A two-dimensional air-varying filtering method for accurate compensation of PFA wavefront bending in a motorized platform

Abstract

This invention relates to a two-dimensional air-varying filtering method for precise compensation of wavefront curvature in PFA (Position Frame Analysis) of a mobile platform. It integrates three-dimensional acceleration into the PFA algorithm's imaging process for coarse-focused PFA imaging of the mobile platform. Based on this, a two-dimensional air-varying filter is constructed, and a block-based approach is used to perform two-dimensional air-varying filtering on the coarse-focused PFA image to achieve coarse correction of wavefront curvature. Finally, a fine-focused PFA image is obtained through geometric deformation correction. Compared to existing technologies, this invention ensures no geometric deformation in the image while maintaining good focusing performance, thus exhibiting higher imaging performance.

Description

Technical Field

[0001] This invention belongs to the field of radar signal processing technology, specifically relating to a two-dimensional air-varying filtering method for precise compensation of PFA wavefront bending on a mobile platform. Background Technology

[0002] In the field of radar signal processing technology, the PFA (Polar Format Algorithm) is a particularly effective imaging algorithm in spotting mode. It uses polar coordinates to store data, avoiding the problem of scattering points moving across distance cells away from the center of the imaging area. Therefore, its effective imaging range in spotting mode is greater than other frequency domain imaging algorithms. However, as the imaging scene increases, the PFA algorithm faces defocusing and geometric deformation problems caused by wavefront curvature. Two-dimensional spatially variable filtering is an effective means to solve PFA imaging of straight-track platforms in the basic mode, but for moving platforms, due to the irregular curved motion and three-dimensional acceleration, the two-dimensional spatially variable filtering originally used for basic PFA mode is no longer applicable.

[0003] The limitations of PFA imaging on mobile platforms can be divided into two parts: its impact on focusing performance and its impact on imaging geometry. Existing technologies can only effectively handle defocusing and geometric deformation caused by wavefront curvature in PFA images moving along straight trajectories. Furthermore, existing two-dimensional air-varying filtering methods for PFA on mobile platforms decompose the slant range model into higher-order approximations using Taylor series, resulting in insufficient accuracy in curved trajectory modes. Summary of the Invention

[0004] To address the aforementioned problems in the existing technology, this invention provides a two-dimensional air-varying filtering method for accurate compensation of wavefront bending in a PFA (Pulse Fascia) system for a mobile platform. The technical problem to be solved by this invention is achieved through the following technical solution:

[0005] This invention provides a two-dimensional air-varying filtering method for accurate compensation of PFA wavefront bending in motorized platforms, comprising:

[0006] Step 1: Acquire the target echo signal, and process the target echo signal using the PFA algorithm based on three-dimensional acceleration to obtain the two-dimensional interpolated signal phase after range interpolation and azimuth interpolation.

[0007] Step 2: Based on the phase of the two-dimensional interpolation signal, obtain a two-dimensional coarse-focused PFA image, and divide the two-dimensional coarse-focused PFA image into several sub-image blocks;

[0008] Step 3: Obtain the precise range frequency domain and azimuth time domain signal phases of the target based on the target's true differential distance. Perform range interpolation and azimuth interpolation processing on the precise range frequency domain and azimuth time domain signal phases in sequence to obtain the precise two-dimensional interpolated signal phases.

[0009] Step 4: Based on the phase of the two-dimensional interpolation signal and the phase of the precise two-dimensional interpolation signal, construct a two-dimensional spatially variable filter corresponding to each sub-image block, and use the two-dimensional spatially variable filter to process each sub-image block to obtain the corresponding wavefront curvature coarse correction sub-image.

[0010] Step 5: Perform geometric deformation correction on the wavefront bending coarse correction sub-image, and synthesize the geometrically deformed sub-image to obtain a fine-focused PFA image.

