-by-step solving a distance error generated by the distance process from any point of the observation area to the radar sampling point;
the imaging module is configured to be used for carrying out iterative calculation on the distance course from any point of the observation area to the sampling point through a stepping distance compensation factor based on the regional division of the sampling point of the planar aperture radar so as to finish the three-dimensional reconstruction of the observation area.
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