SAR imaging method based on actual trajectory of large-angle strabismus two-dimensional space variation motion compensation

Abstract

This invention relates to a large-slant-angle two-dimensional spatially variable motion-compensated SAR imaging method based on actual trajectories, comprising: acquiring echo data s0(t) based on a pre-constructed nonlinear trajectory geometric model of the carrier platform of a large-slant-angle SAR imaging system. r ,η); for echo data s0(t r Range pulse compression is performed on η) to obtain the range frequency domain echo signal s1(f) after range pulse compression. r ,η); for the range frequency domain echo signal s1(f after range pulse compression) r Non-space phase compensation is performed on η) to obtain the compensated signal s2(f) r ,η); for the compensated signal s2(f r Range-directed spatial correction is performed on η) to obtain the corrected range-frequency echo signal s7(f) r ,η); for the corrected range-frequency echo signal s7(f r Azimuth spatial variation correction is performed on the azimuth echo signal (η), and the corrected azimuth echo signal is converted into a SAR image through a two-dimensional Fourier transform. This scheme eliminates the spatial variation of the envelope and phase along the azimuth direction, corrects the motion error of the azimuth spatial variation, and achieves more accurate imaging focusing, exhibiting high precision and efficiency.

Description

Technical Field

[0001] This invention relates to the field of airborne synthetic aperture radar technology, and more specifically, to a large-slant-look two-dimensional spatially variable motion-compensated SAR imaging method based on actual trajectories. Background Technology

[0002] Airborne Synthetic Aperture Radar (SAR) systems can acquire high-resolution radar images and scattering information of important areas, attracting widespread attention and application in both military and civilian fields. With the diversification of application requirements, SAR systems need to operate in a high-slant-out mode to adapt to different monitoring tasks. Compared with traditional wide-slant-out or narrow-slant-out modes, high-slant-out SAR systems can effectively monitor larger areas and acquire information about the foreground region of interest in advance. Furthermore, high-slant-out SAR systems offer greater flexibility, faster response times, and higher revisit frequencies, providing significant advantages for SAR applications in complex environments. Due to factors such as airflow, airborne SAR systems struggle to maintain uniform straight-line flight, resulting in motion errors. Especially in high-slant-out mode, the two-dimensional spatial variation effect of motion errors is more pronounced, significantly impacting the focusing effect of the algorithm and severely affecting image quality, rendering conventional motion compensation algorithms unsuitable. Accurate spatial variation motion compensation algorithms are crucial for high-slant-out airborne SAR imaging. However, traditional two-step motion compensation algorithms primarily address non-slant-variable and spatial variation motion errors in the range direction, failing to compensate for azimuth spatial variation motion errors. Although sub-aperture algorithms exist to compensate for low-order azimuth spatial variation motion errors, this increases the complexity of the algorithm and makes the compensation accuracy insufficient. Summary of the Invention

[0003] To address the aforementioned problems in the existing technology, this invention provides a large-slant-view two-dimensional spatially variable motion-compensated SAR imaging method based on actual trajectories.

[0004] According to a first aspect of the present invention, a large-slant-angle two-dimensional spatially variable motion-compensated SAR imaging method based on actual trajectories is provided, the method comprising:

[0005] Echo data s0(t) is obtained based on the nonlinear trajectory geometric model of the carrier platform of the pre-constructed large squint SAR imaging system. r ,η);

[0006] For the echo data s0(t) r Range pulse compression is performed on η) to obtain the range frequency domain echo signal s1(f) after range pulse compression. r ,η);

[0007] The range frequency domain echo signal s1(f) after range pulse compressionr Non-space phase compensation is performed on η) to obtain the compensated signal s2(f) r ,η);

[0008] For the compensated signal s2(f r Range-directed spatial correction is performed on η) to obtain the corrected range-frequency echo signal s7(f) r ,η);

[0009] The corrected range-frequency domain echo signal s7(f r Azimuth spatial variation correction is performed on η) to obtain the corrected azimuth echo signal s8(f) r ,η);

[0010] The corrected azimuth echo signal s8(f) is transformed using a two-dimensional Fourier transform. r ,η) is converted into a SAR image.