[0011] In one embodiment of the present invention, step 1 includes:

[0012] Step 1.1: Acquire the target echo signal, perform a range-direction Fourier transform on the target echo signal to obtain the range frequency domain and azimuth time domain signals;

[0013] Step 1.2: Perform range pulse compression and phase compensation processing on the range frequency domain and azimuth time domain signals to obtain pulse compression compensated signals, and extract the phase of the pulse compression compensated signals;

[0014] The pulse compression compensation signal is represented as follows:

[0015]

[0016] In the formula, B(f) r ,t a ) represents the pulse pressure compensation signal, f r Represents the distance frequency, t a Indicates location and time, c represents the speed of light, f c The carrier frequency is represented by j, the imaginary unit in the complex form is represented by k, and the modulation frequency is represented by W. r (f r ) represents the distance-frequency domain envelope, w a (t a R(t) represents the azimuth-time envelope. a R represents the instantaneous slant range of the radar reaching the target point. ref Indicates the slant distance history of the scene center point;

[0017] The phase of the pulse compression compensation signal is represented as follows:

[0018]

[0019] In the formula, B'(f r ,ta ) represents the phase of the pulse compression compensation signal, k x Indicates range-oriented beam, k y This indicates the azimuth beam, and x and y represent the coordinates of the target point;

[0020] Step 1.3: Perform range interpolation and azimuth interpolation on the pulse compression compensation signal phase sequentially to obtain the two-dimensional interpolated signal phase;

[0021] The phase of the two-dimensional interpolation signal is represented as follows:

[0022]

[0023] In the formula, k x0 This represents the center time value of the azimuth wavenumber. This represents the distance frequency after interpolation. This indicates the azimuth time after interpolation.

[0024] In one embodiment of the present invention, the instantaneous slant range R(t) of the radar reaching the target point a )for:

[0025] In the formula, a x a y a z These represent the accelerations along the X, Y, and Z axes, respectively, and v y v represents the horizontal flight speed of the aircraft. z H represents the aircraft's flight speed in the altitude direction, and R represents the radar flight altitude. sg θ represents the horizontal distance difference between the radar coordinate system and the imaging coordinate system. yaw This represents the angle difference between the radar coordinate system and the imaging coordinate system.

[0026] In one embodiment of the present invention, step 3 includes:

[0027] Step 3.1: Obtain the accurate range frequency domain and azimuth time domain signal phase using the actual differential distance from the target point to the radar position at each time.

[0028] The precise range frequency domain and azimuth time domain signal phases are represented as follows:

[0029]

[0030] Step 3.2: Perform range interpolation and azimuth interpolation on the precise range frequency domain and azimuth time domain signal phases in sequence to obtain the precise two-dimensional interpolated signal phases.

[0031] In one embodiment of the present invention, step 4 includes:

[0032] Step 4.1: Obtain the center point of each of the sub-image blocks;

[0033] Step 4.2: Based on the coordinates of the center point of each sub-image block, construct the two-dimensional spatially variable filter corresponding to each sub-image block according to the following formula;

[0034] H(f r ,t a )=(-Φ” m (f r ,t a )-D(f r ,t a ));

[0035] In the formula, H(f) r ,t a ) represents a two-dimensional space-varying filter, Φ” m (f r ,t a D(f) represents the phase of the precise two-dimensional interpolated signal. r ,t a () represents the phase of the two-dimensional interpolated signal;

[0036] Step 4.3: Use the two-dimensional spatial variable filter to perform phase compensation on the phase of the two-dimensional interpolation signal of the corresponding sub-image block;

[0037] Step 4.4: Perform range-direction inverse Fourier transform and azimuth-direction Fourier transform on the phase of the phase-compensated two-dimensional interpolated signal to obtain the corresponding wavefront curvature coarse correction sub-image.

[0038] In one embodiment of the present invention, step 5 includes:

[0039] The difference between the center point coordinates of each sub-image block and the true coordinates of the center point is obtained. The difference is used to perform geometric deformation correction on the corresponding wavefront bending coarse correction sub-image. The geometrically deformed sub-images are then synthesized to obtain a fine-focused PFA image.

