Satellite-borne SAR real-time imaging method based on embedded GPU

Abstract

The invention provides a satellite-borne SAR (Synthetic Aperture Radar) real-time imaging method based on an embedded GPU (Graphics Processing Unit), which comprises the following steps of: dividing obtained echo data into a plurality of sub-aperture signals in an azimuth direction through main equipment, and distributing the sub-aperture signals to different node equipment; each node device performs Doppler center compensation on the received sub-aperture signals to obtain a plurality of compensated sub-aperture signals, and performs range unit migration correction and range pulse compression processing on each compensated sub-aperture signal to obtain a plurality of sub-aperture signals subjected to range direction processing; the hyperbolic phase in each sub-aperture signal after range processing is replaced by a standard quadratic phase function through a phase conversion function to obtain a plurality of replaced sub-aperture signals, azimuth inverse Fourier transform is carried out on the sub-aperture signals, and a result is sent to the main device; and the main device performs coherent splicing on the images to obtain full-aperture image data, so that a non-aliasing full-aperture image is obtained, the single-machine processing pressure can be reduced, and the real-time performance is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of radar signal processing, and particularly to a spaceborne SAR real-time imaging method based on an embedded GPU. Background Art

[0002] With the increasing maturity of synthetic aperture radar technology, it has high practical value and a wide range of application scenarios in multiple fields. In the past, the solution for processing spaceborne SAR data was mainly to download the raw data to a ground processor for processing, which usually took several hours and was difficult to meet the application requirements with high real-time performance. However, with the continuous increase in the demand for imaging accuracy, resulting in the continuous improvement of resolution and mapping bandwidth, the amount of echo data obtained by spaceborne SAR satellites has increased sharply, which has brought great pressure to the transmission of spaceborne SAR data. SAR imaging is developing towards ultra-high resolution and large imaging width in geostationary orbit (GEO), which means that it is necessary to process huge amounts of data and perform a large amount of calculations. Imaging processing of wide-swath SAR echo data is an extremely time-consuming and laborious task, with high requirements for hardware resources, and often a single machine cannot meet the needs.

[0003] Parallel computing of multi-core CPUs and multi-core GPUs is a relatively popular high-performance computing architecture at present. Among them, CPUs are suitable for general computing such as serial instructions and task scheduler control; GPUs are suitable for high-throughput computing and can perform large-scale data volume calculations. GPUs have high computing performance, small volume, low power consumption, and a general software and hardware architecture, and can provide high-performance computing capabilities in restricted environments. They have been widely used in high-performance data processing and applications in fields such as surveying and mapping, remote sensing, and geoscience. For remote sensing image processing algorithms with higher complexity, by deeply analyzing each step inside the algorithm and splitting the algorithm, the computationally intensive parts are handed over to the GPU for processing, and the remaining operations with more logical processing and less computational volume are handed over to the CPU for processing. This CPU-GPU heterogeneous parallel computing mode based on algorithm decomposition has become the means to achieve GPU parallel acceleration for remote sensing image processing at present. However, the current spaceborne real-time processing usually adopts the FPGA+DSP mode, which has high costs, a long development cycle, and great development difficulties. Moreover, the current spaceborne SAR real-time imaging algorithms have high requirements for the resources of a single processor, especially for the GPU video memory; the existing algorithms have not been specifically designed according to the characteristics of the GPU, and cannot fully utilize the advantages of high parallelism of the GPU. Often, in the parts with large algorithm computational amounts, full parallelism cannot be achieved, resulting in long processing times; the GPU parallel algorithms adopted by the existing SAR imaging algorithms can only be applied to single requirements, cannot be transplanted and extended, have low flexibility, and consume a large amount of time in data transmission between machines when multiple machines cooperate for processing. Summary of the Invention

[0004] To solve the above problems existing in the prior art, the present invention provides a spaceborne SAR real-time imaging method based on an embedded GPU, specifically including:

[0005] In a first aspect, the present invention provides a spaceborne SAR real-time imaging method based on an embedded GPU, including:

[0006] The master device divides the acquired echo data in the azimuth direction into sub-aperture signals, and sends each sub-aperture signal to a different node device;

[0007] Each node device performs Doppler center compensation on the received sub-aperture signal to obtain multiple compensated sub-aperture signals, and uses the chirp scaling function, range compression function, and phase correction function in CSA to perform range cell migration correction and range pulse compression processing on each compensated sub-aperture signal to obtain multiple sub-aperture signals after range processing; through the phase conversion function, the hyperbolic phase in each sub-aperture signal after range processing is replaced with a standard quadratic phase function to obtain multiple replaced sub-aperture signals, performs azimuth inverse Fourier transform on each replaced sub-aperture signal, and sends the inverse Fourier transform result to the master device;

[0008] The master device coherently splices each inverse Fourier transform result in the global coordinate system to obtain full-aperture image data;

[0009] The master device uses the scaling dechirp function and the full-aperture image data to obtain an alias-free full-aperture image.

[0010] In a second aspect, the present invention further provides a spaceborne SAR real-time imaging system based on an embedded GPU, including:

[0011] A master device and multiple slave devices;

[0012] The master device is used to divide the acquired echo data in the azimuth direction into sub-aperture signals, and send each sub-aperture signal to a different node device;

[0013] Each node device is used to perform Doppler center compensation on the received sub-aperture signal to obtain multiple compensated sub-aperture signals, and use the chirp scaling function, range compression function, and phase correction function in CSA to perform range cell migration correction and range pulse compression processing on each compensated sub-aperture signal to obtain multiple sub-aperture signals after range processing; through the phase conversion function, the hyperbolic phase in each sub-aperture signal after range processing is replaced with a standard quadratic phase function to obtain multiple replaced sub-aperture signals, performs azimuth inverse Fourier transform on each replaced sub-aperture signal, and sends the inverse Fourier transform result to the master device;

[0014] The master device is also used to coherently splice the inverse Fourier transform results in the global coordinate system to obtain full-aperture image data;

[0015] The master device is also used to use the scaled dechirp function and the full-aperture image data to obtain an aliasing-free full-aperture image.

[0016] In a third aspect, the present invention provides a computer-readable storage medium, in which a computer program is stored, and when the computer program is executed by a processor, any method provided in the first aspect is implemented.

[0017] Advantages of the present invention:

[0018] The spaceborne SAR real-time imaging method based on an embedded GPU provided by the present invention divides the acquired echo data into sub-apertures in the azimuth direction through the master device to obtain a plurality of sub-aperture signals, and sends each sub-aperture signal to different node devices; each node device performs Doppler centroid compensation on the received sub-aperture signal to obtain a plurality of compensated sub-aperture signals, and uses the chirp scaling function, range compression function and phase correction function in CSA to perform range cell migration correction and range pulse compression processing on each compensated sub-aperture signal to obtain a plurality of sub-aperture signals after range processing; through the phase conversion function, the hyperbolic phase in each sub-aperture signal after range processing is replaced with a standard quadratic phase function to obtain a plurality of replaced sub-aperture signals, performs azimuth inverse Fourier transform on each replaced sub-aperture signal, and sends the inverse Fourier transform result to the master device; the master device coherently splices the inverse Fourier transform results in the global coordinate system to obtain full-aperture image data; the master device uses the scaled dechirp function and the full-aperture image data to obtain an aliasing-free full-aperture image, which can utilize a distributed architecture, reduce the processing pressure of a single machine, and at the same time has high flexibility, and can expand the number of nodes according to the requirements of the task data volume. In the case where the data communication time between each computing node is serious, the algorithm process is improved, the number of zero-padding points is reduced, thereby reducing the amount of data to be processed and the amount of data that needs to be communicated between machines, thereby reducing the communication duration and improving the real-time performance.