[0011] Optionally, the step of processing the echo data s0(t) r Range pulse compression is performed on η) to obtain the range frequency domain echo signal s1(f) after range pulse compression. r ,η), including:

[0012] For the echo data s0(t) r Perform a range-to-Fourier transform on η) to obtain the range-frequency echo signal s0(f) r ,η);

[0013] The range frequency domain echo signal s0(f) is processed by a pre-constructed range pulse compression function H1. r Range pulse compression is performed on η) to obtain the range frequency domain echo signal s1(f) after range pulse compression. r ,η).

[0014] Optionally, the range frequency domain echo signal s1(f) after range pulse compression r Non-space phase compensation is performed on η) to obtain the compensated signal s2(f) r ,η), including:

[0015] Construct a non-empty variable phase compensation function H2(f) r ,η);

[0016] Through the non-vacuum phase compensation function H2(f) r ,η) for the range frequency domain echo signal s1(f after range pulse compression r Non-space phase compensation is performed on η) to obtain the compensated signal s2(f) r ,η).

[0017] Optionally, the compensation of the signal s2(f) r Range-directed spatial correction is performed on η) to obtain the corrected range-frequency echo signal s7(f) r ,η), including:

[0018] The compensated signal s2(f) is processed by a pre-constructed function H3. r Reconstructing η) yields the range-frequency echo signal s3(f) r ,η);

[0019] For the range frequency domain echo signal s3(f r Perform a range-to-inverse Fourier transform on η) to obtain the range-time domain echo signal s3(t) r ,η);

[0020] The echo signal s3(t) in the distance-time domain is filtered by a pre-constructed pre-filter function H4. r The signal s4(t) is processed to obtain the time-domain echo signal s4(t) in the distance domain. r ,η);

[0021] For the distance-time domain echo signal s4(t) r Perform a range-to-Fourier transform on η) to obtain the range-frequency echo signal s4(f) r ,η);

[0022] The echo signal s4(f) in the distance frequency domain is scaled by a pre-constructed frequency domain scaling function H5. r The signal s5(f) is processed by η to obtain the echo signal s5(f) in the range frequency domain. r ,η);

[0023] For the echo signal s5(f in the range frequency domain) r Perform a range-to-inverse Fourier transform on η) to obtain the range-time domain echo signal s5(t) r ,η);

[0024] The distance-time domain echo signal s5(t) is processed by a pre-constructed compensation function H6. r The signal s6(t) is processed by η to obtain the time-domain echo signal s6(t). r ,η);

[0025] The echo signal s6(t) in the distance-time domain r Perform a range-to-Fourier transform on η) to obtain the corrected range-frequency domain echo signal s7(f) r ,η).

[0026] Optionally, the pre-constructed pre-filtering function H4 refers to the following formula:

[0027]

[0028] Where exp(·) is the exponential function, j is the imaginary unit, and γ is the range modulation frequency. η is the scaling factor, and η is the azimuth time of the carrier platform of the large squint SAR imaging system.

[0029] The scaling factor For reference:

[0030]

[0031] in, Indicates |r P (η)|find|r P |in|r c |Partial derivative at a point,| |Denotes the modulo operation, θ c r is the oblique view from the center point C of the scene to the carrier platform. c Let r be the slant distance vector from the center point C of the scene to the carrier platform. P Let P be the oblique angle from any point P in the scene to the carrier platform, and let [x] be the position of the antenna phase center of the carrier platform of the large oblique-looking SAR imaging system. a (η),y a (η),z a [η], where h is the height of the carrier platform of the large squint SAR imaging system.

[0032] Optionally, the pre-constructed frequency domain scaling function H5 refers to the following formula:

[0033]

[0034] Among them, f r For distance frequency.

[0035] Optionally, the pre-constructed compensation function H6 refers to the following formula:

[0036]

[0037] Among them, f c For carrier frequency.

[0038] Optionally, the corrected range-frequency echo signal s7(f) r Azimuth spatial variation correction is performed on η) to obtain the corrected azimuth echo signal. include:

[0039] Define virtual orientation time

[0040] The virtual orientation time is obtained through SINC interpolation. Substitute the corrected range-frequency echo signal s7(f) r Azimuth spatial variation correction is performed on η) to obtain the corrected azimuth echo signal.

