CN109959933A - A kind of compressed sensing based more baseline circular track synthetic aperture radar image-forming methods - Google Patents
A kind of compressed sensing based more baseline circular track synthetic aperture radar image-forming methods Download PDFInfo
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- G—PHYSICS
- G01—MEASURING; TESTING
- 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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- G01S13/89—Radar or analogous systems specially adapted for specific applications for mapping or imaging
- G01S13/90—Radar or analogous systems specially adapted for specific applications for mapping or imaging using synthetic aperture techniques, e.g. synthetic aperture radar [SAR] techniques
- G01S13/9004—SAR image acquisition techniques
- G01S13/9017—SAR image acquisition techniques with time domain processing of the SAR signals in azimuth
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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
- G01S13/00—Systems using the reflection or reradiation of radio waves, e.g. radar systems; Analogous systems using reflection or reradiation of waves whose nature or wavelength is irrelevant or unspecified
- G01S13/88—Radar or analogous systems specially adapted for specific applications
- G01S13/89—Radar or analogous systems specially adapted for specific applications for mapping or imaging
- G01S13/90—Radar or analogous systems specially adapted for specific applications for mapping or imaging using synthetic aperture techniques, e.g. synthetic aperture radar [SAR] techniques
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- G01S13/9005—SAR image acquisition techniques with optical processing of the SAR signals
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Abstract
The present invention relates to a kind of compressed sensing based more baseline circular track synthetic aperture radar image-forming methods, the step of this method includes: step S1: deriving the compressed sensing imaging algorithm based on rear orientation projection's inverse operator；Step S2: the two-dimensional surface imaging of sub-aperture is carried out using the compressed sensing algorithm based on rear orientation projection's inverse operator；Step S3: using the height of compressed sensing algorithm progress sub-aperture to focusing, and the correction of target two-dimensional coordinate position is further completed；Step S4: all sub-aperture three-dimensional imaging results are subjected to coherent accumulation, obtain final full aperture three-dimensional imaging result.
Description
Technical field
The present invention relates to radar signal processing fields, more particularly to a kind of compressed sensing based more baseline circular tracks to synthesize hole
Diameter radar imaging method solves big more baseline circular track data of synthetic aperture radar collection capacities and lack sampling and nonuniform sampling
In the case of the high problem of secondary lobe after target imaging, to realize the three-dimensional imaging knot for obtaining high quality with a small amount of echo data
Fruit.
Background technique
More baseline circular track synthetic aperture radar are on object height direction, and radar carries out multiple circumference observation to target
Imaging radar.The mode can not only obtain the two-dimentional ground range resolution of sub-wavelength grade, and height with higher is to resolution ratio.
These good characteristics of more baseline circular track synthetic aperture radar make it in automatic target detection, target detection, high-precision landform
The fields such as mapping, biomass parameters estimation, man-made target elevation extraction, safety detection have a very important significance.
Though the potential three-dimension high-resolution imaging for realizing target of more baseline circular track synthetic aperture radar, according to Nai Kuisi
Spy samples criterion, needs the data volume for acquiring and handling big under the mode, brings to hardware store and computing resource and greatly choose
War.In addition, airborne more baseline circular track synthetic aperture radar are in data acquisition, radar platform is difficult to keep in two-dimensional surface
The Circular test of standard is difficult to keep equal interval sampling in height upwards.If by the echo data of acquisition according to meeting Nyquist
Sampling criterion condition is imaged, then will lead to the high problem of secondary lobe after target imaging.
Compressive sensing theory is different from traditional nyquist sampling theorem, is a kind of for sparse or compressible signal
New sampling and reconstruction theory.Under the theoretical frame, when signal has sparsity or compressibility, only it need to acquire or measure and is a small amount of
Signal low dimension projective value can be achieved with the accurate or approximate reconstruction of higher-dimension.Further, it is also possible to complicated by high signal reconstruction
Degree carrys out " exchanging for " low data and acquires complexity.
Currently, compressed sensing based more baseline circular track synthetic aperture radar image-formings have been studied, it is concentrated mainly on height
It spends on upward focal imaging.The full aperture data of more baseline circular track synthetic aperture radar are divided into multiple sub-aperture by Ponce et al.
