CN109856636B - Curve synthetic aperture radar self-adaptive three-dimensional imaging method - Google Patents
Curve synthetic aperture radar self-adaptive three-dimensional imaging method Download PDFInfo
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Abstract
The invention provides a curve synthetic aperture radar self-adaptive three-dimensional imaging method, which mainly solves the problem of low efficiency of the traditional BP imaging method. The method comprises the following implementation steps: 1) The radar platform transmits linear frequency modulation pulses along a parabola and receives echo signals; 2) Performing pulse compression on the echo signal; 3) Performing interpolation processing on the pulse pressure signal; 4) Performing hill climbing search on the one-dimensional distance image subjected to interpolation processing; 5) Performing sparsification processing on the one-dimensional distance image after the hill climbing search; 6) Establishing a gridding imaging plane in a three-dimensional space; 7) Performing self-adaptive projection on the sparse one-dimensional range profile to a gridding imaging plane to obtain a two-dimensional SAR image; 8) And arranging the two-dimensional SAR images into three-dimensional data blocks to obtain a final three-dimensional imaging result. The invention only projects the imaging grids corresponding to the sparse one-dimensional range profile peak value in the imaging process, reduces the times of projection, improves the imaging efficiency and can be used for real-time detection and imaging of a high-speed platform.
Description
Technical Field
The invention belongs to the technical field of digital signal processing, and particularly relates to a self-adaptive three-dimensional imaging method suitable for an SAR (synthetic aperture radar) under a curved aperture, which can be used for real-time detection and imaging of a high-speed platform.
Background
The synthetic aperture radar SAR can detect and image an observation area all day long, all weather long distance, and has wide application field. Most of the SAR systems currently used by people work in the front side view level flight mode. These SAR systems rely on transmitting large time-wide bandwidth product signals to obtain high resolution in the range direction and rely on platform motion to form a large synthetic aperture in the azimuth direction to obtain high resolution in the azimuth direction, but this method can only perform two-dimensional imaging. However, in many applications, such as navigation, autonomous landing, high-precision three-dimensional topographic mapping, etc., it is desirable for the SAR system to operate in a front-looking side view mode and to image the observation region in three dimensions. In addition, the three-dimensional imaging of the observation area has good application value for the detection of the hidden target. The research and development of the SAR system with the three-dimensional imaging capability have important significance.
The curve SAR enables the radar platform to move along a curve in an azimuth-altitude direction plane, so that the azimuth aperture is formed, and meanwhile, the aperture accumulation is carried out in the altitude direction, and the three-dimensional imaging capability is achieved. Since data sampling of the curve SAR in a three-dimensional space is incomplete, designing an effective imaging algorithm is a key to perform high-precision three-dimensional imaging on a target. Most of the existing curve SAR three-dimensional imaging algorithms use RELAX algorithm to estimate the position of scattering point on the basis of three-dimensional Fourier transform of echo data. However, the computation amount of the three-dimensional fourier transform is very large, and after the characteristics of each scattering point are obtained, the RELAX algorithm needs to update all the scattering points in front through iteration, so that the computation complexity is high, and the imaging efficiency is very low. The document "Zhang Zi-shan.research on the 3-D imaging Technology of curricular SAR [ D ], [ Master distribution ], national University of failure Technology, 2009", proposes a dimension-reduced RELAX algorithm aiming at the characteristic of complicated operation of the RELAX algorithm, converts a three-dimensional feature extraction problem into two-dimensional feature extraction problems, greatly reduces the operation amount, and reduces the operation time. However, the method is still based on the idea of three-dimensional fourier transform, the computation amount is still large, the imaging efficiency is low, and the requirement of real-time imaging is difficult to meet.
The article "Pang sho-bao, zhang Xiao-ling.imaging of downward-looking 3D circle SAR by BP algorithm, [ J ]. Electronic Science and Technology,2010,23 (12): 14-17" breaks through the idea of traditional three-dimensional Fourier transform, proposes to use a back projection BP algorithm to perform three-dimensional imaging, and realizes energy accumulation on each imaging grid through integration along a slope course.
