Spaceborne sliding spotlight SAR (Synthetic Aperture Radar) data processing method based on variable sampling initiation

Abstract

The invention relates to a variable sampling start-based satellite-borne sliding spotlight SAR data processing method, which comprises the following steps of: carrying out distance direction blocking on echo data of variable sampling start, carrying out Fourier transform on sub-block data along the distance direction, multiplying by a phase compensation function, and carrying out sampling start alignment; performing two-step azimuth frequency domain aliasing removal on the sub-block data after sampling initial alignment; performing two-dimensional frequency domain matched filtering on the sub-block data after the azimuth frequency domain aliasing is removed; carrying out resampling on the sub-block data subjected to two-dimensional frequency domain matched filtering; and splicing the resampled sub-block data to obtain an imaging result of the whole imaging scene. According to the method, sampling initial alignment is carried out through a distance frequency domain azimuth time domain phase compensation function, zero padding does not need to be carried out on echo data, and the data processing difficulty is reduced; the focusing quality is improved by eliminating azimuth frequency domain aliasing, two-dimensional frequency domain matched filtering and two-dimensional frequency domain resampling.

Description

Technical Field

[0001] The invention relates to the field of radar technology, and in particular to a satellite-borne sliding spotlight mode SAR data processing method based on variable sampling start. Background Art

[0002] Spaceborne synthetic aperture radar (SAR) has the capability of high-resolution earth observation all day and all weather, and is widely used in remote sensing applications such as global climate monitoring, marine and land resource surveying, and disaster monitoring. Spaceborne sliding spotlight mode SAR extends the synthetic aperture time and improves azimuth resolution by rotating the antenna beam. It has higher spatial resolution than traditional strip mode and larger azimuth mapping band width than spotlight mode. It is of great significance in urban mapping, disaster assessment, and other aspects.

[0003] However, with the improvement of resolution, the amount of sub-block data of spaceborne SAR also increases dramatically, which limits the development of spaceborne sliding beam mode SAR technology to a certain extent. In order to solve the problem of large amount of data of spaceborne sliding beam mode SAR, there are two existing methods: variable PRI (Pulse Repetition Interval) technology and variable sampling start technology. The former adjusts the instantaneous PRI according to the change of the distance from the radar to the center of the scene, so that the echo from the center of the scene always remains in the middle of the echo receiving window, thereby improving the effective data rate. The latter reduces the amount of data caused by distance migration by adjusting the sampling start of the current echo in real time.

[0004] For the sliding beam imaging mode using variable sampling start technology, the traditional signal processing method is to align the sampling start of the echo signal by zero padding in the range direction, and then use the conventional method for processing. However, for long synthetic aperture time imaging, this method requires a large amount of zero padding, which doubles the amount of sub-block data and increases the difficulty of processing; and the two-dimensional parameter space variation under the long synthetic aperture reduces the focusing effect. Summary of the invention

[0005] In order to solve the technical problems existing in the above-mentioned prior art, the object of the present invention is to provide a satellite-borne sliding spotlight mode SAR data processing method based on variable sampling start, which has the characteristics of low data processing difficulty and good focusing effect.

[0006] To achieve the above-mentioned object of the invention, the present invention provides a method for processing satellite-borne sliding spotlight mode SAR data based on variable sampling start, comprising the following steps:

[0007] Step S1, dividing the echo data of the variable sampling start into blocks in the range direction, performing Fourier transform on the sub-block data along the range direction, and multiplying the sub-block data with the range-frequency-domain-azimuth-time-domain phase compensation function to perform sampling start alignment; the range-frequency-domain-azimuth-time-domain phase compensation function is obtained by calculating the range migration of the center point of the scene within the synthetic aperture time;

[0008] Step S2, performing two-step azimuth frequency domain aliasing removal on the sub-block data after sampling start alignment;

[0009] Step S3, performing two-dimensional frequency domain matched filtering on the sub-block data after removing azimuth frequency domain aliasing;

[0010] Step S4, resampling the sub-block data after two-dimensional frequency domain matched filtering;

[0011] Step S5: splicing the resampled sub-block data to obtain an imaging result of the entire imaging scene.

