A spaceborne squinted high-resolution sliding spotlight SAR frequency domain imaging method

Abstract

This invention provides a frequency domain imaging method for spaceborne large-angle high-resolution sliding convergence SAR, achieving high-precision imaging of spaceborne large-angle high-resolution sliding convergence SAR. This invention solves the problem of nonlinear variation of the Doppler center of each target point with azimuth time by nonlinear deskewing, and solves the problem of inconsistency of azimuth spatial variables of range migration at different range gates by azimuth resampling, thus making up for the shortcomings of the prior art.

Description

Technical Field

[0001] This invention belongs to the field of synthetic aperture radar technology, and particularly relates to a spaceborne large squint high-resolution sliding convergence SAR frequency domain imaging method. Background Technology

[0002] Synthetic Aperture Radar (SAR) is a widely used Earth remote sensing technology with broad application prospects in fields such as disaster early warning, environmental monitoring, and military reconnaissance. With the development of spaceborne SAR, coverage performance and revisit performance have become two important indicators. Spaceborne large-slant-look SAR, through forward or backward beam illumination, can effectively improve the coverage and revisit performance of spaceborne SAR. Meanwhile, sliding-convergence SAR is a typical high-resolution imaging mode of spaceborne SAR. Therefore, spaceborne large-slant-look high-resolution sliding-convergence SAR has become a current research hotspot in spaceborne SAR.

[0003] However, with the improvement of resolution, spaceborne high-resolution sliding convergence SAR imaging with large squint looks faces the following two challenges. First, the rotation of the sliding convergence beam causes the Doppler center of different point targets in the azimuth direction to change nonlinearly with azimuth time. Traditional algorithms ignore the nonlinear change, resulting in spectral aliasing. Second, range migration has two-dimensional spatial variation, and the azimuth spatial variable of range migration is inconsistent at different range gates. Traditional algorithms ignore this inconsistency, leading to range migration correction failure and image defocusing. Summary of the Invention

[0004] To address the aforementioned problems, this invention provides a spaceborne large-slant-view high-resolution sliding convergence SAR frequency domain imaging method, which can achieve high-precision imaging of spaceborne large-slant-view high-resolution sliding convergence SAR.

[0005] A spaceborne high-angle, high-resolution sliding SAR frequency domain imaging method includes the following steps:

[0006] Step S1: Establish a spaceborne large-slant-look sliding SAR signal model;

[0007] Step S2: Preprocessing, including range travel correction and nonlinear azimuth deskewing, to obtain a decoupled, unambiguous azimuth spectrum;

[0008] Step S3: Range migration azimuth spatial variation correction, including azimuth resampling and polynomial compensation. Azimuth resampling removes the inconsistency of the azimuth spatial variable of range migration at different range gates, and polynomial compensation removes the consistent azimuth spatial variable of range migration.

[0009] Step S4: Range migration correction and range compression. The range-oriented CS algorithm is used to achieve range spatial variation correction of range migration and complete range-oriented focusing.

[0010] Step S5: Azimuth compression. The azimuth NCS algorithm is used to remove the azimuth null variable of the focusing parameters, complete the azimuth focusing, and obtain a two-dimensional focused image.

[0011] Preferably, the method of step S1 includes:

[0012] Based on the geometric configuration of the spaceborne large-slant-look sliding SAR, the target's slant range history R(t) a The slant range model can be represented by a Taylor series expansion:

[0013] R(t a )=r0+k1(t a -t p )+k2(t a -t p ) 2 +k3(t a -t p ) 3 +k4(t a -t p ) 4 +k5(t a -t p ) 5

[0014] In the formula, t a For azimuth time, t p Let r0 be the time at which the synthetic aperture of the target is t. p The distance between the radar and the target is given by k1 to k5, which are the coefficients of the Taylor series expansion slant range model. It should be noted that k1 to k5 vary with the target's slant range r0 and the target's synthetic aperture center time t. p change;

[0015] Based on the Taylor series expansion model, the echo signal can be expressed as:

[0016]

[0017] In the formula, u r (·) and u a (·) represent the range and azimuth signal envelopes, respectively, t r Let K be the distance and time, c be the speed of light, and K be the distance and time. r For frequency modulation, λ is the wavelength.