[0041] Optionally, the virtual orientation time Refer to the following formula:

[0042]

[0043] Among them, f r f is the distance frequency. c For carrier frequency, As a scaling factor, This is the resampling factor;

[0044] The resampling factor Refer to the following formula:

[0045]

[0046] in, Indicates |r P (η)|Find θ at θ c The partial derivatives of θ, || denote the modulo operation, θ c r is the oblique view from the center point C of the scene to the carrier platform. c Let r be the slant distance vector from the center point C of the scene to the carrier platform. P Let P be the oblique angle from any point P in the scene to the carrier platform, and let [x] be the position of the antenna phase center of the carrier platform of the large oblique-looking SAR imaging system. a (η),y a (η),z a [η], where h is the height of the carrier platform of the large squint SAR imaging system.

[0047] The technical solution provided by this invention may include the following beneficial effects:

[0048] Through the above technical solution, a nonlinear trajectory geometric model of the carrier platform of the large squint SAR imaging system was established based on the real flight path. The spatial variation of the envelope and phase along the azimuth direction was eliminated by non-spatial phase compensation and spatial correction, and the motion error of azimuth spatial variation was accurately corrected. This greatly alleviated the influence of the two-dimensional spatial variation of motion error on the imaging focusing effect, and achieved more accurate focusing with higher precision and efficiency.

[0049] Other features and advantages of the present invention will be described in detail in the following detailed description section. Attached Figure Description

[0050] The accompanying drawings are provided to further illustrate the invention and form part of the specification. They are used together with the following detailed description to explain the invention, but do not constitute a limitation thereof. In the drawings:

[0051] Figure 1 This is a flowchart illustrating a large-slant-angle two-dimensional spatially variable motion-compensated SAR imaging method based on actual trajectories, according to an exemplary embodiment.

[0052] Figure 2 This is a schematic diagram of the nonlinear trajectory geometry model of a pre-constructed large-angle SAR imaging system platform according to an exemplary embodiment.

[0053] Figure 3a This is a schematic diagram of the X-axis motion error of a carrier platform for a large squint SAR imaging system according to an exemplary embodiment.

[0054] Figure 3b This is a schematic diagram of the Y-axis motion error of a carrier platform for a large squint SAR imaging system according to an exemplary embodiment.

[0055] Figure 3c This is a schematic diagram of the Z-axis motion error of a carrier platform for a large squint SAR imaging system according to an exemplary embodiment.

[0056] Figure 4a This is a schematic diagram illustrating the imaging result of the coprime factor algorithm at the upper left edge of the scene according to an exemplary embodiment.

[0057] Figure 4b This is a schematic diagram illustrating the imaging result of the coprime factor algorithm at the center point of a scene according to an exemplary embodiment.

[0058] Figure 4c This is a schematic diagram illustrating the imaging result of the coprime factor algorithm at the upper right edge point of a scene according to an exemplary embodiment.

[0059] Figure 5a This is a schematic diagram illustrating the imaging result of the present invention at the upper left edge of a scene according to an exemplary embodiment.

[0060] Figure 5b This is a schematic diagram illustrating the imaging result of the present invention at the center point of a scene according to an exemplary embodiment.

[0061] Figure 5c This is a schematic diagram illustrating the imaging result of the present invention at the upper right edge point of a scene according to an exemplary embodiment.

[0062] Figure 6a This is a schematic diagram illustrating the verification results of a coprime factor algorithm according to an exemplary embodiment.

[0063] Figure 6b This is a schematic diagram illustrating the verification results of the present invention according to an exemplary embodiment. Detailed Implementation

[0064] To facilitate understanding of the present invention, a brief description of the prior art and the inventive concept of the present invention will be provided first.

[0065] Among existing motion compensation algorithms, the two-step motion compensation algorithm is the most widely used. However, this traditional algorithm, based on the beam center assumption, only compensates for spatially variable motion errors in the range direction, while ignoring spatially variable motion errors in the azimuth direction. To compensate for azimuth spatially variable motion errors, researchers have proposed various sub-aperture algorithms, including sub-aperture terrain correction, aperture-dependent algorithms, and Doppler spectrum segmentation algorithms. However, in large squint mode, existing sub-aperture algorithms face two main problems: first, they require a large amount of computation, which not only increases processing time but also consumes more resources; second, due to the approximate handling of motion errors, the compensation accuracy of these algorithms is often insufficient, which directly affects the imaging quality. To address these problems, this invention proposes a large squint two-dimensional spatially variable motion compensation SAR imaging method based on actual trajectories.