[0019] The following will further elaborate on the present invention in conjunction with the drawings and embodiments. Description of the Drawings

[0020] Figure 1 It is a schematic flowchart of a spaceborne SAR real-time imaging method based on an embedded GPU provided by the present invention;

[0021] Figure 2 It is a schematic diagram of the sub-aperture division result provided by the present invention;

[0022] Figure 3 A schematic diagram of a CPU architecture provided by the present invention;

[0023] Figure 4 A schematic diagram of a GPU architecture provided by the present invention;

[0024] Figure 5 A schematic diagram of a CPU+GPU heterogeneous parallel computing architecture provided by the present invention;

[0025] Figure 6 A schematic diagram of a processing flow of a CPU+GPU architecture provided by the present invention. Detailed implementation manners

[0026] The following further describes the present invention in detail with reference to specific embodiments, but the implementation manners of the present invention are not limited thereto.

[0027] Aiming at the problems existing in the prior art, the present invention provides a distributed spaceborne SAR real-time imaging method based on an embedded GPU. By distributing echo data and computing tasks with large data volumes to multiple processing units, on each processing unit, the parts with smaller computational complexity and complex computational amounts of the algorithm are calculated using the CPU, and the matrix operations with large data volumes are processed using the GPU, thereby giving full play to the parallel advantages of the embedded GPU and significantly reducing the processing time. By optimizing the scheduling of the computing, the amount of data to be transmitted between machines is reduced, and the transmission time is significantly reduced. The system architecture adopts a distributed architecture, which has high flexibility and can expand the number of processing units according to the requirements of the task data volume.

[0028] Under the condition of limited hardware resources of a single machine, the computing tasks are reasonably distributed to multiple processors, and at the same time, the amount of data communicated between machines is reduced, so as to significantly improve the imaging processing efficiency and processing accuracy of SAR echo data.

[0029] Figure 1 A schematic diagram of the flow of a spaceborne SAR real-time imaging method based on an embedded GPU provided by the present invention, as Figure 1 shown, the method includes:

[0030] S101. The master device divides the acquired echo data in the azimuth direction into multiple sub-aperture signals, and sends each sub-aperture signal to a different node device.

[0031] As Figure 2 shown, in a possible implementation manner, the master device divides the acquired echo data in the azimuth direction into multiple sub-aperture signals, including:

[0032] The master device divides the acquired echo data into multiple sub-apertures according to a preset sub-aperture size, obtaining multiple sub-aperture signals, and the sub-aperture signals are expressed as:

[0033]

[0034] where a r (·) represents the window function of the linear frequency modulation (LFM) signal, a a (·) represents the azimuth beam window function, γ represents the chirp rate of the transmitted LFM signal, t represents the fast time in range, λ represents the wavelength, c represents the speed of light, t sub represents the slow time in azimuth of the sub-aperture data, and R B represents the straight-line distance from the radar to the point target.

[0035] S102. Each node device performs Doppler centroid compensation on the received sub-aperture signals to obtain multiple compensated sub-aperture signals, and uses the chirp scaling function, range compression function, and phase correction function in CSA to perform range cell migration correction and range pulse compression processing on each compensated sub-aperture signal, obtaining multiple sub-aperture signals after range processing; through the phase conversion function, the hyperbolic phase in each sub-aperture signal after range processing is replaced with a standard quadratic phase function, obtaining multiple replaced sub-aperture signals, performing inverse Fourier transform in azimuth on each replaced sub-aperture signal, and sending the inverse Fourier transform result to the master device.

[0036] The CPU, that is, the central processing unit, is the operation and control core of a computer system and is the final execution unit for information processing and program operation. As Figure 3 shown, the CPU includes an ALU (arithmetic unit), a Control (control unit), a Cache (cache unit), and a DRAM (storage unit), and is suitable for general computing such as serial instruction and task scheduler control.