[0018] Preferably, the method of step S2 includes:

[0019] First, the echo is subjected to a range-to-Fourier transform, and phase H1 is compensated to complete the range travel correction:

[0020]

[0021] In the formula, f c For radar carrier frequency, f r For distance frequency, v s For satellite speed, Centered oblique angle;

[0022] Then, compensate for phase H2 to complete the nonlinear azimuth deskewing;

[0023]

[0024] In the formula,

[0025]

[0026] In the formula, f dc1 f dc2 and f dc3 These represent the Doppler center of the target at different azimuth directions as a function of the target's synthetic aperture center at time t. p The first, second, and third rates of change.

[0027] Preferably, the method of step S3 includes:

[0028] After preprocessing, the slant range histories of each target become:

[0029] R(t a )=R0+K2(t a -t p ) 2 +K3(t a -t p ) 3 +K4(t a -t p ) 4 +K5(t a -t p ) 5

[0030] In the formula,

[0031]

[0032] Spatial variation modeling of the slant range coefficients K2 to K5 for different point targets within the scene:

[0033]

[0034]

[0035] In the formula, R ref K is the shortest slant distance from the scene center reference point. 20 ~K 50 K represents the coefficients of each order of the slope distance at the reference point. rij and Kaij K i The j-th derivatives along the range and azimuth directions (i = 2, 3, 4, 5, j = 1, 2);

[0036] First, range compression is performed, phase H3 is compensated, and inverse Fourier transform of the range is performed:

[0037]

[0038] Among them, K r To adjust the frequency;

[0039] Then, azimuth resampling is performed, with the resampling coefficient varying with the range gate. The relationship between azimuth time before and after resampling is as follows:

[0040] t a ′=[1+β1(R0-R ref )]t a

[0041] In the formula, t a ′ represents the resampled azimuth time, and β1 can be expressed as:

[0042]

[0043] After interpolation, a distance-to-Fourier transform is performed, and phase H4 is compensated to restore the chirp signal's frequency modulation.

[0044]

[0045] Finally, perform consistent range migration azimuth spatial variation correction to compensate for phase:

[0046]

[0047] In the formula,

[0048]

[0049] Preferably, the method of step S4 includes:

[0050] First, we obtain the signal expression in the two-dimensional frequency domain:

[0051]

[0052] In the formula, f a For azimuth frequency;

[0053] Apply the above equation to f r Taylor expansion at 0 yields:

[0054]

[0055] In the formula, φ0(R0,t) p ,f a )~φ3(R0,t p ,f a ) represents the Taylor expansion coefficients of each order;

[0056] Then, ignoring the spatial invariance of the cubic term, compensate for phase H6:

[0057]

[0058] Among them, φ3(R) ref ,0,f a ) represents the coefficients of the third-order Taylor expansion at time t p The value when = 0;

[0059] Performing an inverse Fourier transform from distance to direction, the compensated phase H7 is expressed as:

[0060] H7=exp{jπK s (1-γ)(t r -τ ref ) 2}

[0061] In the formula,

[0062]

[0063] In the formula, φ r11 It is the derivative of φ1 along the distance:

[0064]

[0065] After performing a range Fourier transform and compensating for phase H8, an inverse range Fourier transform is performed to complete range migration correction and range compression.

[0066]

[0067] Finally, compensate for the residual phase H9:

[0068]

[0069] Preferably, the method of step S5 includes:

[0070] First, modulate the azimuth phase at f a Taylor expansion at 0 yields:

[0071]

[0072] In the formula, P2 to P5 are the Taylor expansion coefficients of each order, P ij It is P iThe j-th derivative along the azimuth direction, i = 2, 3, 4, 5, j = 0, 1, 2;

[0073] Then, compensate the phase H in the azimuth frequency domain. 10 :

[0074]

[0075] In the formula,

[0076]

[0077] Where μ is a constant and μ≠1;

[0078] After inverse Fourier transform of azimuth, compensated phase H 11 :

[0079] H 11 =exp{jB2(t' a ) 2 +jB3(t' a ) 3 +jB4(t' a ) 4 +jB5(t' a ) 5}

[0080] In the formula,

[0081]

[0082] Perform azimuth Fourier transform and compensate for phase H. 12 :

[0083]

[0084] In the formula,

[0085]

[0086] Finally, an inverse Fourier transform of the azimuth is performed to obtain a two-dimensional focused SAR image.