[0066] Figure 1 This is a flowchart illustrating a large-squint-angle two-dimensional spatially variable motion-compensated SAR imaging method based on actual trajectories, according to an exemplary embodiment. Figure 1 As shown, the method includes the following steps.

[0067] S101. Obtain echo data s0(t) based on the pre-constructed nonlinear trajectory geometric model of the carrier platform of the large squint SAR imaging system. r ,η).

[0068] Understandable, Figure 2 This is a schematic diagram of the nonlinear trajectory geometry model of a pre-constructed large-slant-look SAR imaging system platform according to an exemplary embodiment, such as... Figure 2 As shown, due to factors such as airflow, the carrier platform moves along a nonlinear trajectory in the xOyz coordinate system. Synthetic Aperture Radar (SAR) has a very large oblique angle of view. The azimuth time of the platform is η, and the position of the antenna phase center (APC) of the carrier platform in the pre-constructed large oblique-view SAR imaging system is represented as [x...]. a (η),y a (η),z a (η)], the coordinates of the scene center point C are (x c ,y c Then the instantaneous slant range history of any point P in the scene can be represented as follows:

[0069]

[0070] The coordinates of point P (x) p ,y p This can be represented as:

[0071]

[0072] The coordinates of point P (x) p ,y p This can be represented as:

[0073]

[0074] Where | represents the modulo operation, θ c The angled view from the scene center point C to the carrier platform, r c Let r be the slant distance vector from the scene center point C to the carrier platform. P Let θ be the oblique angle from any point P in the scene to the carrier platform, and θ be the oblique angle from the center point P in the scene to the carrier platform. The antenna phase center position of the carrier platform in the large oblique-looking SAR imaging system is represented as [x...]. a (η),y a (η),z a [η], where h is the height of the carrier platform of the large squint SAR imaging system.

[0075] S102, regarding echo data s0(t) r Range pulse compression is performed on η) to obtain the range frequency domain echo signal s1(f) after range pulse compression. r ,η).

[0076] Optionally, S102 may include:

[0077] For echo data s0(t) r Perform a range-to-Fourier transform on η) to obtain the range-frequency echo signal s0(f) r ,η);

[0078] The range frequency domain echo signal s0(f) is processed by a pre-constructed range pulse compression function H1. r Range pulse compression is performed on η) to obtain the range frequency domain echo signal s1(f) after range pulse compression. r ,η).

[0079] Specifically, the range frequency domain echo signal s1(f) after range pulse compression r The formula for η can be referenced as follows:

[0080]

[0081] Among them, tr It is the distance of time, f r It is the distance frequency, the distance pulse compression function. γ is the distance modulation frequency, exp(·) is the exponential function, j is the imaginary unit, c is the speed of light, and f c For carrier frequency.

[0082] S103, Range frequency domain echo signal s1(f) after range pulse compression r Non-space phase compensation is performed on η) to obtain the compensated signal s2(f) r ,η).

[0083] Optionally, S103 may include:

[0084] Construct a non-empty variable phase compensation function H2(f) r ,η);

[0085] Through the non-space-variable phase compensation function H2(f) r ,η) for the range frequency domain echo signal s1(f after range pulse compression r Non-space phase compensation is performed on η) to obtain the compensated signal s2(f) r ,η).

[0086] Specifically, the non-space variable phase compensation function H2(f r The formula for η can be referenced as follows:

[0087]

[0088] The compensated signal s2(f r The formula for η can be referenced as follows:

[0089]

[0090] in,

[0091] S104, for the compensated signal s2(f) r Range-directed spatial correction is performed on η) to obtain the corrected range-frequency echo signal s7(f) r ,η).