[0037] The GPU, that is, the Graphics Processing Unit, is a microprocessor specialized for performing image and graphics-related operations on personal computers, workstations, game consoles, and some mobile devices. As Figure 4 shown, the GPU usually includes an ALU (arithmetic unit), a Control (control unit), a Cache (cache unit), and a DRAM (storage unit), and the GPU is suitable for high-throughput computing and can achieve large-scale data volume computing.

[0038] Figure 5 is a CPU+GPU heterogeneous parallel computing architecture, and this architecture can give full play to the advantages of the CPU and the GPU. This architecture can achieve asFigure 6 The processing procedure shown

[0039] When the echo data is divided into multiple sub-apertures in the azimuth direction, the Doppler center will change with the rotation of the antenna beam. Therefore, it is necessary to perform Doppler center compensation on each sub-aperture data.

[0040] In a possible implementation, each node device includes a CPU and a GPU.

[0041] Correspondingly, step S102 specifically includes:[[]]

[0042] The CPU performs Doppler center compensation on the received sub-aperture signals to obtain multiple compensated sub-aperture signals, and sends each compensated sub-aperture signal to the GPU together with the generated chirp scaling vector after azimuth Fourier transform;

[0043] The GPU uses the chirp scaling function, chirp scaling vector, range compression function and phase correction function in the CSA to perform range cell migration correction and range pulse compression processing on the received signals to obtain multiple sub-aperture signals after range processing; through the phase conversion function, the hyperbolic phase in each sub-aperture signal after range processing is replaced with a standard quadratic phase function to obtain multiple replaced sub-aperture signals, perform inverse azimuth Fourier transform on each replaced sub-aperture signal, and send the inverse Fourier transform result to the master device.

[0044] Among them, the range compression function and the phase correction function can adopt existing functions, and there is no specific limitation.

[0045] Optionally, the Doppler center corresponding to each sub-aperture signal is expressed as:

[0046] f dc = K rot × t k ,

[0047] where K rot is the slope of the support area of the time-frequency distribution diagram, t k is the central moment of the k-th sub-aperture signal, and f dc represents the Doppler center corresponding to the sub-aperture signal;

[0048] The Doppler center compensation function is expressed as:

[0049] Hd(t, tsub; R B ) = exp(-j2πfdc(tk + tsub));

[0050] The compensated sub-aperture signal after azimuth Fourier transform is expressed as:

[0051]

[0052] Among them, f sub represents the azimuth frequency of the sub-aperture data,

[0053]

[0054] Optionally, the GPU replaces the hyperbolic phase in each sub-aperture signal after range processing with a standard quadratic phase function through a phase conversion function, and obtains multiple replaced sub-aperture signals s k (t, f sub ; R B ). The expression is:

[0055]

[0056] Among them, H4(t, f sub ; R B ) represents the phase conversion function, v represents the satellite radial velocity, and R B represents the straight-line distance from the radar to the point target. K scl =-2v 2 / λR ref , K scl represents the azimuth scaling factor, R ref represents the reference distance from the satellite to the center line of the scene, λ represents the wavelength, and f dc represents the Doppler center corresponding to the sub-aperture signal.

[0057] The present invention fully utilizes the characteristics of numerous GPU computing cores for algorithm design, adopts a distributed architecture based on an embedded GPU to complete real-time imaging tasks, can effectively reduce the processing pressure of a single machine, improve efficiency at the same time, and has high flexibility.

[0058] S103. The master device performs coherent stitching on the results of each inverse Fourier transform in the global coordinate system to obtain full-aperture image data.

[0059] In a possible implementation manner, the master device performs coherent stitching on the results of each inverse Fourier transform in the global coordinate system to obtain full-aperture image data, including:

[0060] The master device calculates the number of pixels for translation of multiple sub-aperture complex-valued images according to the position numbers corresponding to each sub-aperture signal; the master device sequentially translates and superimposes each sub-aperture complex-valued image according to the calculated number of pixels to complete coherent stitching and obtain full-aperture image data.