[0087] The present invention has the following beneficial effects:

[0088] This invention provides a frequency domain imaging method for spaceborne large-angle, high-resolution sliding convergence SAR, achieving high-precision imaging of spaceborne large-angle, high-resolution sliding convergence SAR. This invention addresses the problem of nonlinear variation of the Doppler center of targets at various azimuth points with azimuth time through nonlinear deskewing, and solves the problem of inconsistency of azimuth spatial variables in range migration at different range gates through azimuth resampling, thus overcoming the shortcomings of existing technologies. Attached Figure Description

[0089] Figure 1A flowchart of a spaceborne large-slant-view high-resolution sliding SAR frequency domain imaging method provided by the present invention;

[0090] Figure 2 This is the imaging result of a high-resolution sliding convergence SAR point target on a spaceborne, large-slant-viewing surface. Detailed Implementation

[0091] To enable those skilled in the art to better understand the present application, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings.

[0092] like Figure 1 As shown, a spaceborne large-slant-look high-resolution sliding SAR frequency domain imaging method includes the following steps:

[0093] S1: Establish a spaceborne large-slant-look sliding SAR signal model;

[0094] Based on the geometric configuration of the spaceborne large-slant-look sliding SAR, the target's slant range history R(t) a The slant range model can be represented by a Taylor series expansion:

[0095] R(t a )=r0+k1(t a -t p )+k2(t a -t p ) 2 +k3(t a -t p ) 3 +k4(t a -t p ) 4 +k5(t a -t p ) 5

[0096] In the formula, t a For azimuth time, t p Let r0 be the time at which the synthetic aperture of the target is t. p The distance between the radar and the target is given by k1 to k5, which are the coefficients of the Taylor series expansion slant range model. It should be noted that k1 to k5 vary with the target's slant range r0 and the target's synthetic aperture center time t. p change.

[0097] Based on the Taylor series expansion model, the echo signal can be expressed as:

[0098]

[0099] In the formula, u r (·) and u a(·) represent the range and azimuth signal envelopes, respectively, t r Let K be the distance and time, c be the speed of light, and K be the distance and time. r For frequency modulation, λ is the wavelength.

[0100] S2: Preprocessing, including distance travel correction and nonlinear azimuth deslant, to obtain a decoupled, unambiguous azimuth spectrum.

[0101] First, the echo is subjected to a range-to-Fourier transform, and the phase H1 is compensated to complete the range travel correction.

[0102]

[0103] In the formula, f c For radar carrier frequency, f r For distance frequency, v s For satellite speed, Centered oblique angle.

[0104] Then, phase compensation H2 is performed to complete the nonlinear azimuth deslant removal.

[0105]

[0106] In the formula,

[0107]

[0108] In the formula, f dc1 f dc2 and f dc3 These represent the Doppler center of the target at different azimuth directions as a function of the target's synthetic aperture center at time t. p The first, second, and third rates of change.

[0109] S3: Range migration azimuth spatial variation correction, including azimuth resampling and polynomial compensation. Azimuth resampling removes the inconsistency of azimuth spatial variables in range migration at different range gates, and polynomial compensation removes the consistent azimuth spatial variables in range migration.

[0110] To correct for the azimuth spatial variation of range migration, its spatial variation needs to be analyzed first. After preprocessing, the slant range history of each target becomes:

[0111] R(t a )=R0+K2(t a -t p ) 2 +K3(t a -t p ) 3 +K4(t a -t p ) 4 +K5(t a -tp ) 5

[0112] In the formula,

[0113]

[0114] Spatial variation modeling of the slant range coefficients K2 to K5 for different point targets within the scene:

[0115]

[0116]

[0117] In the formula, R ref K is the shortest slant distance from the scene center reference point. 20 ~K 50 K represents the coefficients of each order of the slope distance at the reference point. rij and K aij K i The j-th derivatives along the range and azimuth directions (i = 2, 3, 4, 5, j = 1, 2).

[0118] First, distance compression is performed, phase H3 is compensated, and inverse Fourier transform of the distance is performed.

[0119]

[0120] Among them, K r To adjust the frequency;

[0121] Then, azimuth resampling is performed, with the resampling coefficient varying with the range gate. The relationship between azimuth time before and after resampling is as follows:

[0122] t a ′=[1+β1(R0-R ref )]t a

[0123] In the formula, t a ′ represents the resampled azimuth time, and β1 can be expressed as:

[0124]

[0125] After interpolation, a distance-to-Fourier transform is performed, and phase H4 is compensated to restore the chirp signal's frequency modulation.