[0040] Compared with the prior art, the beneficial effects of the present invention are as follows:

[0041] 1. The two-dimensional air-varying filtering method for precise compensation of wavefront curvature in PFA (Position Optimization Aspect) of a motorized platform of the present invention integrates three-dimensional acceleration into the imaging process of the PFA algorithm for coarse-focused PFA imaging of the motorized platform. Based on this, a two-dimensional air-varying filter is constructed, and two-dimensional air-varying filtering is performed on the coarse-focused PFA imaging using a block-based approach to achieve coarse correction of wavefront curvature. Finally, a fine-focused PFA image is obtained through geometric deformation correction. Compared with the prior art, the method of the present invention ensures that the image has no geometric deformation while maintaining good focusing effect, and has higher imaging performance.

[0042] The above description is merely an overview of the technical solution of the present invention. In order to better understand the technical means of the present invention and to implement it in accordance with the contents of the specification, and to make the above and other objects, features and advantages of the present invention more apparent and understandable, preferred embodiments are described in detail below with reference to the accompanying drawings. Attached Figure Description

[0043] Figure 1 This is a schematic diagram of a radar signal model under a maneuvering trajectory provided by an embodiment of the present invention;

[0044] Figure 2 This is a schematic diagram of a two-dimensional air-varying filtering method for precise compensation of PFA wavefront bending of a motorized platform provided in an embodiment of the present invention;

[0045] Figure 3 This is a flowchart of a two-dimensional air-varying filtering method for precise compensation of PFA wavefront bending in a motorized platform, provided in an embodiment of the present invention.

[0046] Figure 4 This is a simulation comparison diagram of the imaging results of the PFA algorithm under different maneuvering modes provided by an embodiment of the present invention;

[0047] Figure 5 This is a simulation diagram of the two-dimensional sidelobe performance of a point target obtained by the two-dimensional air-varying filtering method for precise compensation of PFA wavefront bending in the maneuvering mode provided in the embodiments of the present invention. Detailed Implementation

[0048] To further illustrate the technical means and effects adopted by the present invention to achieve the intended purpose, the following describes in detail a two-dimensional air-varying filtering method for precise compensation of wavefront bending of PFA (Planetary Facilitation Array) of a motorized platform, in conjunction with the accompanying drawings and specific embodiments.

[0049] The foregoing and other technical contents, features, and effects of the present invention will be clearly presented in the following detailed description of specific embodiments in conjunction with the accompanying drawings. Through the description of the specific embodiments, a more in-depth and concrete understanding can be gained of the technical means and effects adopted by the present invention to achieve its intended purpose. However, the accompanying drawings are for reference and illustration only and are not intended to limit the technical solutions of the present invention.

[0050] Example 1

[0051] Before introducing the method of this invention, we first analyze the radar signal model under maneuvering trajectory motion. Ideally, such as Figure 1The diagram shows a radar signal model under a maneuvering trajectory. The SAR signal model of this maneuvering platform follows a curved, variable-speed flight trajectory. The radar's flight altitude is H. After velocity synthesis, a three-dimensional Cartesian coordinate system O-XYZ is established with the ground projection of the aircraft's center position as the origin, the horizontal resultant velocity direction as the Y-axis, the clockwise direction perpendicular to the Y-axis as the X-axis, and the altitude direction as the Z-axis. The aircraft's horizontal flight velocity is v. y The flight speed in the altitude direction is v z The accelerations along the X, Y, and Z axes are a, a, and a, respectively. x a y a z The coordinates of any point P on the trajectory can be represented as: Let the center Q of the imaging scene have coordinates Q(x) in the three-dimensional rectangular coordinate system O-XYZ. n ,y n With the direction from O to Q as the X' axis and the counterclockwise direction perpendicular to the X' axis as the Y' axis, establish a two-dimensional imaging coordinate system X'QY'. Define the horizontal distance difference between the two coordinate systems (radar coordinate system and imaging coordinate system) as 0. where R s The distance from the carrier aircraft to the center of the scene at the center moment is represented by the angle difference θ. yaw Let the coordinates of a point in the imaging two-dimensional coordinate system X'QY' be T(x,y), and its coordinates in the O-XYZ coordinate system be T(x',y'). The relationship between the two coordinates can be obtained from the two-dimensional coordinate transformation matrix. Let the transformation matrix be... Right now