[0061] S104. The master device uses a scaled dechirp function and full-aperture image data to obtain an aliasing-free full-aperture image.

[0062] In a possible implementation, the master device uses a scaled dechirp function and full-aperture image data to obtain an aliasing-free full-aperture image, including: the master device multiplies the scaled dechirp function and the full-aperture image data and then performs azimuth Fourier transform to obtain an aliasing-free full-aperture image.

[0063] Optionally, the scaled dechirp function is expressed as:

[0064]

[0065] where H5() represents the scaled dechirp function, t sub represents the azimuth slow time of the sub-aperture data, R B represents the straight-line distance from the radar to the point target, and t k is the central time of the k-th sub-aperture signal.

[0066] The spaceborne SAR real-time imaging method based on an embedded GPU provided by the present invention divides the acquired echo data into sub-apertures in the azimuth direction through the master device to obtain multiple sub-aperture signals, and sends each sub-aperture signal to different node devices; each node device performs Doppler center compensation on the received sub-aperture signal to obtain multiple compensated sub-aperture signals, and uses the chirp scaling function, range compression function, and phase correction function in CSA to perform range cell migration correction and range pulse compression processing on each compensated sub-aperture signal to obtain multiple sub-aperture signals after range processing; through the phase conversion function, the hyperbolic phase in each sub-aperture signal after range processing is replaced with a standard quadratic phase function to obtain multiple replaced sub-aperture signals, performs azimuth inverse Fourier transform on each replaced sub-aperture signal, and sends the inverse Fourier transform result to the master device; the master device performs coherent stitching on each inverse Fourier transform result in the global coordinate system to obtain full-aperture image data; the master device uses a scaled dechirp function and full-aperture image data to obtain an aliasing-free full-aperture image, which can utilize a distributed architecture, reduce the processing pressure of a single machine, and at the same time has high flexibility, can expand the number of nodes according to the requirements of the task data volume, and in the case of serious data communication time consumption between each computing node, improve the algorithm process, reduce the number of zero-padding points, thereby reducing the amount of data to be processed and the amount of data to be communicated between machines, thereby reducing the communication duration and improving the real-time performance.

[0067] The present invention also provides a spaceborne SAR real-time imaging system based on an embedded GPU, including: a master device and multiple slave devices.

[0068] A master device, configured to perform sub-aperture division on acquired echo data in the azimuth direction to obtain multiple sub-aperture signals, and send each sub-aperture signal to different node devices.

[0069] Each node device is configured to perform Doppler center compensation on the received sub-aperture signal to obtain multiple compensated sub-aperture signals, and perform range cell migration correction and range pulse compression processing on each compensated sub-aperture signal by using the chirp scaling function, range compression function, and phase correction function in CSA to obtain multiple sub-aperture signals after range direction processing; by using a phase conversion function, replace the hyperbolic phase in each sub-aperture signal after range direction processing with a standard quadratic phase function to obtain multiple replaced sub-aperture signals, perform azimuth inverse Fourier transform on each replaced sub-aperture signal, and send the inverse Fourier transform result to the master device.

[0070] The master device is further configured to perform coherent stitching on each inverse Fourier transform result in the global coordinate system to obtain full-aperture image data.

[0071] The master device is further configured to use a scaling dechirp function and the full-aperture image data to obtain an aliasing-free full-aperture image.

[0072] The present invention further provides a structure of an electronic device, including a processor, a communication interface, a memory, and a communication bus. Among them, the processor, the communication interface, and the memory complete communication with each other through the communication bus.

[0073] The memory is used to store a computer program.

[0074] When the processor is configured to execute the program stored on the memory, the steps provided in the above method embodiments are implemented.

[0075] The communication interface is used for communication between the above electronic device and other devices.

