CN108957452A - A kind of adaptive FFBP imaging method of synthetic aperture radar - Google Patents
A kind of adaptive FFBP imaging method of synthetic aperture radar Download PDFInfo
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- G—PHYSICS
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- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
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Abstract
The present invention proposes a kind of adaptive FFBP imaging method of synthetic aperture radar, solves the problems, such as that existing FFBP imaging method computational efficiency is lower.Implementation step are as follows: (1) distance is carried out to matched filtering to the echo-signal of synthetic aperture radar；(2) sub-aperture image is obtained；(3) multiple base two is carried out to sub- subaperture image to merge；(4) target detection is carried out to fused first width sub-aperture image；(5) target pixel points coordinate in remaining sub-aperture image is obtained；(5) to all sub-aperture image adaptive interpolation；(7) base two is carried out to all sub-aperture images after interpolation to merge；(8) target pixel points coordinate in prime sub-aperture image is transferred to the same level；(9) step (5) to (8) are repeated, a width full aperture SAR image is ultimately formed.In imaging process of the present invention, retains target pixel points and reject clutter background, reduce data volume and reduce interpolation number, improve computational efficiency.
Description
Technical Field
The invention belongs to the technical field of digital signal processing, and relates to a self-adaptive FFBP imaging method suitable for an SAR in a front side view mode, which can be used for real-time detection and imaging of a high-speed platform.
Background
Conventional Synthetic Aperture Radars (SAR) are typically in front view mode. However, in many real applications, radar is required to have front-side imaging capabilities, such as navigation, autonomous landing and ground taxi guidance. Therefore, the radar front-side imaging technology has important application value. However, in high-resolution front-side looking SAR imaging, the coupling effect between the target distance direction and the azimuth direction is much more severe than in the low-resolution front-side looking mode, which poses a challenge to the focusing performance of the SAR imaging algorithm. With the development of SAR technology, researchers have proposed a variety of imaging algorithms. In general, these imaging algorithms can be divided into two categories: frequency domain algorithms and time domain algorithms.
The frequency domain algorithm realizes two-dimensional fractal processing between the distance dimension and the azimuth dimension by correcting the coupling between the distance dimension and the azimuth dimension, and has simple realization and high imaging efficiency. However, frequency domain algorithms make many approximations in correcting for coupling between range and azimuth, and these approximation conditions are typically sensitive to SAR parameters such as wavelength, bandwidth, squint angle, aperture length, etc. Therefore, the application of frequency domain imaging algorithms in high resolution front side looking SAR systems is limited.
Currently, a typical time domain Algorithm is the Back-Projection (BP) Algorithm. The essence of the BP algorithm is that the antenna phase array performs beam forming along a specific direction, and the energy accumulation of each pixel point on an imaging grid is realized through the integration along the slope course. The BP algorithm ideally solves the distance and orientation coupling problem and is suitable for image reconstruction under complex imaging geometries such as front-side view or nonlinear flight path. However, the calculation complexity of the BP algorithm is up to O (N)3) And the imaging efficiency is low. In order to improve the time-domain imaging efficiency, the document "Synthetic imaging radar processing using fast transformed Back-Projection, ieee transformations on aeronautics and electronic systems, vol.39, No.3, pp.760-776, jul.2003" proposes a fast decomposed Back-Projection (FFBP) imaging method. Specifically, FFBP imaging methodThe full aperture of the synthetic aperture radar is uniformly divided into a plurality of sub apertures, the number of the sub apertures is an integer power of 2, each sub aperture data is projected to a corresponding polar coordinate system to form a sub aperture image, then, all the sub aperture images are subjected to multiple primary-secondary fusion, and pixel-by-pixel interpolation is carried out on the sub aperture images in each image fusion process until a full aperture SAR image is finally fused. FFBP imaging method reduces computational complexity to O (N) by aperture segmentation2log2N) can be applied to a front-side view SAR imaging system. However, the method has the defects that pixel-by-pixel interpolation and accumulation are performed during sub-aperture image fusion, the data volume is large, and the calculation efficiency is still difficult to meet the requirement of real-time detection.