[0126]

[0127] Finally, perform consistent range migration azimuth spatial variation correction to compensate for phase:

[0128]

[0129] In the formula,

[0130]

[0131] It is worth noting that after completing the spatial variation correction for range migration azimuth, the coefficient K 20 ~K 50 The time t at the center of the synthetic aperture of the target p And the value of the shortest slant distance R0 will change.

[0132] S4: Range migration correction and range compression. The range-oriented CS algorithm is used to achieve range spatial variation correction of range migration and complete range-oriented focusing.

[0133] First, we obtain the signal expression in the two-dimensional frequency domain:

[0134]

[0135] In the formula, f a This represents the azimuth frequency.

[0136] Apply the above equation to f r Taylor expansion at 0 yields:

[0137]

[0138] In the formula, φ0(R0,t) p ,f a )~φ3(R0,t p ,f a ) represents the Taylor expansion coefficients of each order.

[0139] Then, ignoring the spatial invariance of the cubic term, compensate for phase H6:

[0140]

[0141] Among them, φ3(R) ref ,0,f a ) represents the coefficients of the third-order Taylor expansion at time t p The value when = 0;

[0142] Performing an inverse Fourier transform from distance to direction, the compensated phase H7 is expressed as:

[0143] H7=exp{jπK s (1-γ)(t r -t ref ) 2}

[0144] In the formula,

[0145]

[0146] In the formula, φ r11 It is the derivative of φ1 along the distance:

[0147]

[0148] After performing a range Fourier transform and compensating for phase H8, an inverse range Fourier transform is performed to complete range migration correction and range compression.

[0149]

[0150] Finally, compensate for the residual phase H9:

[0151]

[0152] S5: Azimuth compression, using the azimuth-oriented NCS algorithm to remove azimuth null variables of the focusing parameters, completes azimuth focusing, and obtains a two-dimensional focused image.

[0153] First, modulate the azimuth phase at f a Taylor expansion at 0 yields:

[0154]

[0155] In the formula, P2 to P5 are the Taylor expansion coefficients of each order, P ij It is P i The j-th derivative along the azimuth direction, i = 2, 3, 4, 5, j = 0, 1, 2.

[0156] Then, compensate the phase H in the azimuth frequency domain. 10 :

[0157]

[0158] In the formula,

[0159]

[0160] Where μ is a constant and μ≠1;

[0161] After inverse Fourier transform of azimuth, compensated phase H 11 :

[0162] H 11 =exp{jB2(t' a ) 2 +jB3(t' a ) 3 +jB4(t' a ) 4 +jB5(t' a ) 5}

[0163] In the formula,

[0164]

[0165] Perform azimuth Fourier transform and compensate for phase H. 12 :

[0166]

[0167] In the formula,

[0168]

[0169] Finally, an inverse Fourier transform of the azimuth is performed to obtain a two-dimensional focused SAR image.

[0170] Example:

[0171] The effectiveness of the present invention will be further illustrated below through a simulation experiment of a high-resolution sliding convergence SAR point target on a spaceborne large-angle squint.

[0172] The simulation parameters of spaceborne high-angle-view high-resolution sliding SAR are shown in Table 1.

[0173] Table 1 Simulation parameters of spaceborne high-slant-look high-resolution sliding SAR

[0174]

[0175] Imaging was performed using the spaceborne large squint high-resolution sliding SAR frequency domain imaging method proposed in this invention, and the imaging results are as follows: Figure 2 As shown in Table 2, the resolution, peak sidelobe ratio, and integral sidelobe ratio of the target points at the top left, center, and bottom right were evaluated.

[0176] Table 1. Evaluation results of point targets using spaceborne high-resolution sliding convergence SAR with large squint.

[0177]

[0178] Therefore, this invention provides a frequency domain imaging method for spaceborne large-angle, high-resolution sliding convergence SAR, achieving high-precision imaging of spaceborne large-angle, high-resolution sliding convergence SAR. This invention addresses the problem of nonlinear variation of the Doppler center of targets at various azimuth points with azimuth time through nonlinear deskewing, and solves the problem of inconsistency of azimuth spatial variables in range migration at different range gates through azimuth resampling, thus overcoming the shortcomings of existing technologies.