Disclosure of Invention
The invention aims to provide a curve synthetic aperture radar self-adaptive three-dimensional imaging method aiming at the defects in the prior art and fully considering the sparsity of target distribution in an actual scene so as to reduce the operation amount and improve the imaging efficiency.
The technical idea of the invention is as follows: finding a target pointer by mountain climbing search on the one-dimensional range profile, and setting all signal values except the target pointer on the one-dimensional range profile to be 0 to obtain a sparse one-dimensional range profile; establishing a gridding imaging plane on a ground plane, and translating the plane upwards for a plurality of times along the height direction at equal intervals to obtain a plurality of gridding imaging planes; in each gridding imaging plane, only the grids corresponding to the sparse one-dimensional distance image peak value are projected, and the other grids are not projected; arranging all the projected gridding imaging planes into a three-dimensional data block from bottom to top according to the sequence from low to high in height to obtain a final three-dimensional imaging result. The concrete implementation steps comprise:
(1) The radar platform flies along a parabola, transmits chirp at a fixed pulse repetition frequency PRF and receives echo signals
Wherein it is present>
Indicating a fast time, N indicating a pulse number, N =1,2, … …, N being the number of pulses to be transmitted in total;
(2) For echo signal
Performing pulse compression treatment to obtain pulse pressure signal>
(3) To pulse pressure signal
Performing 8 times of interpolation processing to obtain a one-dimensional distance image>
(4) Along a fast time
For one-dimensional distance image>
Performing mountain climbing search:
(4a) Finding a one-dimensional range profile
Maximum value of (V) max Setting an initial search threshold ≧>
(4b) At search threshold V 0 Upper pair
Performing peak search, and recording target pointer t d ；
(4c) Let V 0 ＝0.5×V 0 ；
(4d) Repeating the steps (4 b) - (4 c) until the search threshold V is reached 0 Below the signal noise level, defining the search threshold as a noise threshold V;
(5) For one-dimensional range profile
Performing thinning treatment:
(5a) One-dimensional distance image
At the target pointer t d The corresponding signal value is kept unchanged, and the rest signal values are all set to be 0, so that the sparse one-dimensional distance image is obtained>
(5b) The target pointer t is obtained by searching according to the step (4) d At a fast time
Above by t d Taking the occupied interval as the center, extending 100 quick time sampling points to two sides respectively, and setting the interval as a search interval I;
(5c) For other one-dimensional range profile
Along fast time>
In the search interval I, performing peak value search on the noise threshold V obtained in the step (4), keeping the signals at the peak value unchanged, setting the rest signals to be 0, and obtaining other sparse one-dimensional distance images ^ 4>
(5d) Thinning the one-dimensional range profile obtained in (5 a)
Other sparse one-dimensional range images @obtainedin (5 c) and (5 c)>
And (3) combining into a sparse one-dimensional range profile set S:
(6) Establishing (A + 1) gridded imaging planes g 'uniformly distributed along the height direction in three-dimensional space' 0 ,g′ 1 ,g′ 2 ,……,g′ A Where A represents the number of gridding imaging plane translations:
(6a) Establishing a three-dimensional rectangular coordinate system in space by taking the center of a ground scene as an origin o, the azimuth direction as an x axis, the distance direction as a y axis and the height direction as a z axis;
(6b) With the plane z =0 as the imaging plane g 0 G centered on the origin o 0 Respectively along the x-axisAnd y-axis are gridded to obtain a gridded imaging plane g' 0 Each grid corresponding to a three-dimensional space coordinate (x) p ,y q 0), where P and Q represent the ordinal number of the grid rows and columns, respectively, P =1,2, … …, P, Q =1,2, … …, Q, P, and Q represent the total number of grids along the x-axis and y-axis, respectively;
(6c) Gridding imaging plane g 'in (6 b)' 0 Translating the surface A times along the z-axis at intervals of delta h to obtain (A + 1) gridded imaging planes g 'uniformly distributed from bottom to top along the z-axis' 0 ,g′ 1 ,……,g′ a ,……,g′ A Wherein g' a Denotes the a-th gridded image forming plane, a =0,1,2, … …, A, g' a The three-dimensional space coordinate corresponding to the grid of the p-th row and the q columns is (x) p ,y q ,aδh)；