[0052]

[0053] So,

[0054]

[0055] Therefore, the instantaneous slant distance of the radar reaching point T in the O-XYZ coordinate system is:

[0056]

[0057] The instantaneous slant distance R(t) a If we expand the function to the point target position (x,y), then...

[0058] R(t a )≈R ref (t a )+k x x+k y y (4);

[0059] Where R ref k represents the slant distance history of the scene center point.x Indicates range-oriented beam, k y Indicates the azimuth beam, where,

[0060]

[0061]

[0062]

[0063] Please refer to the above. Figure 2 and Figure 3 , Figure 2 This is a schematic diagram of a two-dimensional air-varying filtering method for precise compensation of PFA wavefront bending of a motorized platform provided in an embodiment of the present invention; Figure 3 This is a flowchart of a two-dimensional air-varying filtering method for precise compensation of wavefront bending in a PFA (Power Fascia) of a motorized platform, provided by an embodiment of the present invention. As shown in the figure, the two-dimensional air-varying filtering method for precise compensation of wavefront bending in a PFA of a motorized platform according to this embodiment includes:

[0064] Step 1: Acquire the target echo signal, and process the target echo signal using the PFA algorithm based on three-dimensional acceleration to obtain the two-dimensional interpolated signal phase after range interpolation and azimuth interpolation.

[0065] Specifically, step 1 includes:

[0066] Step 1.1: Acquire the target echo signal, perform a range-direction Fourier transform on the target echo signal to obtain the range frequency domain and azimuth time domain signals;

[0067] In this embodiment, after the SAR radar transmits a linear frequency modulated (LFM) signal, it receives the target echo signal. For example, after transmitting an LFM signal to a ship, it can receive the target echo signal. The received target echo signal is a range-time domain and azimuth-time domain signal A(t). r ,t a ), where t r t represents distance and time. a Represents azimuth time. For this distance-time domain and azimuth-time domain signal A(t)... r ,t a Perform a range-direction Fourier transform to obtain the range-frequency domain and azimuth-time domain signals A'(f). r ,t a ), f r Indicates distance frequency.

[0068] Step 1.2: Perform range pulse compression and phase compensation processing on the range frequency domain and azimuth time domain signals to obtain the pulse compression compensated signal, and extract the phase of the pulse compression compensated signal;

[0069] Specifically, by analyzing the range frequency domain and azimuth time domain signals A'(f r ,t a Multiply by the matched filter reference function to achieve range pulse compression processing.

[0070] Then, phase compensation processing is performed on the range frequency domain and azimuth time domain signals that have undergone range pulse compression to make the echo phase at the scene center point zero, resulting in the pulse compression compensated signal, the expression of which is:

[0071]

[0072] In the formula, B(f) r ,t a ) represents the pulse pressure compensation signal, f r Represents the distance frequency, t a Indicates azimuth time, c represents speed of light, fc represents carrier frequency, j represents the imaginary unit in complex form, k represents frequency modulation, and W r (f r ) represents the distance-frequency domain envelope, w a (t a R(t) represents the azimuth-time envelope. a R represents the instantaneous slant range of the radar reaching the target point. ref Indicates the slant distance history of the scene center point;

[0073] Since the signal amplitude has no effect on focusing, for ease of description, only the phase term is retained. Therefore, the pulse compression compensation signal B(f) r ,t a The phase term B'(f) r ,t a ) is represented as:

[0074]

[0075] In the formula, B'(f r ,t a ) represents the phase of the pulse compression compensation signal, k x Indicates range beam, k y This indicates the azimuth beam, and x and y represent the coordinates of the target point.