[0179] In summary, the above are merely preferred embodiments of the present invention and are not intended to limit the scope of protection of the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A spaceborne large-slant-look high-resolution sliding-convergence SAR frequency domain imaging method, characterized in that, Includes the following steps: Step S1: Establish a spaceborne large-slant-look sliding SAR signal model; Step S2: Preprocessing, including range travel correction and nonlinear azimuth deskewing, to obtain a decoupled, unambiguous azimuth spectrum; Step S3: Range migration azimuth spatial variation correction, including azimuth resampling and polynomial compensation. Azimuth resampling removes the inconsistency of the azimuth spatial variable of range migration at different range gates, and polynomial compensation removes the consistent azimuth spatial variable of range migration. Step S4: Range migration correction and range compression. The range-oriented CS algorithm is used to achieve range spatial variation correction of range migration and complete range-oriented focusing. Step S5: Azimuth compression. The azimuth NCS algorithm is used to remove the azimuth null variable of the focusing parameters, complete the azimuth focusing, and obtain a two-dimensional focused image.

2. The spaceborne large-slant-look high-resolution sliding-convergence SAR frequency domain imaging method as described in claim 1, characterized in that, The method in step S1 includes: Based on the geometric configuration of the spaceborne large-slant-look sliding SAR, the target's slant range history The slant distance model is represented by Taylor series expansion: In the formula, For location and time, The target synthetic aperture center time, for The distance between the radar and the target at any given time. ~ These are the coefficients of each order in the Taylor series expansion slant distance model; it should be noted that... ~ With the target slant distance and the target's synthetic aperture center time change; Based on the Taylor series expansion model, the echo signal can be expressed as: In the formula, and These are the range and azimuth signal envelopes, respectively. For distance and time, At the speed of light, To adjust the frequency, λ is the wavelength.

3. The spaceborne large-slant-view high-resolution sliding convergence SAR frequency domain imaging method as described in claim 2, characterized in that, The method in step S2 includes: First, the echo is subjected to a range-to-Fourier transform, and phase compensation is performed. Complete distance walking correction: In the formula, For radar carrier frequency, For distance frequency, For satellite speed, Centered oblique angle; Then, compensate for the phase. Complete the nonlinear orientation deslant removal; In the formula, In the formula, , and These represent the Doppler center times of different point targets in different azimuth directions, as a function of the target's synthetic aperture center. The first, second, and third rates of change.

4. The spaceborne large-slant-view high-resolution sliding convergence SAR frequency domain imaging method as described in claim 3, characterized in that, The method in step S3 includes: After preprocessing, the slant range histories of each target become: In the formula, Slant range coefficients of different point targets within the scene ~ Spatial variation modeling: In the formula, The shortest slant distance to the scene center reference point. ~ These are the coefficients for the slope distance of the reference point. and They are respectively Along the distance and azimuth directions First derivative, , ; First, perform distance compression and phase compensation. And perform inverse Fourier transform of the distance: in, To adjust the frequency; Then, azimuth resampling is performed, with the resampling coefficient varying with the range gate; the relationship between azimuth time before and after resampling is as follows: In the formula, This represents the azimuth time after resampling. It can be represented as: After interpolation, a distance-to-Fourier transform is performed, and phase compensation is applied. To restore the chirp signal's modulation frequency; Finally, perform consistent range migration azimuth spatial variation correction to compensate for phase: In the formula, 。 5. The spaceborne large-slant-view high-resolution sliding convergence SAR frequency domain imaging method as described in claim 4, characterized in that, The method in step S4 includes: First, we obtain the signal expression in the two-dimensional frequency domain: In the formula, For azimuth frequency; The above formula is in Taylor expansion yields: In the formula, ~ These are the Taylor expansion coefficients of each order; Then, ignoring the spatial invariance of the cubic term, the phase is compensated. : in, Indicates the third-order Taylor expansion coefficients in The value at time; Perform inverse Fourier transform from distance to compensate for phase. Represented as: In the formula, In the formula, yes Derivative along the distance: Perform distance Fourier transform and compensate for phase. Then, an inverse Fourier transform of the distance is performed to complete the distance migration correction and distance compression; Finally, compensate for the residual phase. : 。 6. The spaceborne large-slant-look high-resolution sliding convergence SAR frequency domain imaging method as described in claim 5, characterized in that, The method in step S5 includes: First, modulate the azimuth phase at Taylor expansion yields: In the formula, ~ Here are the Taylor expansion coefficients of each order. yes Along the azimuth direction First derivative, , ; Then, phase compensation is performed in the azimuth frequency domain. : In the formula, in, It is a constant, and ; After inverse Fourier transform of azimuth, phase compensation : In the formula, Perform azimuth Fourier transform and compensate for phase. : In the formula, Finally, an inverse Fourier transform of the azimuth is performed to obtain a two-dimensional focused SAR image.

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