(7) (A + 1) gridded imaging planes g 'in (6 c) are paired with the thinned one-dimensional range profile set S obtained in (5 d)' 0 ,g′ 1 ,……,g′ a ,……,g′ A Self-adaptive projection is carried out to obtain (A + 1) two-dimensional SAR images M 0 ,M 1 ,……,M a ,……,M A Wherein M is a Indicates that the thinned one-dimensional range image set S is on the a-th gridded imaging plane g' a The image formed above;
(8) Obtaining (A + 1) two-dimensional SAR images M obtained in step (7) 0 ,M 1 ,……,M a ,……,M A A three-dimensional Data block Data with the size of P multiplied by Q multiplied by (A + 1) is arranged from bottom to top in the sequence from low to high in height, and the three-dimensional Data block Data is the final three-dimensional imaging result.
Compared with the prior art, the invention has the following advantages:
according to the invention, the obtained three-dimensional imaging result is realized by performing sparsification treatment on the interpolated one-dimensional range profile and performing adaptive projection on the imaging grids in the three-dimensional space by using the sparsified one-dimensional range profile, so that the defect of a large amount of redundant operation caused by projection by traversing all grids in the conventional BP imaging method is avoided, the times of projection operation are reduced, the calculated amount is reduced, and the efficiency of curve SAR three-dimensional imaging is effectively improved; meanwhile, when the one-dimensional range profile is subjected to sparse processing, the data below the noise threshold are all set to be 0, so that the method has good inhibition performance on clutter or noise.
Drawings
FIG. 1 is a flow chart of an implementation of the present invention;
FIG. 2 is a schematic view of a flight path of a radar platform according to the present invention;
FIG. 3 is a schematic diagram of mountain climbing search for a one-dimensional distance image according to the present invention;
FIG. 4 is a schematic diagram illustrating the operation of thinning a one-dimensional range profile according to the present invention;
FIG. 5 is a schematic diagram of a gridding imaging plane built in a three-dimensional space according to the present invention;
FIG. 6 is a schematic diagram of adaptive projection according to the present invention;
FIG. 7 is a schematic diagram of three-dimensional block formation according to the present invention;
FIG. 8 is a comparison of the effects of projection imaging using the present invention and the prior art;
fig. 9 is a graph showing the results of three-dimensional imaging using the present invention.
Detailed Description
The technical solutions and effects of the present invention are further described in detail below with reference to the accompanying drawings and specific embodiments.
Referring to fig. 1, the implementation steps of the invention are as follows:
step 1, the radar flies along a parabola, and sends and receives echo signals:
the radar platform flies along a parabola, the flight path is shown in figure 2, and a chirp signal is transmitted at a fixed pulse repetition frequency PRF
And receives an echo signal pick-up>
Wherein, t represents the total time,
representing fast time, T representing pulse width, f c Denotes the carrier frequency, γ denotes the signal modulation frequency, c denotes the speed of light, N denotes the pulse number, and N =1,2, … …, N is the total number of pulses transmitted, R n The distance from the nth slow moment radar to the target is shown, j represents an imaginary unit, and rect (-) represents a rectangular window function.
2a) For echo signal
Go out the carrier frequency to obtain the base frequency signal->
2b) The base frequency signal
And a reference signal>
Performing conjugate multiplication in frequency domain, and converting the product back to time domain to obtain pulse pressureSignal>
Wherein, B r Representing the signal bandwidth, lambda represents the wavelength of the carrier,
the fast time domain Fourier transformation is shown, the IFFT is shown to be inverse Fourier transformation, (. The) shows the conjugation of the data, rect (the) shows a rectangular window function, sinc (the) shows a sine function; reference signal->
The expression of (a) is: />
To pulse pressure signal
Performing 8 times of interpolation processing, selecting a sine function with the length of 8 by an interpolation kernel to obtain a one-dimensional distance image>
Step (ii) of4, along with the fast time
For one-dimensional distance image>
And performing mountain climbing search to obtain a noise threshold V.