[0092] Optionally, S104 may include:

[0093] The compensated signal s2(f) is processed by a pre-constructed function H3. r Reconstructing η) yields the range-frequency echo signal s3(f) r ,η);

[0094] For the range frequency domain echo signal s3(f rPerform a range-to-inverse Fourier transform on η) to obtain the range-time domain echo signal s3(t) r ,η);

[0095] The echo signal s3(t) in the time domain is filtered by a pre-constructed pre-filter function H4. r The signal s4(t) is processed to obtain the time-domain echo signal s4(t) in the distance domain. r ,η);

[0096] For the echo signal s4(t) in the distance-time domain r Perform a range-to-Fourier transform on η) to obtain the range-frequency echo signal s4(f) r ,η);

[0097] The echo signal s4(f) in the distance frequency domain is scaled using a pre-constructed frequency domain scaling function H5. r The signal s5(f) is processed by η to obtain the echo signal s5(f) in the range frequency domain. r ,η);

[0098] For the echo signal s5(f) in the range frequency domain r Perform a range-to-inverse Fourier transform on η) to obtain the range-time domain echo signal s5(t) r ,η);

[0099] The echo signal s5(t) in the distance-time domain is compensated by a pre-constructed compensation function H6. r The signal s6(t) is processed by η to obtain the time-domain echo signal s6(t). r ,η);

[0100] For the echo signal s6(t) in the distance-time domain r Perform a range-to-Fourier transform on η) to obtain the corrected range-frequency domain echo signal s7(f) r ,η).

[0101] Specifically, the range-frequency echo signal s3(f r The formula for η can be referenced as follows:

[0102]

[0103] Among them, the pre-built functions

[0104] Echo signal s4(t) in the distance-time domain r The formula for η can be referenced as follows:

[0105] s4(f r ,η)=s3(t r ,η)×H4;

[0106] The pre-constructed pre-filter function H4 is based on the following formula:

[0107]

[0108] Where exp(·) is the exponential function, j is the imaginary unit, and γ is the range modulation frequency. η is the scaling factor, and η is the azimuth time of the carrier platform of the large squint SAR imaging system.

[0109] Scale factor For reference:

[0110]

[0111] in, Indicates |r P (η)|find|r P |in|r c Partial derivative at a point;

[0112] Echo signal s5(f) in the distance frequency domain r The formula for η can be referenced as follows:

[0113] s5(f r ,η)=s4(t r ,η)×H5;

[0114] The pre-constructed frequency domain scaling function H5 is referenced by the following formula:

[0115]

[0116] Among them, f r For distance frequency;

[0117] Echo signal s6(t) in the distance-time domain r The formula for η can be referenced as follows:

[0118] s6(t r ,η)=s5(t r ,η)×H6;

[0119] The pre-constructed compensation function H6 is based on the following formula:

[0120]

[0121] S105, For the corrected range-frequency domain echo signal s7(f r Azimuth spatial variation correction is performed on η) to obtain the corrected azimuth echo signal.

[0122] Optionally, S105 may include:

[0123] Define virtual orientation time

[0124] Virtual orientation time is obtained through SINC interpolation. Substituting the corrected range-frequency echo signal s7(f) r Azimuth spatial variation correction is performed on η) to obtain the corrected azimuth echo signal.

[0125] It is understandable that SINC interpolation refers to the Whittaker-Shannon interpolation formula.

[0126] Specifically, virtual location time Refer to the following formula:

[0127]

[0128] Among them, f r f is the distance frequency. c For carrier frequency, As a scaling factor, This is the resampling factor;

[0129] Resampling factor Refer to the following formula:

[0130]

[0131] in, Indicates |r P (η)|Find θ at θ c The partial derivatives of .

[0132] S106. The corrected azimuth echo signal is converted using a two-dimensional Fourier transform. Convert to SAR image.

[0133] In one embodiment, a simulation experiment is conducted according to the present invention using the parameter information in Table 1, as shown in Table 1 below:

[0134] Table 1

[0135]

[0136] Figure 3a This is a schematic diagram of the X-axis motion error of a carrier platform for a large squint SAR imaging system according to an exemplary embodiment. Figure 3b This is a schematic diagram of the Y-axis motion error of a carrier platform for a large squint SAR imaging system according to an exemplary embodiment. Figure 3cThis is a schematic diagram of the Z-axis motion error of a carrier platform for a large squint SAR imaging system according to an exemplary embodiment. The motion error after applying the present invention is as follows: Figure 3a , Figure 3b and Figure 3c As shown.