[0076] Step 1.3: Perform range interpolation and azimuth interpolation on the pulse compression compensation signal phase sequentially to obtain the two-dimensional interpolated signal phase;

[0077] Specifically, the pulse compression compensation signal phase B'(f r ,t a It can be represented in another form:

[0078]

[0079]

[0080] Where, k x0 This indicates the center time value of the azimuth wavenumber.

[0081] Through the corresponding interpolation relationship: The range frequency f after interpolation is used. r Represented as Then we can obtain f r and The conversion relationship between them is as follows:

[0082]

[0083] This transformation relationship allows us to obtain the range-direction interpolated phase C(f). r ,t a ):

[0084]

[0085] Furthermore, through the corresponding interpolation relationship: The azimuth time after interpolation is t a Represented as Then we can obtain t a and The conversion relationship between them is as follows:

[0086]

[0087] For the completed range interpolation phase C(f) r ,t a This transformation relationship yields the phase D(f) of the two-dimensional interpolated signal. r ,t a ):

[0088]

[0089] Step 2: Based on the phase of the two-dimensional interpolation signal, obtain a two-dimensional coarse-focused PFA image, and divide the two-dimensional coarse-focused PFA image into several sub-image blocks;

[0090] Specifically, the phase of the two-dimensional interpolated signal is subjected to inverse Fourier transform in the range direction and Fourier transform in the azimuth direction to obtain a two-dimensional coarse-focused PFA image.

[0091] The two-dimensional coarse-focused PFA image is represented as follows:

[0092]

[0093] To maintain phase preservation, the last phase of the two-dimensional coarse-focused PFA image s(x,y) can be compensated off along the x-axis. Therefore, the two-dimensional coarse-focused PFA image s(x,y) can be expressed as:

[0094]

[0095] Furthermore, the two-dimensional coarse-focused PFA image is divided into several sub-image blocks. In this embodiment, the two-dimensional coarse-focused PFA image is divided into sub-images of size 128*128.

[0096] Step 3: Obtain the precise range frequency domain and azimuth time domain signal phases of the target based on the target's true differential distance. Perform range interpolation and azimuth interpolation processing on the precise range frequency domain and azimuth time domain signal phases in sequence to obtain the precise two-dimensional interpolated signal phases.

[0097] Specifically, step 3 includes:

[0098] Step 3.1: Obtain the accurate range frequency domain and azimuth time domain signal phase using the actual differential distance from the target point to the radar position at each time.

[0099] The precise range frequency domain and azimuth time domain signal phases are represented as follows:

[0100]

[0101] Step 3.2: Perform range interpolation and azimuth interpolation on the precise range frequency domain and azimuth time domain signal phases in sequence to obtain the precise two-dimensional interpolated signal phases.

[0102] Specifically, through the distance-corresponding interpolation relationship: The interpolated distance frequency f r Represented as This allows us to obtain the precise range-frequency domain and azimuth-time domain signal phase Φ' after range interpolation. m (f r ,t a ).

[0103] Furthermore, through the corresponding interpolation relationship of the azimuth: The azimuth time after interpolation is t a Represented as This yields the precise two-dimensional interpolated signal phase Φ” after two-dimensional interpolation. m (f r ,t a ).

[0104] Step 4: Based on the phase of the two-dimensional interpolation signal and the phase of the precise two-dimensional interpolation signal, construct a two-dimensional spatially variable filter corresponding to each sub-image block. Use the two-dimensional spatially variable filter to process each sub-image block to obtain the corresponding wavefront curvature coarse correction sub-image.

[0105] Specifically, step 4 includes:

[0106] Step 4.1: Obtain the center point of each sub-image patch;

[0107] Step 4.2: Based on the coordinates of the center point of each sub-image block, construct the two-dimensional spatially variable filter corresponding to each sub-image block according to the following formula;

[0108] H(f r ,t a )=(-Φ” m (f r ,t a )-D(f r ,t a )) (19);

[0109] In the formula, H(f) r ,t a ) represents a two-dimensional space-varying filter, Φ” m (f r ,t a D(f) represents the phase of the precise two-dimensional interpolated signal. r ,t a ) represents the phase of a two-dimensional interpolated signal.