Referring to fig. 3, the specific implementation of this step is as follows:
4a) Finding a one-dimensional range profile
Maximum value of (V) max Setting an initial search threshold +>
4b) At search threshold V 0 Upper pair
Performing peak search and recording target pointer t d ；
4c) Let V 0 ＝0.5×V 0 ；
4d) Repeating steps 4 b) to 4 c) until the search threshold V is reached 0 Below the signal noise level, this search threshold is defined as the noise threshold V.
Step 5, for the one-dimensional range profile
And performing thinning treatment to obtain a thinned one-dimensional range profile set S.
Referring to fig. 4, the specific implementation of this step is as follows:
5a) One-dimensional distance image
At the target pointer t d The corresponding signal value is kept unchanged, and the rest signal values are all set to be 0, so that the sparse one-dimensional distance image is obtained>
5b) According to the target pointer t d At a fast time
Above by t d The occupied interval is 100 fast time sampling points which are respectively extended from the center to two sides, and the interval is set as a search interval I;
5c) For other one-dimensional range profile
Along fast time>
In a search interval I, performing peak value search on a noise threshold V, keeping signals at the peak value unchanged, setting the rest signals to be 0, and obtaining other sparse one-dimensional range image/based on the value of the peak value>
5d) Thinning the one-dimensional range profile obtained in 5 a)
And other thinned one-dimensional range images obtained in 5 c)>
And (3) combining into a sparse one-dimensional range profile set S:
Referring to fig. 5, the specific implementation of this step is as follows:
6a) Establishing a three-dimensional rectangular coordinate system in space by taking the center of a ground scene as an origin o, the azimuth direction as an x axis, the distance direction as a y axis and the height direction as a z axis;
6b) With the plane z =0 as the imaging plane g 0 G centered on the origin o 0 Respectively carrying out grid division along an x axis and a y axis to obtain a grid imaging plane g' 0 The grid spacing δ x on the x-axis and the grid spacing δ y on the y-axis should satisfy:
each grid corresponds to a three-dimensional space coordinate (x) p ,y q 0), where P and Q denote the grid row and column index numbers, respectively, P =1,2, … …, P, Q =1,2, … …, Q, P and Q denote the grid numbers along the x-axis and y-axis, respectively, R denotes the distance of the radar to the center of the scene when the radar is located at the center of the synthetic aperture, L x The equivalent projected length of the curved synthetic aperture in the azimuth direction,
representing the pitch angle of the radar when the radar is positioned in the center of the synthetic aperture;
6c) Gridding in 6 b) to an image plane g' 0 Translating the surface A times along the z-axis at intervals of delta h to obtain (A + 1) gridded imaging planes g 'uniformly distributed from bottom to top along the z-axis' 0 ,g′ 1 ,……,g′ a ,……,g′ A G 'as shown in FIG. 5' a The three-dimensional space coordinate corresponding to the grid of the p-th row and the q columns is (x) p ,y q A δ h), the interval δ h of translation should satisfy:
wherein g' a Representing the a-th gridded imagingPlane, a =0,1,2, … …, a denotes the number of times the gridded imaging plane is translated, R denotes the distance of the radar to the center of the scene when the radar is centered on the synthetic aperture, L z Representing the equivalent projected length of the curvilinear synthetic aperture in elevation.
Step 7, using the thinned one-dimensional range profile set S to grid (A + 1) imaging planes g' 0 ,g′ 1 ,g′ 2 ,……,g′ A And (5) performing adaptive projection.