[0076] The method provided by the embodiments of the present invention can be applied to an electronic device. Specifically, the electronic device can be: a desktop computer, a portable computer, a smart mobile terminal, a server, etc. This is not limited herein, and any electronic device that can implement the present invention belongs to the protection scope of the present invention.

[0077] The present invention further provides a computer-readable storage medium, in which a computer program is stored, and when the computer program is executed by a processor, the steps provided in the above method embodiments are implemented.

[0078] For the system / electronic device / storage medium / program product embodiments, since they are basically similar to the method embodiments, the description is relatively simple. For the specific content, beneficial effects and other relevant aspects, please refer to the partial description of the method embodiments.

[0079] The terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the quantity of the indicated technical features. Thus, features defined with "first" and "second" may explicitly or implicitly include one or more of such features. In the description of the present invention, "a plurality of" means two or more unless otherwise specifically defined.

[0080] The above content is a further detailed description of the present invention in combination with specific preferred embodiments, and it cannot be determined that the specific implementation of the present invention is only limited to these descriptions. For those of ordinary skill in the technical field to which the present invention pertains, without departing from the concept of the present invention, several simple deductions or substitutions can be made, and all should be regarded as belonging to the protection scope of the present invention.

Claims

1. A spaceborne SAR real-time imaging method based on an embedded GPU, characterized in that, Including: The master device divides the acquired echo data in the azimuth direction into multiple sub-aperture signals, and sends each of the sub-aperture signals to different node devices; Each of the node devices performs Doppler centroid compensation on the received sub-aperture signals to obtain multiple compensated sub-aperture signals, and uses the chirp scaling function, range compression function, and phase correction function in CSA to perform range cell migration correction and range pulse compression processing on each of the compensated sub-aperture signals to obtain multiple sub-aperture signals after range direction processing; through the phase conversion function, the hyperbolic phase in each of the sub-aperture signals after range direction processing is replaced with a standard quadratic phase function to obtain multiple replaced sub-aperture signals, performs azimuth inverse Fourier transform on each of the replaced sub-aperture signals, and sends the inverse Fourier transform result to the master device; The master device performs coherent stitching on each of the inverse Fourier transform results in the global coordinate system to obtain full-aperture image data; The master device uses the chirp dechirp function and the full-aperture image data to obtain an aliasing-free full-aperture image.

2. The method according to claim 1, characterized in that, The master device divides the acquired echo data in the azimuth direction into multiple sub-aperture signals, including: The master device divides the acquired echo data into multiple sub-apertures according to a preset sub-aperture size to obtain multiple sub-aperture signals, and the sub-aperture signals are expressed as: where a r (·) represents the window function of the linear frequency modulation (LFM) signal, a a (·) represents the azimuth beam window function, γ represents the chirp rate of the transmitted LFM signal, t represents the fast time in range, λ represents the wavelength, c represents the speed of light, t sub represents the slow time in azimuth of the sub-aperture data, and R B represents the straight-line distance from the radar to the point target.

3. The method according to claim 2, wherein Each of the node devices includes a CPU and a GPU; Correspondingly, each of the node devices performs Doppler centroid compensation on the received sub-aperture signals to obtain multiple compensated sub-aperture signals, and uses the chirp scaling function, range compression function, and phase correction function in CSA to perform range cell migration correction and range pulse compression processing on each of the compensated sub-aperture signals to obtain multiple sub-aperture signals after range direction processing; through the phase conversion function, the hyperbolic phase in each of the sub-aperture signals after range direction processing is replaced with a standard quadratic phase function to obtain multiple replaced sub-aperture signals, performs azimuth inverse Fourier transform on each of the replaced sub-aperture signals, and sends the inverse Fourier transform result to the master device, including: The CPU performs Doppler centroid compensation on the received sub-aperture signals to obtain multiple compensated sub-aperture signals, and sends each of the compensated sub-aperture signals together with the generated chirp scaling vector after azimuth Fourier transform to the GPU; The GPU uses the chirp scaling function, the chirp scaling vector, range compression function, and phase correction function in CSA to perform range cell migration correction and range pulse compression processing on the received signals to obtain multiple sub-aperture signals after range direction processing; through the phase conversion function, the hyperbolic phase in each of the sub-aperture signals after range direction processing is replaced with a standard quadratic phase function to obtain multiple replaced sub-aperture signals, performs azimuth inverse Fourier transform on each of the replaced sub-aperture signals, and sends the inverse Fourier transform result to the master device.