[0110] Step 4.3: Use a two-dimensional spatially variable filter to perform phase compensation on the two-dimensional interpolation signal of the corresponding sub-image block;

[0111] Specifically, the phase D(f) of the two-dimensional interpolation signal of the sub-image block r ,t a ) and the two-dimensional spatially variable filter H(f) of the sub-image block r ,t a Multiply the two phases and perform phase compensation to obtain a coarsely corrected phase for wavefront bending.

[0112] Step 4.4: Perform range-direction inverse Fourier transform and azimuth-direction Fourier transform on the phase of the phase-compensated two-dimensional interpolated signal to obtain the corresponding wavefront curvature coarse correction sub-image.

[0113] Step 5: Perform geometric deformation correction on the coarse correction sub-image of wavefront curvature, and synthesize the geometrically deformed sub-images to obtain the fine-focused PFA image.

[0114] To reduce computational load, a two-dimensional coarse-focused PFA image block operation was performed. Although the center phase of each sub-image block was accurately corrected, a two-dimensional phase error with spatial variation in distance and orientation still exists for other positions within the sub-image block, resulting in geometric deformation within the sub-image block except for the center point. Therefore, it is necessary to correct the geometric deformation within the sub-image blocks for the remaining deformation within the sub-image blocks.

[0115] Specifically, step 5 includes

[0116] The difference between the center point coordinates of each sub-image block and the true coordinates of that center point is obtained. The difference is used to perform geometric deformation correction on the corresponding wavefront bending coarse correction sub-image. The geometrically deformed sub-images are then synthesized to obtain a fine-focused PFA image.

[0117] In this embodiment, for any point in the scene, let its true position be (x... ip ,y ip Its position in the two-dimensional coarse-focused raw PFA image of the maneuvering platform obtained directly from step 5 is as follows: (i.e., the location where geometric deformation occurs), the corresponding relationship can be expressed by the following formula:

[0118]

[0119] After completing the two-dimensional spatial filtering of the sub-image blocks, the positions of the points were partially corrected, and the positions of points with geometric deformation were no longer... Let (x) ip ,y ip The points corresponding to the sub-image blocks after two-dimensional spatial filtering are: This can be obtained through the compensation amount of the center point of each sub-image block. The specific expression is finally completed. and Interpolation can complete geometric correction, resulting in a geometrically corrected sub-image. All geometrically corrected sub-images are then combined to obtain a finely focused PFA image I(x,y).

[0120] It should be noted that, based on the two-dimensional spatially variable filter construction method, a two-dimensional spatially variable filter can be directly constructed for each point of the two-dimensional coarse-focused PFA image. Then, the constructed two-dimensional spatially variable filter can be used to eliminate the wavefront curvature error of the two-dimensional coarse-focused PFA image, resulting in a wavefront curvature corrected image, without the need for further geometric deformation correction.

[0121] The two-dimensional air-varying filtering method for precise compensation of wavefront curvature in PFA (Position Optimization Aspect) of a mobile platform, as described in this invention, integrates three-dimensional acceleration into the imaging process of the PFA algorithm. It performs coarse-focused PFA imaging of the mobile platform, and on this basis, constructs a two-dimensional air-varying filter. A block-based approach is used to perform two-dimensional air-varying filtering on the coarse-focused PFA image to achieve coarse correction of wavefront curvature. Finally, through geometric deformation correction, a fine-focused PFA image is obtained. Compared with existing technologies, this method ensures no geometric deformation of the image while maintaining good focusing performance, thus exhibiting higher imaging performance.

[0122] Example 2

[0123] This embodiment uses simulation experiments to illustrate the effectiveness of the two-dimensional air-varying filtering method for precise compensation of wavefront bending of the PFA (Planetary Facilitation Assist) in Embodiment 1.