7a) Calculating the a-th gridded imaging plane g' a All grid coordinates of (1 { (x)) p ,y q A δ h) l P =1,2, … …, P, Q =1,2, … …, Q } distance to radar at nth slow time { R a (P, Q, n) | P =1,2, … …, P, Q =1,2, … …, Q }, where a denotes the index number of the gridded imaging plane;
7b) A meshes imaging plane g' a All grids in the system correspond to the nth sparse one-dimensional range profile
To give g' a Up and &>
Grid set W corresponding to peak value an ；
7c) Will be provided with
To a grid set W an The middle grid is projected, and the rest grids are not projected to obtain->
In g' a Image g 'made above' an As shown in fig. 6;
7d) G 'of each element in the sparse one-dimensional range profile set S' a Projecting an image on the image to form a sum of g' a Corresponding image set: g a ＝{g′ a1 ,g′ a2 ,……,g′ an ,……,g′ aN Get wherein g' an Denotes the n-thSparsifying one-dimensional range profile
At the a-th gridded imaging plane g' a The above-described image;
7e) Set the image G a All the elements in (1) are added to obtain S in g' a Two-dimensional SAR image M formed above a ：
M a ＝g′ a1 +g′ a2 +……+g′ an +……+g′ aN
7f) Repeating steps 7 a) to 7 e) for all gridded imaging planes g' 0 ,g′ 1 ,……,g′ a ,……,g′ A The same operation is executed to obtain (A + 1) two-dimensional SAR images M 0 ,M 1 ,……,M a ,……,M A 。
Step 8, the (A + 1) two-dimensional SAR images M 0 ,M 1 ,……,M a ,……,M A Arranged into three-dimensional data blocks.
The (A + 1) two-dimensional SAR images M obtained in the step 7 0 ,M 1 ,……,M a ,……,M A Arranging a three-dimensional Data block Data with the size of P multiplied by Q multiplied by (A + 1) from bottom to top in the sequence from low to high in height, wherein the three-dimensional Data block Data is the final three-dimensional imaging result, and arranging the two-dimensional SAR image in the figure 7 (a) into the three-dimensional Data block in the figure 7 (b) as shown in the figure 7 to finish the curve synthetic aperture radar self-adaptive three-dimensional imaging.
The effect of the invention is further illustrated by the following simulation experiments:
experiment one:
1.1 Experimental conditions):
radar signal parameters and system parameters were set as shown in table 1:
TABLE 1 Experimental parameters
An experimental scene is as follows: the SAR platform works in a level flight normal side view mode, and the number of accumulated pulses along the azimuth direction is 512. 5 strong scattering points are arranged on the ground plane at a distance interval of 15m and an azimuth interval of 20m, and weak scattering points are randomly arranged on the ground plane to simulate clutter background.
1.2 Content of the experiment):
the existing BP and the imaging method of the present invention are respectively used to image the same scene, and the experimental results are shown in fig. 8, where:
FIG. 8 (a) is a geometrical diagram showing the distribution of scattering points,
FIG. 8 (b) is a comparison graph of the one-dimensional range profile before and after thinning,
figure 8 (c) is the prior art BP imaging result,
fig. 8 (d) is the imaging result of the present invention.
The total imaging time for both imaging methods is shown in table 2.
TABLE 2 comparison of imaging times for Current BP and invention
| Image forming method | Run time(s) |
| Existing BP | 104.6 |
| The invention | 66.6 |
1.3 Analysis of experimental results:
as can be seen from fig. 8 (b), after the one-dimensional range profile is subjected to the thinning processing, the one-dimensional range profile will retain only the data of the target, and the data of the clutter is set to 0, thereby reducing the data amount. It can be seen from the comparison of the imaging results in fig. 8 (c) and (d) that there are more clutter pixel points in the image formed by the existing BP, but the image formed by the present invention has only target scattering points, and the imaging quality is higher. As can be seen from the imaging time comparison of table 2, the imaging efficiency of the present invention is higher than that of the existing BP imaging method.