[0012] According to a technical solution of the present invention, in step S1, it specifically includes:

[0013] Step S11, dividing the echo data starting from the variable sampling into blocks in the range direction;

[0014] Step S12: Perform range-direction Fourier transform on the sub-block data, perform range-direction frequency-domain phase compensation, and achieve sampling start alignment of the sub-block data with variable sampling start. The calculation formula is as follows:

[0015]

[0016] Among them, sig(t a ,t r ) represents the sub-block data starting from the variable sampling, sig 0 (t a ,t r ) represents the sub-block data after sampling start alignment, IFFT r and FFT r They represent inverse distance to Fourier transform and distance to Fourier transform, respectively, r represents the frequency in the distance direction, c represents the speed of light, and t a and t r They represent the azimuth time and the distance time respectively, j represents the imaginary unit; Δ R (t a ) represents the distance migration with time in azimuth, and its calculation formula is as follows:

[0017] Δ R (t a )=R mid -R sp (t a) (2)

[0018] Among them, R mid Represents the slant distance between the radar and the beam aiming point at the center of the synthetic aperture, R sp (t a ) represents the azimuth time t a The corresponding slant range of the radar to the beam aiming point.

[0019] According to a technical solution of the present invention, in the step S2, it specifically includes:

[0020] Step S21: construct a first orientation reference function, wherein the formula of the first orientation reference function is:

[0021]

[0022] Among them, K a represents the azimuth frequency modulation slope, and its calculation formula is:

[0023]

[0024] Among them, R rot represents the shortest slant distance from the beam aiming point to the radar track, λ represents the wavelength of the radar transmission signal, and v r Indicates the effective satellite speed;

[0025] Step S22, performing azimuth de-skewing, zero padding, Fourier transform and time domain phase compensation on the sub-block data after sampling start alignment, which is expressed as:

[0026] sig 1 (t′ a )=FFT a {Z a [sig(t a )*H 1 (t a )]}*H 2 (t′ a ) (5)

[0027] Among them, Z a [·] represents the zero-filling operator for the azimuth direction, sig 1 (t′ a ) represents the signal after anti-aliasing in azimuth, t′ a Indicates the azimuth time after zero padding, FFT a {·} represents the azimuthal Fourier transform; H 2 (t′ a ) represents the second azimuth reference function, which is used for phase compensation and its expression is:

[0028] H 2 (t′a )=exp{jπK a (t′ a ) 2} (6)

[0029] Among them, t′ a Represents the azimuth time after zero filling;

[0030] Step S23, performing azimuth frequency domain phase compensation on the sub-block data obtained in step S23, and the sub-block data after azimuth frequency domain phase compensation is expressed as:

[0031] sig′ 1 (t′ a )=IFFT a {FFT a [sig 1 (t′ a )]*H 3 (f′ a )} (7)

[0032] Among them, IFFT a H stands for inverse azimuthal Fourier transform; 3 (f′ a ) represents the third azimuth reference function, which is used for frequency domain phase compensation in azimuth. Its expression is:

[0033]

[0034] Among them, f′ a Represents the azimuth frequency after zero padding.

[0035] According to a technical solution of the present invention, in step S3, two-dimensional frequency domain matched filtering is performed by using a frequency domain reference function, and the frequency domain reference function is expressed as

[0036]

[0037] Among them, f c represents the radar carrier frequency, f r Represents the distance frequency, R ref (t′ a ) represents the slope distance obtained by polynomial fitting.

[0038] According to a technical solution of the present invention, in step S3, when the polynomial is a fourth-order model, equation (9) is expressed as:

[0039]

[0040] Among them, the azimuth time t′ after zero filling a The expression is

[0041]

[0042] f e represents the Doppler frequency, and its expression is

[0043]

[0044] k 1 ,k 2 ,k 3 ,k 4 For R ref (t′ a ) at t′ a =t′ a_c Taylor expansion coefficient, t′ a_c represents the zero Doppler moment, and

[0045] Then the sub-block data after two-dimensional frequency domain matched filtering is expressed as

[0046] sig ff (f r ,f′ a )=FFT a {FFT r [sig′ 1 (t′ a ,t r )]}*H 4 (f r ,f′ a ) (13)

[0047] Among them, FFT r Represents the distance to Fourier transform, sig′ 1 (t′ a ,t r ) represents the two-dimensional time domain signal after the azimuth aliasing is removed in two steps.

[0048] According to a technical solution of the present invention, in step S4, it specifically includes:

[0049] Step S41, using the interpolation method to perform two-dimensional frequency domain resampling on the sub-block data after matched filtering, arranging a number of reference points along the range direction and the azimuth direction, and calculating the interpolation axis;

[0050] Assume that the azimuth frequency axis and the distance frequency axis after two-dimensional frequency domain resampling are f a_new and f r_new , then the two-dimensional frequency domain resampling can be expressed as follows:

[0051]

[0052] Step S42: Perform range frequency domain phase compensation and two-dimensional inverse Fourier transform on the resampled sub-block data to obtain a precisely focused SAR image Img, which is expressed as:

[0053] Img=IFFT a {IFFT r [sig′ f ' f (f r_new ,f a_new )*H 5 (f r_new )]} (15)

[0054] Among them, H 5 (f r_new )=exp(-j2πf r_new Δ t ), used for time shift in range to eliminate the range misalignment caused by block segmentation; Δ t It is the time shift caused by the slant distance difference between the central slant distance of the sub-block data and the slant distance of the corresponding position of the entire slant distance axis.