[0137] Figure 4a This is a schematic diagram illustrating the imaging result of the coprime factor algorithm at the upper left edge of a scene according to an exemplary embodiment. Figure 4b This is a schematic diagram illustrating the imaging result of the coprime factor algorithm at the center point of a scene according to an exemplary embodiment. Figure 4c This is a schematic diagram illustrating the imaging result of the coprime factor algorithm at the upper right edge of a scene according to an exemplary embodiment. Figure 5a This is a schematic diagram illustrating the imaging result of the present invention at the upper left edge of a scene according to an exemplary embodiment. Figure 5b This is a schematic diagram illustrating the imaging result of the present invention at the center point of a scene according to an exemplary embodiment. Figure 5c This is a schematic diagram illustrating the imaging result of the present invention at the upper right edge point of a scene according to an exemplary embodiment. Figure 6a This is a schematic diagram illustrating the verification results of the coprime factor algorithm according to an exemplary embodiment. Figure 6b This is a schematic diagram illustrating the verification results of the present invention according to an exemplary embodiment. Figure 4a , Figure 4b , Figure 4c , Figure 5a , Figure 5b and Figure 5c The vertical axis represents distance, and the horizontal axis represents direction. According to the above illustration, for scene edge points, the contour map obtained using the coprime factor algorithm shows adhesion between the azimuth main lobe and side lobes, indicating defocusing of the edge point targets. This demonstrates that existing technologies lack sufficient accuracy in compensating for motion errors, while the contour map obtained using this invention clearly separates the main lobe and side lobes, resulting in better visual effects. The better image quality at edge points indicates that this invention can effectively compensate for spatially varying motion errors. Figure 6a and Figure 6b As shown, the invention was verified using actual measurement data, proving its effectiveness.

[0138] Airborne platforms are significantly affected by external factors such as airflow, making motion errors difficult to avoid. This invention significantly improves the imaging quality of large-angle-view airborne SAR by accurately compensating for two-dimensional spatially varied motion errors, thereby enhancing system stability and robustness. The large angle of view increases the coverage of the airborne radar, and the precise motion compensation algorithm ensures high-quality imaging of this large-angle-view data, enabling the acquisition of broader reconnaissance information and providing reliable data for decision-making. In the field of geological exploration, this invention helps obtain high-resolution geological information over a wider geographical area, improving exploration results and efficiency. This invention supports resource remote sensing monitoring, enabling broader regional coverage, facilitating resource remote sensing monitoring, ensuring the quality of remote sensing data, and providing reliable data for resource management. This invention can also acquire disaster information over a wider range, facilitating timely early warning and enhancing natural disaster early warning capabilities. This invention significantly improves the imaging performance and adaptability of large-angle-view airborne SAR, has broad application prospects in geology, resources, and disaster fields, and is of great significance to the development of airborne radar technology.

[0139] The preferred embodiments of the present invention have been described in detail above with reference to the accompanying drawings. However, the present invention is not limited to the specific details of the above embodiments. Within the scope of the technical concept of the present invention, various simple modifications can be made to the technical solution of the present invention, and these simple modifications all fall within the protection scope of the present invention.

[0140] It should also be noted that the various specific technical features described in the above specific embodiments can be combined in any suitable way without contradiction. In order to avoid unnecessary repetition, the present invention will not describe the various possible combinations separately.

[0141] Furthermore, various different embodiments of the present invention can be combined in any way, as long as they do not violate the spirit of the present invention, they should also be regarded as the content disclosed by the present invention.

Claims

1. A large squint two-dimensional space-variant motion compensation SAR imaging method based on actual trajectory, characterized in that, The method comprises: According to a pre-constructed nonlinear trajectory geometric model of a carrier platform of a large-oblique SAR imaging system, echo data is acquired ; wherein, is an azimuth time of the carrier platform of the large-oblique SAR imaging system, is a range fast time; performing range pulse compression on the echo data to obtain a range pulse compressed range frequency domain echo signal ; wherein, is a range frequency; the range pulse-compressed range frequency domain echo signal performing non-vanishing phase compensation to obtain a compensated signal ; to the compensated signal performing range-dependent correction on the distance domain echo signal to obtain a corrected distance domain echo signal ; the corrected range frequency domain echo signal azimuthally varying correction is performed to obtain a corrected azimuth echo signal ; wherein, is a virtual azimuth time; by two-dimensional Fourier transformation, the corrected azimuthal echo signals are converted into a SAR image; The method comprises the following steps: The azimuth direction is corrected to obtain a corrected azimuth echo signal The method comprises the following steps: Defining virtual orientation time ; The virtual azimuth time is corrected by SINC interpolation The corrected distance frequency domain echo signal is brought in Azimuthally space-varying correction is performed to obtain a corrected azimuth echo signal ; the virtual orientation time With reference to the following equation: ； wherein, is the distance frequency, is the carrier frequency, is the variable factor, is the resampling factor; The resampling factor With reference to the following equation: ； wherein, denotes the partial derivative with respect to , , , denotes the modulo operation, is the scene center point is the slant angle of the scene center point is the slant distance vector of the scene center point is the scene center point is the slant angle of the scene center point is the slant angle of the scene center point , is the height of the platform of the large squint SAR imaging system.