Experiment two:
2.1 Experimental conditions):
radar signal parameters and system parameters were set as shown in table 3:
TABLE 3 Experimental parameters
An experimental scene is as follows: the SAR platform works in a front side view mode, the motion trail is a parabola, the number of accumulated pulses in slow time is 2048, 6 scattering points are arranged in a three-dimensional space, the azimuth interval delta x =2m, the distance interval delta y =2m, and the height interval delta z =1.5m.
2.2 Experimental contents):
the present invention is used to perform three-dimensional imaging on the scene, and the imaging result is shown in fig. 9, in which:
figure 9 (a) shows a scatter plot in a scene,
figure 9 (b) is the result of three-dimensional imaging of figure 9 (a) using the present invention,
figure 9 (c) is the result of the present invention imaging the range-azimuth planar projection of the observed scene,
figure 9 (d) is the result of the present invention imaging the elevation-azimuth planar projection of the observed scene,
figure 9 (e) is the result of the present invention imaging the range-height projection of an observed scene onto a plane,
FIG. 9 (f) is a sectional view in the direction of distance of FIG. 9 (b),
FIG. 9 (g) is an azimuthal cross-sectional view of FIG. 9 (b),
FIG. 9 (h) is a highly sectional view of FIG. 9 (b),
figure 9 (i) is a top view of the three-dimensional imaging results of the present invention,
figure 9 (j) is a front view of the three-dimensional imaging results of the present invention,
fig. 9 (k) is a left side view of the three-dimensional imaging result of the present invention.
Table (4) shows the three-dimensional imaging time comparison of the existing BP and the present invention for the same scene.
TABLE 4 time comparison of three-dimensional imaging of Current BP and invention
| Image forming method | Run time(s) |
| Existing BP | 165.4 |
| The invention | 124.4 |
2.3 Analysis of experimental results:
as can be seen from FIG. 9 (b), the present invention can perform three-dimensional imaging on an observation scene, and the relative geometric position relationship between scattering points is correct. As can be seen from FIGS. 9 (c) to 9 (e), the geometric relationship of the scattering points in the three-dimensional space can be correctly reflected by the projection imaging performed on different imaging planes. As can be seen from FIGS. 9 (f) and 9 (g), the three-dimensional imaging results have good peak side lobe ratios in the range direction and the azimuth direction, and the side lobes are below-12 dB.
As can be seen from fig. 9 (h), the side lobes are degraded, about-10 dB, due to the uneven distribution of radar sampling points in the elevation direction, but still the scattering points can be resolved in the elevation direction.
As can be seen from fig. 9 (i) to 9 (k), the three views of the three-dimensional imaging exhibit a geometric positional relationship of the scattering points in accordance with fig. 9 (a), and in accordance with the two-dimensional projection results of fig. 9 (c) to 9 (e).
As can be seen from table 4, the three-dimensional imaging efficiency of the present invention is superior to that of the existing BP imaging algorithm.
In conclusion, the imaging efficiency of the three-dimensional imaging method is superior to that of the traditional BP algorithm.