Disclosure of Invention
The invention aims to provide a target detection-based adaptive FFBP imaging method aiming at the defects in the prior art, and the method is used for solving the technical problem of low calculation efficiency in the conventional FFBP imaging method.
The technical idea of the invention is as follows: in the self-adaptive FFBP imaging process, the sub-aperture image is subjected to multiple primary-secondary fusion to form a high-resolution sub-aperture image, the high-resolution sub-aperture image is subjected to target detection, and target pixel point coordinates are output; and then, only interpolating and accumulating the target pixel points, setting the clutter pixel points to be zero, and performing multiple times of primary-secondary fusion on the interpolated high-resolution sub-aperture image until a full-aperture SAR image is finally formed. The concrete implementation steps comprise:
(1) distance direction matching filtering is carried out on an echo signal of the synthetic aperture radar:
linear frequency-modulated signal s transmitted to synthetic aperture radart(tr) The echo signal is processed with carrier frequency elimination to obtain a base frequency signal s (t)r,taP) and for the fundamental frequency signal s (t)r,taP) carrying out distance direction matching filtering to obtain a distance compression signal s of the full aperture of the synthetic aperture radarrc(tr,taP) where trFor a fast time, taFor slow time, p represents the coordinates of the target;
(2) acquiring a sub-aperture image of the synthetic aperture radar:
(2a) supposing that the FFBP algorithm needs x-level image fusion, wherein x is more than or equal to 2 and is an integer, uniformly dividing the full aperture of the synthetic aperture radar into N sub-apertures with the length of L/N, wherein L is the length of the full aperture of the synthetic aperture radar, and N is 2x；
(2b) Establishing a polar coordinate system of each sub-aperture, and compressing the distance of each sub-aperture into a signal src(tr,taP) back projecting to polar coordinate system of corresponding subaperture to obtain first-stage image set S containing N pieces of image arranged from small to large according to subaperture sequence[1]，Wherein,represents the ith sub-aperture image, (-)[·]Representing the number of levels of the current image;
(3) for the first level image set S[1]Performing multiple primary-secondary fusion on the N sub-aperture images:
for the first level image set S[1]Carrying out (k-1) second-base fusion on the N sub-aperture images to obtain a solution containing N/2(k -1)Kth level image set S of swath sub-aperture images[k]The angular domain resolution of the fused subaperture image reaches lambdamin2L rad, and converting S[k]N2 in (1)(k-1)The breadth aperture images are numbered from small to large according to the aperture sequence, lambdaminRepresents the minimum wavelength of the transmitted signal;
(4) for the k-level image set S[k]The first sub-aperture image ofAnd (3) carrying out target detection:
for the k-level image set S[k]Middle first sub-aperture imageTarget detection is carried out to obtain a first sub-aperture imageCoordinates of target pixel point in (1)
(5) Obtaining coordinatesIn subaperture imageCorresponding coordinates in
Will be provided withTarget pixel point coordinates inIs transmitted to S[k]Middle removingThe remaining sub-aperture images of (2) to obtain coordinatesIn subaperture imageCorresponding coordinates inWherein n represents the number of sub-pictures, and
n＝2,3,……,N/2(k-1)；
(6) for the k-level image set S[k]N/2 in (1)(k-1)Carrying out self-adaptive interpolation on the breadth aperture image:
from the first sub-aperture imageCoordinates of middle target pixel pointAnd coordinatesIn subaperture imageCorresponding coordinates inAt the kth level of the image set S[k]N/2 of(k-1)Interpolating a target pixel point in the amplitude aperture image, and setting a clutter pixel point to be zero to obtain an interpolated image set S'[k]；
(7) Is prepared from S'[k]All sub-aperture images in (a) are subjected to one-shot basis-two fusion:
is prepared from S'[k]N/2 in (1)(k-1)Performing primary basis-two fusion on the amplitude aperture image to obtain an image containing N/2[k-2](k +1) th-level subaperture image set S of amplitude subaperture images[k+1]And then S is[k+1]N/2 in (1)[k-2]Numbering the breadth aperture images from small to large according to the aperture sequence;
(8) imaging the subapertureTarget pixel point coordinates inDelivery to sub-aperture images
Collecting the k-th level image S[k]Middle first sub-aperture imageTarget pixel point coordinates inTo the (k +1) th level image set S[k+1]First sub-aperture image ofObtaining a first sub-aperture imageCoordinates of target pixel point in (1)
(9) And (5) making k equal to k +1, and repeating the steps (5) to (8) until a full-aperture SAR image only containing the target pixel point is formed.