2. The actual trajectory based squinted two-dimensional space-variant motion compensation SAR imaging method according to claim 1, characterized in that, The echo data The distance pulse compression processing is performed to obtain a distance pulse compressed distance frequency domain echo signal , comprising: performing a Fourier transform on the echo data in the range direction to obtain a range-frequency domain echo signal performing a Fourier transform on the echo data in the range direction to obtain a range-frequency domain echo signal performing a Fourier transform on the echo data in the range direction to obtain a range-frequency domain echo signal by a pre-constructed range pulse compression function on the range frequency domain echo signal performing range pulse compression to obtain the range pulse compressed range frequency domain echo signal .

3. The actual trajectory based squinted two-dimensional space-variant motion compensation SAR imaging method according to claim 1, characterized in that, The distance frequency domain echo signal after the distance pulse pressure Non-vanishing phase compensation is performed to obtain a compensated signal , comprising: Constructing non-empty phase compensation function ; by the non-varying phase compensation function on the range-compressed range-frequency domain echo signal performing non-varying phase compensation to obtain a compensated signal .

4. The actual trajectory based squinted two-dimensional space-variant motion compensation SAR imaging method according to claim 1, characterized in that, The compensated signal is subjected to a distance domain deconvolution to obtain a corrected distance domain echo signal The distance domain deconvolution is performed to obtain a corrected distance domain echo signal , comprising: by a pre-constructed function to the compensated signal reconstruction, to obtain a distance frequency domain echo signal ; performing inverse Fourier transform on the distance frequency domain echo signal to obtain a distance time domain echo signal performing inverse Fourier transform on the distance frequency domain echo signal to obtain a distance time domain echo signal performing inverse Fourier transform on the distance frequency domain echo signal to obtain a distance time domain echo signal by a pre-constructed pre-filter function echo signals of the distance time domain processed to obtain echo signals of the distance time domain ; echo signals of the distance domain performing a distance-wise Fourier transform to obtain echo signals of the distance domain ; by a pre-constructed frequency domain variable function the distance frequency domain echo signal is processed to obtain the distance frequency domain echo signal ; to the distance domain performing inverse Fourier transform in the distance direction to obtain echo signals in the distance time domain ; by a pre-constructed compensation function echo signals of the distance time domain are processed to obtain echo signals of the distance time domain ; echo signals of the distance domain performing a distance-wise Fourier transform to obtain the corrected echo signals of the distance frequency domain .

5. The actual trajectory based squinted two-dimensional space-variant motion compensation SAR imaging method according to claim 4, characterized in that, The pre-constructed pre-filter function With reference to the following equation: ； wherein, is an exponential function, is an imaginary unit, is a distance-modulated frequency, is a variable scaling factor, is the azimuth time of the carrier platform of the large squint SAR imaging system; The covariate Reference is made to the following: ； wherein, denotes the partial derivative with respect to denotes the partial derivative with respect to denotes the modulo operation, is the scene center point is the slant angle of the scene center point is the slant range vector of the scene center point is the slant angle of an arbitrary point in the scene is the slant range vector of an arbitrary point in the scene is the slant angle of an arbitrary point in the scene, the antenna phase center position of the airborne platform of the large squint SAR imaging system is denoted as , is the height of the airborne platform of the large squint SAR imaging system.​​ 6. The actual trajectory based squinted two-dimensional space-variant motion compensation SAR imaging method according to claim 5, characterized in that, The pre-constructed frequency domain variable function Referring to the following formula: ； wherein is the distance frequency.

7. The real trajectory based two-dimensional space-variant motion compensation SAR imaging method for strabismus according to claim 6, characterized in that, The pre-constructed compensation function With reference to the following equation: ； wherein is the carrier frequency.

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