4. The method according to claim 3, wherein The Doppler center corresponding to each of the sub-aperture signals is expressed as: f dc = K rot × t k , Among them, K rot is the slope of the support area of the time-frequency distribution diagram, t k is the central time of the k-th sub-aperture signal, f dc represents the Doppler center corresponding to the sub-aperture signal; The Doppler center compensation function, expressed as: Hd(t, tsub; R B ) = exp(-j2πfdc(tk + tsub)); After azimuth Fourier transform, the compensated sub-aperture signal is expressed as: where f sub represents the azimuth frequency of the sub-aperture data, 5. The method according to claim 4, characterized in that, The GPU replaces the hyperbolic phase in each of the sub-aperture signals processed in the range direction with a standard quadratic phase function through a phase conversion function, obtaining a plurality of replaced sub-aperture signals, expressed as: Among them, H4(t, f sub ; R B ) represents the phase conversion function, v represents the satellite radial velocity, and R B represents the straight-line distance from the radar to the point target. K scl = -2v 2 / λR ref , K scl represents the azimuth scaling factor, R ref represents the reference distance from the satellite to the center line of the scene, λ represents the wavelength, and f dc represents the Doppler center corresponding to the sub-aperture signal.

6. The method according to claim 5, characterized in that, The master device performs coherent stitching on each of the inverse Fourier transform results in the global coordinate system to obtain full-aperture image data, including: The master device calculates the number of pixels for translation for a plurality of sub-aperture complex-valued images according to the position number corresponding to each sub-aperture signal; The master device sequentially translates and superimposes each of the sub-aperture complex-valued images according to the calculated number of pixels to complete coherent stitching and obtain the full-aperture image data.

7. The method according to claim 6, characterized in that The master device uses a scaled dechirp function and the full-aperture image data to obtain an aliasing-free full-aperture image, including: The master device multiplies the scaled dechirp function and the full-aperture image data and then performs azimuth Fourier transform to obtain an aliasing-free full-aperture image.

8. The method according to claim 7, wherein The scaled dechirp function, expressed as: Wherein, H5(·) represents the scaled dechirp function.

9. An on-orbit SAR real-time imaging system based on an embedded GPU, characterized in that, Including: A master device and a plurality of slave devices; The master device is used to divide the acquired echo data into sub-apertures in the azimuth direction to obtain a plurality of sub-aperture signals, and send each of the sub-aperture signals to different node devices; Each of the node devices is used to perform Doppler center compensation on the received sub-aperture signals to obtain a plurality of compensated sub-aperture signals, perform range cell migration correction and range pulse compression processing on each of the compensated sub-aperture signals by using the chirp scaling function, range compression function and phase correction function in CSA to obtain a plurality of sub-aperture signals processed in the range direction; through a phase conversion function, replace the hyperbolic phase in each of the sub-aperture signals processed in the range direction with a standard quadratic phase function to obtain a plurality of replaced sub-aperture signals, perform azimuth inverse Fourier transform on each of the replaced sub-aperture signals, and send the inverse Fourier transform result to the master device; The master device is further used to perform coherent stitching on each of the inverse Fourier transform results in the global coordinate system to obtain full-aperture image data; The master device is further used to use a scaled dechirp function and the full-aperture image data to obtain an aliasing-free full-aperture image.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the method according to any one of claims 1-8 is implemented.

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