Compared with the prior art, the invention has the following advantages:
when the angular domain resolution of the full-aperture SAR image acquired by the invention reaches lambda along with the increase of the image fusion timesminat/2L rad, only set of images S[k]The first sub-aperture image in the image is used for target detection, the coordinates of target pixel points in the other sub-aperture images are obtained in a coordinate transmission mode, and the sub-aperture image only subjected to target pixel point interpolation is subjected to multi-time base-two fusion,the defect of large calculation data volume caused by pixel-by-pixel interpolation and accumulation in the conventional FFBP imaging method is overcome, the calculation data volume is reduced, the interpolation times are reduced, and compared with the prior art, the imaging efficiency is effectively improved.
Drawings
FIG. 1 is a flow chart of an implementation of the present invention;
FIG. 2 is a schematic diagram of coordinate transmission of a target pixel point;
FIG. 3 is a comparison of the present invention and the prior art for the effect of imaging a scene in an optical image;
FIG. 4 is a 6 th to 9 th order sub-aperture image contrast map of the present invention and prior art imaging the same scene;
fig. 5 is a comparison graph of the present invention and prior art for the run time of processing of each stage of sub-aperture images.
Detailed Description
The invention is described in further detail below with reference to the figures and the specific embodiments.
Referring to fig. 1, the implementation steps of the invention are as follows:
step 1) distance direction matched filtering is carried out on echo signals of the synthetic aperture radar:
step 1a) synthetic aperture radar transmits a chirp signal s at a fixed pulse repetition frequencyt(tr)：
st(tr)＝rect(tr／Tp)·exp[j2π(fctr+γtr 2/2)]
Wherein, trFor a fast time, tpIs the pulse width, fcFor the carrier frequency, γ corresponds toAnd adjusting the frequency.
Step 1b) removing carrier frequency of echo signal after receiving echo to obtain base frequency signal s (t)r,ta;p):
wherein alpha ispIs the scattering intensity of the target, wr(tr)＝rect[(tr-Δt)/Tp]，wa(ta) For the azimuth window function of the radar beam, Δ t is 2R (t)a(ii) a p)/c is the signal two-way time delay, taFor slow time, c denotes the speed of light and p denotes the coordinates of the object.
Step 1c) for the fundamental frequency signal s (t)r,taP) carrying out distance direction matching filtering to obtain a distance compression signal s of the full aperture of the synthetic aperture radarrc(tr,ta;p)：
Where λ represents the carrier wavelength.
Step 2) obtaining a sub-aperture image of the synthetic aperture radar:
step 2a) assuming that the FFBP algorithm needs x-level image fusion, wherein x is more than or equal to 2 and is an integer, and uniformly dividing the full aperture of the synthetic aperture radar into N sub-apertures with the length of L/N, wherein L is the length of the full aperture of the synthetic aperture radar, and N is 2x；
Step 2b) establishing a polar coordinate system of each sub-aperture, and compressing the distance of each sub-aperture into a signal src(tr,taP) back projecting to polar coordinate system of corresponding subaperture to obtain first-stage image set S containing N pieces of image arranged from small to large according to subaperture sequence[1]，Wherein one sub-aperture imageThe expression of (a) is:
wherein i represents the ith sub-aperture (.)[·]the image is represented in a series, M (M is 1,2, 3.. multidot.m) is a pulse index, α is a back projection vector corresponding to a pixel point in a scene, and R is an instantaneous slant distance vector between a radar and the pixel point.