[0055] According to one aspect of the present invention, there is provided an electronic device, comprising: one or more processors, one or more memories, and one or more computer programs; wherein the processor is connected to the memory, and the one or more computer programs are stored in the memory, and when the electronic device is running, the processor executes the one or more computer programs stored in the memory, so that the electronic device executes the above-mentioned spaceborne sliding-beam SAR data processing method based on variable sampling start.

[0056] According to one aspect of the present invention, a computer-readable storage medium is provided for storing computer instructions, and when the computer instructions are executed by a processor, the above-mentioned space-borne sliding spotlight SAR data processing method based on variable sampling start is implemented.

[0057] Compared with the prior art, the present invention has the following beneficial effects:

[0058] The present invention proposes a method for processing satellite-borne sliding spotlight mode SAR data based on variable sampling start, by performing range-wise block division and range-wise Fourier transform on echo data, and multiplying it with the range migration of the center point of the scene within the calculated synthetic aperture time to obtain the range frequency domain azimuth time domain phase compensation function, so as to achieve sampling start alignment, thereby eliminating the need for zero padding operation, reducing the difficulty of SAR data processing, and improving the SAR data processing efficiency. At the same time, the present invention removes azimuth frequency domain aliasing in two steps, completes suppression compression through two-dimensional frequency domain matched filtering, and completes residual range migration correction, residual secondary range compression and residual azimuth compression through two-dimensional frequency domain resampling, so as to obtain a precisely focused SAR image, thereby improving the imaging effect of the entire imaging scene. BRIEF DESCRIPTION OF THE DRAWINGS

[0059] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments are briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention, and for ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0060] Figure 1 A flowchart schematically shows a method for processing satellite-borne sliding spotlight mode SAR data based on variable sampling start according to an embodiment of the present invention;

[0061] Figure 2 A schematic diagram showing the position of a variable sampling start echo window in a receiving window according to an embodiment of the present invention;

[0062] Figure 3 A schematic diagram schematically showing echoes collected by a conventional method of simulation according to an embodiment of the present invention;

[0063] Figure 4 A schematic diagram schematically showing a simulated variable sampling start echo according to an embodiment of the present invention;

[0064] Figure 5 A schematic diagram schematically showing a two-dimensional spectrum of variable sampling start echo data according to an embodiment of the present invention;

[0065] Figure 6 A schematic diagram schematically showing a two-dimensional spectrum of variable sampling initial echo data after two-step anti-aliasing according to an embodiment of the present invention;

[0066] Figure 7 A schematic diagram schematically showing a result of echo range compression of a traditional method simulated according to an embodiment of the present invention;

[0067] Figure 8 A schematic diagram schematically showing a simulation result of variable sampling start echo distance compression according to an embodiment of the present invention;

[0068] Fig. 9 A schematic diagram schematically showing a target 1 image result of a simulation with variable sampling starting data points according to an embodiment of the present invention;

[0069] Fig.10 A schematic diagram schematically showing the imaging result of a target 2 with variable sampling starting data points according to an embodiment of the present invention;

[0070] Fig.11A schematic diagram schematically showing a slice of imaging result of target 1 with variable sampling starting data points according to one embodiment of the present invention;

[0071] Fig.12 A schematic diagram schematically showing a slice of a simulation result of imaging a target 2 with variable sampling starting data points according to an embodiment of the present invention; DETAILED DESCRIPTION

[0072] The description of the embodiments of this specification should be combined with the corresponding drawings, which should be considered as part of the complete specification. In the drawings, the shape or thickness of the embodiments may be enlarged and indicated for simplification or convenience. Furthermore, the parts of each structure in the drawings will be described separately. It is worth noting that the elements not shown in the drawings or not described in words are in a form known to ordinary technicians in the relevant technical field.

[0073] The description of the embodiments herein and any reference to directions and orientations are only for the convenience of description and are not to be construed as any limitation on the scope of protection of the present invention. The following description of the preferred embodiments may involve combinations of features, which may exist independently or in combination, and the present invention is not particularly limited to the preferred embodiments. The scope of the present invention is defined by the claims.