[0124] 1. Simulation conditions

[0125] <![CDATA[Carrier frequency f c > 17GHz Pulse repetition frequency 2800Hz bandwidth 100MHz Altitude (h) 26km Sampling frequency 120MHz Central slope distance (R) 32km Pulse width 10μs Target speed (50, 140, -105) m / s Yaw angle 52°s Target acceleration <![CDATA[(-2,21,-8)m / s 2 ]]>

[0126] 2. Simulation Content and Result Analysis

[0127] Please see Figure 4 The simulation comparison diagrams of the PFA algorithm imaging results under different maneuvering modes are shown. (a) The image shows the imaging result of the original maneuvering platform PFA algorithm. It can be seen that the geometric deformation of the imaging result is serious, which has a great impact on the imaging effect. (b) The image shows the imaging result of the method proposed in this invention. It can be seen that the geometric deformation is effectively corrected and the range and azimuth are aligned.

[0128] Please see Figure 5 The simulation diagram of the two-dimensional sidelobe performance of the point target obtained by the two-dimensional air-varying filtering method with precise compensation for PFA wavefront curvature in the maneuvering mode is shown. Figures (a) and (b) are the distance and azimuth sidelobe ratios of the point target in the imaging result of the method of the present invention, respectively. It can be seen that the focusing effect is good.

[0129] It should be noted that, in this document, relational terms such as "first" and "second" are used merely to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations are intended to cover non-exclusive inclusion, such that an article or apparatus comprising a list of elements includes not only those elements but also other elements not expressly listed. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the article or apparatus that includes said element.

[0130] The above is a further detailed description of the present invention in conjunction with specific preferred embodiments, and the specific implementation of the present invention should not be considered to be limited to these descriptions. For those skilled in the art of the present invention, without departing from the concept of the present invention, several simple deductions or substitutions can be made, which should be considered to fall within the scope of protection of the present invention.