Step 3) for the first-level image set S[1]Performing multiple primary-secondary fusion on the N sub-aperture images:
for the first level image set S[1]Carrying out (k-1) second-base fusion on the N sub-aperture images to obtain a solution containing N/2(k -1)Kth level image set S of swath sub-aperture images[k]The angular domain resolution of the fused subaperture image reaches lambdamin2L rad, and converting S[k]N/2 in (1)(k-1)The breadth aperture images are numbered from small to large according to the aperture sequence, lambdaminRepresenting the minimum wavelength of the emission signal, in the process of the two-step fusion, a sinc function with the length of 8 points is used for preceding-stage sub-aperture imagesAndinterpolation is carried out to obtainAndthen the interpolated sub-aperture imageAndadding pixel points by pixel points to obtain a new sub-aperture image
Step 4) for the k-th level image set S[k]The first sub-aperture image ofAnd (3) carrying out target detection:
for the k-level image set S[k]Middle first sub-aperture imagePerforming target detection by using SP-CFAR algorithm to obtain a first sub-aperture imageCoordinates of target pixel point in (1)
Step 5) obtaining coordinatesIn subaperture imageCorresponding coordinates in
Will be provided withTarget pixel point coordinates inIs transmitted to S[k]Middle removingThe remaining sub-aperture images of (a) as shown in the first row of fig. 2, result in coordinatesIn subaperture imageCorresponding coordinates in
Wherein N represents the number of the sub-image, and N is 2,3, … …, N/2(k-1)，L[k]Is the sub-aperture length in the processing at level k.
Step 6) for the k-th level image set S[k]N/2 in (1)(k-1)Carrying out self-adaptive interpolation on the breadth aperture image:
from the first sub-aperture imageCoordinates of middle target pixel pointAnd coordinatesIn subaperture imageCorresponding coordinates inAt the kth level of the image set S[k]N/2 of(k-1)Interpolating a target pixel point in the amplitude aperture image, using a sinc function with the length of 8 points for an interpolation kernel, and setting a clutter pixel point to be zero to obtain an interpolated image set S'[k]；
Step 7) preparing S'[k]All sub-aperture images in (a) are subjected to one-shot basis-two fusion:
is prepared from S'[k]N/2 in (1)(k-1)Performing primary basis-two fusion on the amplitude aperture image to obtain an image containing N/2[k-2](k +1) th-level subaperture image set S of amplitude subaperture images[k+1]And then S is[k+1]N/2 in (1)[k-2]Numbering the breadth aperture images from small to large according to the aperture sequence;
step 8) sub-aperture imagingTarget pixel point coordinates inDelivery to sub-aperture images
Collecting the k-th level image S[k]Middle first sub-aperture imageTarget pixel point coordinates inTo the (k +1) th level image set S[k+1]First sub-aperture image ofAs shown in the second row of fig. 2, a first sub-aperture image is obtainedCoordinates of target pixel point in (1)
And 9) enabling k to be k +1, and repeating the steps (5) to (8) until a full-aperture SAR image only containing the target pixel point is formed.
The technical effect of the invention is further explained by combining the actual measurement data processing experiment of the Ku wave band as follows:
1. experimental conditions and contents:
TABLE 1 measured data System parameters
The FFBP imaging method and the self-adaptive FFBP imaging method are respectively utilized to image the same scene, and the main targets in the scene are some artificial buildings. In the scene imaging processing, 9-level sub-aperture images are generated, and the SP-CFAR algorithm is used for target detection when the 6 th-level sub-aperture images are processed. Fig. 3 shows experimental results, where fig. 3(a) is an imaging result of a conventional FFBP imaging method, fig. 3(b) is an imaging result of an adaptive FFBP imaging method, and fig. 3(c) is a corresponding google map optical image. Fig. 4 is a 6 th to 9 th-level sub-aperture image contrast map of the same scene imaged by the FFBP and the adaptive FFBP, wherein the first behavior is the FFBP imaging result and the second behavior is the adaptive FFBP imaging result. The computer run time of the FFBP and adaptive FFBP imaging methods for each stage of sub-aperture image processing is given in fig. 5. The measured data system parameters are shown in table 1 and the total imaging time for both algorithms is shown in table 2.