Claims (5)
1. A curve synthetic aperture radar self-adaptive three-dimensional imaging method is characterized by comprising the following steps:
(1) The radar platform flies along a parabola, transmits chirp at a fixed pulse repetition frequency PRF and receives echo signals
Wherein it is present>
Indicating a fast time, N indicating a pulse number, N =1,2, … …, N being the number of pulses to be transmitted in total;
(2) For echo signal
Performing pulse compression treatment to obtain pulse pressure signal>
(3) To pulse pressure signal
Performing 8 times of interpolation processing to obtain a one-dimensional distance image>
(4) Along a fast time
For one-dimensional distance image>
Performing mountain climbing search:
(4a) Finding a one-dimensional range profile
Maximum value of (V) max Setting an initial search threshold ≧>
(4b) At search threshold V 0 Upper pair
Performing peak search, and recording target pointer t d ；
(4c) Let V 0 ＝0.5×V 0 ；
(4d) Repeating the steps (4 b) - (4 c) until the search threshold V is reached 0 Below the signal noise level, defining the search threshold as a noise threshold V;
(5) For one-dimensional range profile
Performing thinning treatment:
(5a) One-dimensional distance image
At the target pointer t d The corresponding signal value is kept unchanged, and the rest signal values are all set to be 0, so that the sparse one-dimensional distance image is obtained>
(5b) Searching to obtain a target pointer t according to the step (4) d At a fast time
Above by t d The occupied interval is the center, and the continuation is respectively 10 to two sidesSetting 0 fast time sampling points as a search interval I;
(5c) For other one-dimensional range profile
Along a fast time->
In a search interval I, performing peak value search on the noise threshold V obtained in the step (4), keeping the signal at the peak value unchanged, setting the rest signals to be 0, and obtaining other sparse one-dimensional distance image->
(5d) Thinning the one-dimensional range profile obtained in (5 a)
Other thinned one-dimensional range profile obtained in (5 c) and (5 d)
And (3) combining into a sparse one-dimensional range profile set S:
(6) Establishing (A + 1) gridded imaging planes g 'uniformly distributed along the height direction in three-dimensional space' 0 ,g′ 1 ,g′ 2 ,……,g′ A Where A represents the number of gridding imaging plane translations:
(6a) Establishing a three-dimensional rectangular coordinate system in space by taking the center of a ground scene as an original point o, the azimuth direction as an x axis, the distance direction as a y axis and the height direction as a z axis;
(6b) With the plane z =0 as the imaging plane g 0 G centered on the origin o 0 Respectively carrying out grid division along an x axis and a y axis to obtain a grid imaging plane g' 0 Each ofEach grid corresponding to a three-dimensional space coordinate (x) p ,y q 0), where P and Q denote the grid row and column index numbers, respectively, P =1,2, … …, P, Q =1,2, … …, Q, P, and Q denote the total number of grids along the x-axis and y-axis, respectively;
(6c) Gridding imaging plane g 'in (6 b)' 0 The image is translated upwards for A times along the z axis at intervals of delta h to obtain (A + 1) gridded imaging planes g 'which are uniformly distributed from bottom to top along the z axis' 0 ,g′ 1 ,……,g′ a ,……,g′ A Wherein g' a Denotes the u-th gridded imaging plane, a =0,1,2, … …, A, g' a The three-dimensional space coordinate corresponding to the grid of the p-th row and the q-th column is (x) p ,y q ,aδh)；
(7) The thinned one-dimensional range image set S obtained in step (5 d) is used to grid imaging planes g 'of (A + 1) in step (6 c)' 0 ,g′ 1 ,……,g′ a ,……,g′ A Self-adaptive projection is carried out to obtain (A + 1) two-dimensional SAR images M 0 ,M 1 ,……,M a ,……,M A Wherein M is a Indicates that the thinned one-dimensional range image set S is on the a-th gridded imaging plane g' a The image formed above; wherein (A + 1) gridded imaging planes g 'are subjected to sparse one-dimensional range profile set S' 0 ,g′ 1 ,……,g′ a ,……,g′ A Making adaptive projection, namely making sparse one-dimensional range profile
Non-zero value of (g) 'to gridding imaging plane' 0 ,g′ 1 ,……,g′ a ,……,g′ A The projection is done, zero is not done, which is implemented as follows:
(7a) Calculating the a-th gridded imaging plane g' a All grid coordinates in { (x) p ,y q A δ h) l P =1,2, … …, P, Q =1,2, … …, Q } distance to radar at nth slow time { R a (P, Q, n) | P =1,2, … …, P, Q =1,2, … …, Q }, where P and Q represent the row number and column number of the mesh, respectively, and P and Q represent the number of meshes divided along the x-axis and y-axis, respectivelyN denotes the pulse number, N =1,2, … …, N is the number of pulses emitted in total, a denotes the number of gridded imaging planes, a =0,1,2, … …, a denotes the number of times gridded imaging planes are translated, δ h denotes the interval between imaging planes;