Diameter, to each sub-aperture data first use Turbo Factor backprojection method carry out two-dimensional imaging, afterwards using compressed sensing algorithm into
Sub-aperture 3-D image is finally carried out Incoherent beam combining, realizes the three-dimension high-resolution of wood land by row height to focusing
(Ponce O, Prats-Iraola P, Scheiber R, et al.Polarimetric 3-D reconstruction is imaged
from multicircular SAR at P-band[J].IEEE Geoscience and Remote Sensing
Letters,2014(4):803-807).Austin et al. is realized also with compressed sensing based height to focus method
More baseline circular track synthetic aperture radar image-formings (Austin C D, the Ertin E, Moses of GOTCHA data and Backhoe data
R L.Sparse signal methods for 3-D radar imaging[J].IEEE Journal of Selected
Topics in Signal Processing,2011(3):408-423)。
Summary of the invention
It is an object of the present invention to provide a kind of compressed sensing based more baseline circular track synthetic aperture radar image-forming methods, can
It is few in echo data amount and there are the three-dimensional imaging results in the case where lack sampling and nonuniform sampling, obtaining high quality.
In order to achieve the above objectives, the present invention provides a kind of compressed sensing based more baseline circular track synthetic aperture radar image-formings
The step of method includes:
Step S1: the compressed sensing imaging algorithm based on rear orientation projection's inverse operator is derived；
Step S2: the two-dimensional surface imaging of sub-aperture is carried out using the compressed sensing algorithm based on rear orientation projection's inverse operator；
Step S3: it using the height of compressed sensing algorithm progress sub-aperture to focusing, and further completes target two dimension and sits
The correction of cursor position；
Step S4: all sub-aperture three-dimensional imaging results are subjected to coherent accumulation, obtain final full aperture three-dimensional imaging
As a result.
The beneficial effects of the present invention are: the data volume that need to be acquired for more baseline circular track synthetic aperture radar is big, and owe
The high problem of secondary lobe after target imaging in the case of sampling and nonuniform sampling, is synthesized using compressed sensing based more baseline circular tracks
Aperture radar imaging method converts imaging problem to and seeks Optimal solution problem, realizes and obtains high quality with a small amount of echo data
Three-dimensional imaging result.
Detailed description of the invention
Fig. 1 is the general flow chart of compressed sensing based more baseline circular track synthetic aperture radar image-forming methods in the present invention；
Fig. 2 is the imaging geometry figure of more baseline circular track synthetic aperture radar；
Fig. 3 is the flow chart that the present invention derives the compressed sensing imaging algorithm based on rear orientation projection's inverse operator；
Fig. 4 is the present invention using the compressed sensing imaging algorithm realization sub-aperture two-dimensional surface based on rear orientation projection's inverse operator
The flow chart of imaging；
Fig. 5 is that the present invention uses compressed sensing algorithm realization sub-aperture height to focusing, and further completes target two dimension
The flow chart of coordinate position correction.
Specific embodiment
To make the objectives, technical solutions, and advantages of the present invention clearer, below in conjunction with specific embodiment, and reference
Attached drawing is described in further detail the present invention.
Fig. 1 shows in the present invention a kind of the total of compressed sensing based more baseline circular track synthetic aperture radar image-forming methods
Flow chart.The specific implementation steps are as follows for this method:
Step S1: the compressed sensing imaging algorithm based on rear orientation projection's inverse operator is derived, following four step is divided into:
Step S11: the echo signal model of more baseline circular track synthetic aperture radar is established.More baseline circular track synthetic aperture thunders
Under expression patterns, radar surrounding target region carries out circumference observation, and imaging geometry is as shown in Figure 2.Consider that radar surrounding target flies
M baseline of row, the distance at radar to target area center is constant R under every baselinec, radar bearing angle is φ ∈ [0,2 π].
Δ θ, the corresponding downwards angle of visibility θ of i-th baseline are divided between remembering between the downwards angle of visibility of adjacent two baselinemFor θm=θ1+ (m-1) Δ θ, m
=1,2 ... M.
Assuming that observed object is discrete point target, wherein the coordinate position of n-th of target is (xn,yn,zn), scattering
Coefficient is σn, and radar transmitter frequency stairstep signal, then under the m articles baseline, the echo-signal that radar receives is,
Wherein, k=2 π/λ, λ are wavelength.
Step S12: the two-dimensional imaging model based on back-projection algorithm is established.Each baseline is carried out using back-projection algorithm
The expression formula of reconstruction is,
Wherein,
kc=2 π/λc, λcFor center wavelength.
If above-mentioned rear orientation projection's process is indicated with operator P, above-mentioned reconstruction process is write as Vector-Matrix Form and is,
Step S13: compressed sensing based echo-signal observation model is established.Write echo-signal as Vector-Matrix Form
For,
S=Φ σ
Wherein, Φ is
The matrix of composition.
Under compressive sensing theory frame, it is Φ that calculation matrix, which may be selected, and sparse matrix is unit matrix.
Step S14: the compressed sensing echo-signal observation model based on rear orientation projection's inverse operator is derived, and by imaging process
Be converted to optimization problem.