TABLE 2 comparison of experimental imaging times of measured data
| Image forming method | Run time(s) |
| FFBP | 169.76 |
| Adaptive FFBP | 101.32 |
2. And (3) analyzing an experimental result:
as can be seen from fig. 3, the adaptive FFBP preserves the target of interest while rejecting clutter background. As can be seen from fig. 4, in the 6 th-level sub-aperture image, there are more clutter pixels in the detection result because the resolution and the signal-to-noise ratio of the sub-aperture image are lower. As the sub-aperture length increases, the target structure becomes clearer and clutter pixels are gradually eliminated. As can be seen from fig. 5, the running time of adaptive FFBP on the 6 th level sub-aperture image processing is slightly higher than the corresponding running time of FFBP, since the SP-CFAR detection starts from the 6 th level sub-aperture image. In the 7 th to 9 th-level sub-aperture images, only a few pixel points are interpolated based on the detection result, and the processing time of each level of the self-adaptive FFBP imaging method is greatly shortened.
In conclusion, the imaging efficiency of the imaging method is superior to that of the conventional FFBP imaging method.
Claims (5)
1. A synthetic aperture radar self-adaptive FFBP imaging method is characterized by comprising the following steps:
(1) distance direction matching filtering is carried out on an echo signal of the synthetic aperture radar:
linear frequency-modulated signal s transmitted to synthetic aperture radart(tr) The echo signal is processed with carrier frequency elimination to obtain a base frequency signal s (t)r，ta(ii) a p) and for the fundamental frequency signal s (t)r，ta(ii) a p) carrying out distance direction matching filtering to obtain a full-aperture distance compression signal s of the synthetic aperture radarrc(tr，ta(ii) a p) in which t)rFor a fast time, taFor slow time, p represents the coordinates of the target;
(2) acquiring a sub-aperture image of the synthetic aperture radar:
(2a) supposing that the FFBP algorithm needs x-level image fusion, wherein x is more than or equal to 2 and is an integer, uniformly dividing the full aperture of the synthetic aperture radar into N sub-apertures with the length of L/N, wherein L is the length of the full aperture of the synthetic aperture radar, and N is 2x；
(2b) Establishing a polar coordinate system of each sub-aperture, and compressing the distance of each sub-aperture into a signal src(tr，ta(ii) a p) back projecting to a polar coordinate system of a corresponding subaperture to obtain a first-level image set S containing N images which are arranged from small to large according to the sequence of the subapertures[1]，Wherein,represents the ith sub-aperture image, (-)[·]Representing the number of levels of the current image;
(3) for the first level image set S[1]Performing multiple primary-secondary fusion on the N sub-aperture images:
for the first level image set S[1]Carrying out (k-1) second-base fusion on the N sub-aperture images to obtain a solution containing N/2(k-1)Kth level image set S of swath sub-aperture images[k]The angular domain resolution of the fused subaperture image reaches lambdamin2Lrad, and converting S[k]N/2 in (1)(k-1)The breadth aperture images are numbered from small to large according to the aperture sequence, lambdaminRepresents the minimum wavelength of the transmitted signal;
(4) for the k-level image set S[k]The first sub-aperture image ofAnd (3) carrying out target detection:
for the k-th image setAnd then S[k]Middle first sub-aperture imageTarget detection is carried out to obtain a first sub-aperture imageCoordinates of target pixel point in (1)
(5) Obtaining coordinatesIn subaperture imageCorresponding coordinates in
Will be provided withTarget pixel point coordinates inIs transmitted to S[k]Middle removingThe remaining sub-aperture images of (2) to obtain coordinatesIn subaperture imageCorresponding coordinates inWhere N denotes the number of the subimages and N is 2,3, … …, N/2(k-1)；
(6) For the k-level image set S[k]N/2 in (1)(k-1)Carrying out self-adaptive interpolation on the breadth aperture image:
from the first sub-aperture imageCoordinates of middle target pixel pointAnd coordinatesIn subaperture imageCorresponding coordinates inAt the kth level of the image set S[k]N/2 of(k-1)Interpolating a target pixel point in the amplitude aperture image, and setting a clutter pixel point to be zero to obtain an interpolated image set S'[k]；
(7) Is prepared from S'[k]All sub-aperture images in (a) are subjected to one-shot basis-two fusion:
is prepared from S'[k]N/2 in (1)(k-1)Performing primary basis-two fusion on the amplitude aperture image to obtain an image containing N/2[k-2](k +1) th-level subaperture image set S of amplitude subaperture images[k+1]And then S is[k+1]N/2 in (1)[k-2]Numbering the breadth aperture images from small to large according to the aperture sequence;
(8) imaging the subapertureTarget pixel point coordinates inDelivery to sub-aperture images
Collecting the k-th level image S[k]Middle first sub-aperture imageTarget pixel point coordinates inTo the (k +1) th level image set S[k+1]First sub-aperture image ofObtaining a first sub-aperture imageCoordinates of target pixel point in (1)
(9) And (5) making k equal to k +1, and repeating the steps (5) to (8) until a full-aperture SAR image only containing the target pixel point is formed.