(7b) G' a All grids in the system correspond to the nth sparse one-dimensional range profile
To give g' a Up and>
grid set W corresponding to peak value an ；
(7c) Will be provided with
Set W to the grid an The middle grid is projected, and the rest grids are not projected to obtain->
In g' a Image g 'made above' an ；
(7d) G 'of each element in the sparse one-dimensional range profile set S' a Projecting an image on the screen to form a projection image of g' a Corresponding image set: g a ＝{g′ a1 ,g′ a2 ,……,g′ an ,……,g′ aN Get wherein g' an Representing the nth thinned one-dimensional range profile
At the a-th gridding imaging plane g' a The above-described image;
(7e) Collecting images G a All the elements in (1) are added to obtain S in g' a Two-dimensional SAR image M formed above a ：
M a ＝g′ a1 +g′ a2 +……+g′ an +……+g′ aN
(7f) Repeating (7 a) - (7 e) for all gridded imaging planes g' 0 ,g′ 1 ,……,g′ a ,……,g′ A The same operation is executed, and (A + 1) two-dimensional SAR images M can be obtained 0 ,M 1 ,……,M a ,……,M A ；
(8) Obtaining (A + 1) two-dimensional SAR images M obtained in step (7) 0 ,M 1 ,……,M a ,……,M A A three-dimensional Data block Data with the size of P multiplied by Q multiplied by (A + 1) is arranged from bottom to top in the sequence from low to high in height, and the three-dimensional Data block Data is the final three-dimensional imaging result.
2. The method of claim 1, wherein the echo signal in (1)
The expression of (a) is:
wherein, t represents the total time,
denotes fast time, T denotes pulse width, f c Denotes the carrier frequency, gamma denotes the signal modulation frequency, c denotes the speed of light, N denotes the pulse number, N =1,2, … …, N is the total number of pulses transmitted, R n The distance from the nth slow moment radar to the target is shown, j represents an imaginary unit, and rect (-) represents a rectangular window function.
3. The method of claim 1, wherein the echo signals in (2) are summed
The pulse compression treatment is realized as follows:
(2a) Go back toWave signal
Go out the carrier frequency to obtain the base frequency signal->
/>
Wherein the content of the first and second substances,
representing fast time, n the pulse number, T the pulse width, R n The distance from the radar to a target at the nth slow moment is represented, c represents the speed of light, gamma represents the signal frequency modulation rate, j represents an imaginary unit, lambda represents the wavelength of a carrier wave, and rect (-) represents a rectangular window function;
(2b) The base frequency signal
And a reference signal->
Performing conjugate multiplication in the frequency domain, and converting the product back to the time domain to obtain a pulse pressure signal->
Wherein, B r Which is indicative of the bandwidth of the signal,
means Fourier transform, IFFT in the fast time domainIs represented as an inverse Fourier transform, (. Cndot.) * Indicating that the data is conjugated, sinc (-) indicating a sine function, the reference signal->
The expression of (a) is:
4. the method of claim 1, wherein g is centered around the origin o in (6 b) 0 And respectively carrying out grid division along an x axis and a y axis, wherein the interval delta x of the grid on the x axis and the interval delta y of the grid on the y axis meet the following conditions:
wherein, λ represents the wavelength of the carrier signal, R represents the distance from the radar to the center of the scene when the radar is located at the center of the synthetic aperture, and L x Is the equivalent projected length of the curved synthetic aperture in the azimuth direction, c represents the speed of light, B r Which is indicative of the bandwidth of the signal,
representing the pitch angle of the radar when the radar is centered in the synthetic aperture.
5. The method of claim 1, wherein the gridding in (6 c) is to image plane g' 0 And (3) translating along the z-axis upwards, wherein the translation interval delta h satisfies the following conditions:
wherein λ represents the wavelength of the carrier signal, R represents the distance from the radar to the center of the scene when the radar is located at the center of the synthetic aperture, and L z Representing the equivalent projected length of the curvilinear synthetic aperture in elevation.
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