In conjunction with rear orientation projection's reconstruction process and compressed sensing based echo-signal observation model, can obtain
Φ≈P-1
Structural matrix G is,
G=P-1≈Φ
In actual conditions, there are noise jamming, therefore the compression sense based on rear orientation projection's inverse operator during measuring echo
The expression formula for knowing echo-signal observation model is,
S=G σ+n
Wherein, n indicates observation noise.
Further consider that the down-sampled model of echo data, observation model are represented by,
Wherein, SDIndicate down-sampled echo-signal, nDIndicate down-sampled observation noise.
According to compressive sensing theory, target scattering coefficient is solvedIt can be converted into and solve lq(0≤q≤1) optimization problem,
Meet
Further it can be equivalent to solve following optimization problem again,
Wherein, | | | |FFor Frobenius norm, Dθ、DfRespectively orientation angular domain, the down-sampled square on step frequency domain
Battle array, λ is regularization parameter.
Step S2: carrying out the two-dimensional surface imaging of sub-aperture using the compressed sensing algorithm based on rear orientation projection's inverse operator,
Detailed process is as shown in figure 3, be divided into following four step:
Step S21: being divided into several sub-apertures for full aperture echo data, obtains the down-sampled echo data of each sub-aperture
SD。
Step S22: determine that observing matrix is DG, sparse matrix is unit matrix I.
Step S23: threshold value ratio is γ, and selecting amplitude threshold is γ PSD。
Step S24: the compressed sensing based on rear orientation projection's inverse operator is carried out using soft-threshold iterative algorithm and is rebuild, realizes son
The two-dimensional imaging in aperture.
Step S3: it using the height of compressed sensing algorithm progress sub-aperture to focusing, and further completes target two dimension and sits
The correction of cursor position, detailed process is as shown in figure 4, be divided into following four step:
Step S31: compressed sensing based height is established to focus model.Under the m articles baseline, the two of any one sub-aperture
Tieing up imaging results T (x ', y ', φ) is
Wherein,S (x, y) is the two-dimentional window letter to match with the finite-duration of target
Number, fp(x,y,zp(x, y)) indicate that the p scattering point that different height is upward at two-dimensional coordinate (x, y), * indicate convolution.
Considering φ=90 °, the two-dimensional imaging result of any one sub-aperture is expressed as,
When height to sampling meet Nyquist criterion when,
It enablesThen
Remember Tm=[Tm],Then
T≈ψf+n
Wherein, n indicates observation noise.
Further considering the down-sampled model of echo data, compressed sensing based height is expressed as to focus model,
TD≈Dψf+nD
Wherein, TDIndicate down-sampled two-dimensional imaging as a result, nDIndicate down-sampled observation noise.
Step S32: determine that observing matrix is D ψ, sparse matrix is unit matrix I.
Step S33: carrying out compressed sensing based reconstruction using base tracking Denoising Algorithm, realizes the height of sub-aperture to poly-
It is burnt.
Step S34: the pixel coordinate (x ', y ') and target true three-dimension coordinate in the two-dimensional imaging result of sub-aperture are utilized
Relationship between (x, y, z), calibrated altitude is to the target two-dimensional coordinate position after focusing, i.e.,
Step S4: all sub-aperture three-dimensional imaging results are subjected to coherent accumulation, obtain final full aperture three-dimensional imaging
As a result.
The above, the only specific embodiment in the present invention, but scope of protection of the present invention is not limited thereto, appoints
What is familiar with the people of the technology within the technical scope disclosed by the invention, it will be appreciated that expects transforms or replaces, and should all cover
Within scope of the invention.
Claims (4)
1. a kind of compressed sensing based more baseline circular track synthetic aperture radar image-forming methods, which is characterized in that the step of this method
Suddenly include:
Step S1: the compressed sensing imaging algorithm based on rear orientation projection's inverse operator is derived；
Step S2: the two-dimensional surface imaging of sub-aperture is carried out using the compressed sensing algorithm based on rear orientation projection's inverse operator；
Step S3: using the height of compressed sensing algorithm progress sub-aperture to focusing, and target two-dimensional coordinate position is further completed
The correction set；
Step S4: all sub-aperture three-dimensional imaging results are subjected to coherent accumulation, obtain final full aperture three-dimensional imaging result.
2. compressed sensing based more baseline circular track synthetic aperture radar image-forming methods according to claim 1, feature
The step of being, deriving the compressed sensing imaging algorithm based on rear orientation projection's inverse operator is as follows:
Step S11: the echo signal model of more baseline circular track synthetic aperture radar is established.More baseline circular track synthetic aperture radar moulds
Under formula, radar surrounding target region carries out circumference observation.Consider M baseline of radar surrounding target flight, radar under every baseline
Distance to target area center is constant Rc, radar bearing angle is φ ∈ [0,2 π].Between the downwards angle of visibility for remembering adjacent two baseline
Between be divided into Δ θ, the corresponding downwards angle of visibility θ of i-th baselinemFor θm=θ1+ (m-1) Δ θ, m=1,2 ... M.