2. The method of claim 1, wherein step (3) is performed on the first-level image set S[1]The N sub-aperture images are subjected to multiple primary-secondary fusion, and the fusion method comprises the following steps:
adopting a fusion method in FFBP to collect S the first-level image[1]The N sub-aperture images are subjected to multiple primary-secondary fusion until the angular domain resolution of each fused sub-aperture image reaches lambdaminStopping at/2 Lrad to obtain a product containing N/2(k-1)Kth level image set S of swath sub-aperture images[k]，λminFor the minimum wavelength of the transmitted signal, L is the synthetic aperture radar full aperture length.
3. The synthetic aperture radar adaptive FFBP imaging method according to claim 1, wherein the k-th level image set S in step (4) is[k]The first sub-aperture image ofAnd (5) carrying out target detection by adopting an SP-CFAR algorithm.
4. The synthetic aperture radar adaptive FFBP imaging method according to claim 1, wherein the coordinates in step (5) areIn subaperture imageCorresponding coordinates inWhereinAndthe calculation formulas of (A) and (B) are respectively as follows:
wherein L is[k]Is the sub-aperture length in the k-th stage processing, (. DEG)[·]Indicates the number of stages the current image is in, and n indicates the image number.
5. The synthetic aperture radar adaptive FFBP imaging method according to claim 1, wherein the first sub-aperture image of step (8)Coordinates of target pixel point in (1)WhereinAndthe calculation formulas of (A) and (B) are respectively as follows:
wherein, (.)[·]Indicating the number of levels in which the current image is located, L[k]Is the sub-aperture length in the processing at level k.
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| CN110837128A (en) * | 2019-11-26 | 2020-02-25 | 内蒙古工业大学 | Imaging method of cylindrical array radar |
| CN111352108A (en) * | 2020-02-28 | 2020-06-30 | 南昌大学 | Fast SAR echo signal simulation method based on FFBP reverse processing |
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| CN110579762A (en) * | 2019-09-17 | 2019-12-17 | 上海无线电设备研究所 | Terahertz circular track SAR rapid back projection imaging method |
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| CN110837128B (en) * | 2019-11-26 | 2021-09-10 | 内蒙古工业大学 | Imaging method of cylindrical array radar |
| CN111352108A (en) * | 2020-02-28 | 2020-06-30 | 南昌大学 | Fast SAR echo signal simulation method based on FFBP reverse processing |
| CN113514827A (en) * | 2021-03-03 | 2021-10-19 | 南昌大学 | Synthetic aperture radar imaging processing method and application in unmanned aerial vehicle cluster mode |
| CN113514827B (en) * | 2021-03-03 | 2023-09-05 | 南昌大学 | Synthetic aperture radar imaging processing method and application in unmanned aerial vehicle cluster mode |
| CN113933835A (en) * | 2021-09-02 | 2022-01-14 | 深圳大学 | Rapid imaging method for vehicle-mounted synthetic aperture radar |
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