Claims

1. A two-dimensional air-varying filtering method for precise compensation of PFA wavefront bending in a mobile platform, characterized in that, The motion trajectory of the SAR signal model of the maneuvering platform is a curved, variable-speed flight, and the method includes: Step 1: Acquire the target echo signal, and process the target echo signal using the PFA algorithm based on three-dimensional acceleration to obtain the two-dimensional interpolated signal phase after range interpolation and azimuth interpolation. Step 1 includes: Step 1.1: Acquire the target echo signal, perform a range-direction Fourier transform on the target echo signal to obtain the range frequency domain and azimuth time domain signals; Step 1.2: Perform range pulse compression and phase compensation processing on the range frequency domain and azimuth time domain signals to obtain pulse compression compensated signals, and extract the phase of the pulse compression compensated signals; The pulse pressure compensation signal is represented as follows: ； In the formula, This indicates a pulse pressure compensation signal. Indicates distance frequency, Indicates location and time. Represents the speed of light. Indicates the carrier frequency. j The imaginary unit in the complex form, Indicates frequency modulation. Represents the distance-frequency domain envelope. Indicates the location-time envelope. This represents the instantaneous slant range of the radar reaching the target point. Indicates the slant distance history of the scene center point; The phase of the pulse compression compensation signal is represented as follows: ； In the formula, This indicates the phase of the pulse compression compensation signal. Indicates range beam. Indicates azimuth beam. and Represents the coordinates of the target point; Radar flight altitude is After velocity synthesis, a three-dimensional rectangular coordinate system O-XYZ is established with the ground projection position of the aircraft's center position as the origin, the horizontal resultant velocity direction as the Y-axis, the clockwise direction perpendicular to the Y-axis as the X-axis, and the height direction as the Z-axis. Let the coordinates of the imaging scene center Q in the three-dimensional rectangular coordinate system O-XYZ be... Let the direction from O to Q be the X' axis, and the direction counterclockwise and perpendicular to the X' axis be the Y' axis. Establish a two-dimensional imaging coordinate system X'QY'. The transformation relationship between the two coordinate systems is as follows: , Let X'QY' be the coordinates of a point in the imaging two-dimensional coordinate system. for In the O-XYZ coordinate system, the instantaneous slant range of the radar reaching the target point in the O-XYZ coordinate system is obtained according to the transformation relationship between the two coordinate systems. for: In the formula, , , These represent the accelerations along the X, Y, and Z axes, respectively. This indicates the horizontal flight speed of the aircraft. This indicates the aircraft's speed in the altitude direction. Indicates the radar's flight altitude. This represents the horizontal distance difference between the radar coordinate system and the imaging coordinate system. This represents the angle difference between the radar coordinate system and the imaging coordinate system; Step 1.3: Perform range interpolation and azimuth interpolation on the pulse compression compensation signal phase sequentially to obtain the two-dimensional interpolated signal phase; The phase of the two-dimensional interpolation signal is represented as follows: ； In the formula, This represents the center time value of the azimuth wavenumber. This represents the range frequency after range interpolation. This indicates the azimuth time after interpolation. Step 2: Based on the phase of the two-dimensional interpolation signal, obtain a two-dimensional coarse-focused PFA image, and divide the two-dimensional coarse-focused PFA image into several sub-image blocks; Step 3: Obtain the precise range frequency domain and azimuth time domain signal phases of the target based on the target's true differential distance. Perform range interpolation and azimuth interpolation processing on the precise range frequency domain and azimuth time domain signal phases in sequence to obtain the precise two-dimensional interpolated signal phases. Step 4: Based on the phase of the two-dimensional interpolation signal and the phase of the precise two-dimensional interpolation signal, construct a two-dimensional spatially variable filter corresponding to each sub-image block, and use the two-dimensional spatially variable filter to process each sub-image block to obtain the corresponding wavefront curvature coarse correction sub-image. Step 5: Perform geometric deformation correction on the wavefront bending coarse correction sub-image, and synthesize the geometrically deformed sub-image to obtain a fine-focused PFA image.

2. The two-dimensional air-varying filtering method for precise compensation of wavefront bending in PFA of a mobile platform according to claim 1, characterized in that, Step 3 includes: Step 3.1: Obtain the accurate range frequency domain and azimuth time domain signal phase using the actual differential distance from the target point to the radar position at each time. The precise range frequency domain and azimuth time domain signal phases are represented as follows: ； Step 3.2: Perform range interpolation and azimuth interpolation on the precise range frequency domain and azimuth time domain signal phases in sequence to obtain the precise two-dimensional interpolated signal phases.

3. The two-dimensional air-varying filtering method for precise compensation of wavefront bending in PFA of a mobile platform according to claim 2, characterized in that, Step 4 includes: Step 4.1: Obtain the center point of each of the sub-image blocks; Step 4.2: Based on the coordinates of the center point of each sub-image block, construct the two-dimensional spatially variable filter corresponding to each sub-image block according to the following formula; ； In the formula, This represents a two-dimensional space-varying filter. Represents the phase of a precise two-dimensional interpolated signal. Indicates the phase of the two-dimensional interpolated signal; Step 4.3: Use the two-dimensional spatial variable filter to perform phase compensation on the phase of the two-dimensional interpolation signal of the corresponding sub-image block; Step 4.4: Perform range-direction inverse Fourier transform and azimuth-direction Fourier transform on the phase of the phase-compensated two-dimensional interpolated signal to obtain the corresponding wavefront curvature coarse correction sub-image.

4. The two-dimensional air-varying filtering method for precise compensation of wavefront bending in PFA of a mobile platform according to claim 3, characterized in that, Step 5 includes: The difference between the center point coordinates of each sub-image block and the true coordinates of the center point is obtained. The difference is used to perform geometric deformation correction on the corresponding wavefront bending coarse correction sub-image. The geometrically deformed sub-images are then synthesized to obtain a fine-focused PFA image.

Images