Assuming that observed object is discrete point target, wherein the coordinate position of n-th of target is (xn,yn,zn), scattering coefficient
For σn, and radar transmitter frequency stairstep signal, then under the m articles baseline, the echo-signal that radar receives is,
Wherein, k=2 π/λ, λ are wavelength.
Step S12: the two-dimensional imaging model based on back-projection algorithm is established.Each baseline is rebuild using back-projection algorithm
Expression formula be,
Wherein,
kc=2 π/λc, λcFor center wavelength.
If above-mentioned rear orientation projection's process is indicated with operator P, above-mentioned reconstruction process is write as Vector-Matrix Form and is,
Step S13: compressed sensing based echo-signal observation model is established.Being write echo-signal as Vector-Matrix Form is,
S=Φ σ
Wherein, Φ isStructure
At matrix.
Under compressive sensing theory frame, it is Φ that calculation matrix, which may be selected, and sparse matrix is unit matrix.
Step S14: the compressed sensing echo-signal observation model based on rear orientation projection's inverse operator is derived, and imaging process is converted
For optimization problem.
In conjunction with rear orientation projection's reconstruction process and compressed sensing based echo-signal observation model, Φ ≈ P can be obtained-1
Structural matrix G is,
G=P-1≈Φ
In actual conditions, there is noise jamming during measuring echo, therefore return based on the compressed sensing of rear orientation projection's inverse operator
The expression formula of wave signal observation model is,
S=G σ+n
Wherein, n indicates observation noise.
Further consider that the down-sampled model of echo data, observation model are represented by,
Wherein, SDIndicate down-sampled echo-signal, nDIndicate down-sampled observation noise.
According to compressive sensing theory, target scattering coefficient is solvedIt can be converted into and solve lq(0≤q≤1) optimization problem,
Meet
Further it can be equivalent to solve following optimization problem again,
Wherein, | | | |FFor Frobenius norm, Dθ、DfRespectively orientation angular domain, the down-sampled matrix on step frequency domain, λ
For regularization parameter.
3. compressed sensing based more baseline circular track synthetic aperture radar image-forming methods according to claim 1, feature
Be, using based on rear orientation projection's inverse operator compressed sensing algorithm carry out sub-aperture two-dimensional surface be imaged the step of include:
Step S21: being divided into several sub-apertures for full aperture echo data, obtains the down-sampled echo data S of each sub-apertureD。
Step S22: determine that observing matrix is DG, sparse matrix is unit matrix I.
Step S23: threshold value ratio is γ, and selecting amplitude threshold is γ PSD。
Step S24: the compressed sensing based on rear orientation projection's inverse operator is carried out using soft-threshold iterative algorithm and is rebuild, realizes sub-aperture
Two-dimensional imaging.
4. compressed sensing based more baseline circular track synthetic aperture radar image-forming methods according to claim 1, feature
It is, using the height of compressed sensing algorithm progress sub-aperture to focusing, and further completes the position correction of target two-dimensional coordinate
The step of include:
Step S31: compressed sensing based height is established to focus model.Under the m articles baseline, any one sub-aperture two dimension at
As result T (x ', y ', φ) is
Wherein,S (x, y) is the two-dimentional window function to match with the finite-duration of target, fp
(x,y,zp(x, y)) indicate that the p scattering point that different height is upward at two-dimensional coordinate (x, y), * indicate convolution.
Considering φ=90 °, the two-dimensional imaging result of any one sub-aperture is expressed as,
When height to sampling meet Nyquist criterion when,
It enablesThen
Remember Tm=[Tm], Then
T≈ψf+n
Wherein, n indicates observation noise.
Further considering the down-sampled model of echo data, compressed sensing based height is expressed as to focus model,
TD≈Dψf+nD
Wherein, TDIndicate down-sampled two-dimensional imaging as a result, nDIndicate down-sampled observation noise.
Step S32: determine that observing matrix is D ψ, sparse matrix is unit matrix I.
Step S33: carrying out compressed sensing based reconstruction using base tracking Denoising Algorithm, realizes the height of sub-aperture to focusing.
Step S34: using in the two-dimensional imaging result of sub-aperture pixel coordinate (x ', y ') and target true three-dimension coordinate (x,
Y, z) between relationship, calibrated altitude is to the target two-dimensional coordinate position after focusing, i.e.,
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