[0074] like Figure 1 As shown, a method for processing satellite-borne sliding spotlight mode SAR data based on variable sampling start of the present invention comprises the following steps:

[0075] Step S1, dividing the echo data of the variable sampling start into blocks in the range direction, performing Fourier transform on the variable sampling start data of the sub-block data along the range direction, and multiplying it with the range frequency domain azimuth time domain phase compensation function to perform sampling start alignment; the range frequency domain azimuth time domain phase compensation function is obtained by calculating the range migration of the scene center point within the synthetic aperture time;

[0076] Step S2, performing two-step azimuth frequency domain aliasing removal on the sub-block data after sampling start alignment;

[0077] Step S3, performing two-dimensional frequency domain matched filtering on the sub-block data after removing azimuth frequency domain aliasing;

[0078] Step S4, resampling the sub-block data after two-dimensional frequency domain matched filtering;

[0079] Step S5: splicing the resampled sub-block data to obtain an imaging result of the entire imaging scene.

[0080] The present invention divides echo data into blocks in the range direction, performs Fourier transform in the range direction on sub-block data, calculates the range migration of the center point of the scene within the synthetic aperture time, obtains the range frequency domain azimuth time domain phase compensation function, realizes the sampling start alignment of the sub-block data, and the operation does not need to fill zero, which greatly reduces the processing difficulty of the sub-block data and improves the data processing efficiency; eliminates aliasing in the azimuth frequency domain through a two-step method, realizes consistent compression through two-dimensional frequency domain matched filtering, respectively sets reference points along the range direction and the azimuth direction, calculates the range frequency and azimuth frequency interpolation axes, performs two-dimensional frequency domain resampling, completes residual range migration correction, residual secondary range compression, residual azimuth compression and space-variant error compensation; compensates for the misalignment between different blocks through range frequency domain phase multiplication, obtains accurately focused range sub-block SAR images through two-dimensional Fourier inverse transform, performs image splicing on the obtained range sub-block SAR images, and obtains the imaging result of the entire imaging scene.

[0081] The embodiments of the present invention are described in detail below with reference to the accompanying drawings.

[0082] The spaceborne sliding restraint mode SAR data processing method based on variable sampling start provided in this embodiment includes the following steps:

[0083] Step S1: performing range-wise block division on the echo data starting from the variable sampling, and performing start alignment processing on the sub-block data starting from the variable sampling.

[0084] Figure 2 The schematic diagram of the position of the variable sampling start echo window in the receiving window in this embodiment is shown, with the vertical direction being the azimuth direction and the horizontal direction being the distance direction. Figure 2 It can be seen that since the sampling start of the sub-block data varies with the azimuth time, the sampling start alignment needs to be performed before imaging processing.

[0085] In step S1, it specifically includes:

[0086] Step S11, dividing the echo data starting from the variable sampling into blocks in the range direction;

[0087] Step S12: Perform a range Fourier transform on the sub-block data at the start of the variable sampling, convert it to the range frequency domain, perform range frequency domain phase compensation, and achieve the start alignment of the time domain data sampling. This process can be expressed as:

[0088]

[0089] Among them, sig(t a ,t r ) represents the sub-block data of the variable sampling start, sig 0 (t a ,t r ) represents the sub-block data after sampling start alignment, IFFTr and FFT r They represent inverse distance to Fourier transform and distance to Fourier transform, respectively, r represents the distance frequency, c represents the speed of light, t a and t r They represent azimuth time and distance time respectively, and j represents an imaginary unit.

[0090] Δ R (t a ) represents the distance migration that changes with time in azimuth, and its calculation formula is expressed as:

[0091] Δ R (t a )=R mid -R sp (t a ) (2)

[0092] R mid Represents the slant distance from the center of the scene at the center of the synthetic aperture.

[0093] By using the above method, no zero padding operation is required after the distance sampling start alignment.

[0094] Step S2: performing two-step azimuth frequency domain aliasing removal on the sub-block data after sampling start alignment.

[0095] Specifically include:

[0096] Step S21: construct a first orientation reference function, the formula of the first orientation reference function is:

[0097]

[0098] Among them, K a represents the azimuth frequency modulation slope, and its calculation formula is:

[0099]

[0100] Where R rot represents the shortest slant distance from the beam aiming point to the radar track, λ represents the wavelength of the radar transmission signal, and v r Indicates the effective satellite speed;

[0101] Step S22, perform azimuth de-skewing, zero padding, Fourier transform and time domain phase compensation on the sub-block data after sampling start alignment. The process is expressed as

[0102] sig 1 (t′ a )=FFT a {Z a [sig(t a )*H1 (t a )]}*H 2 (t′ a ) (5)

[0103] Among them, sig 1 (t′ a ) represents the signal after anti-aliasing in azimuth, Z a [·] indicates zero-padding operator, FFT a {·} represents the azimuthal Fourier transform, H 2 (t′ a ) represents the second azimuth reference function, which is used for phase compensation and its expression is:

[0104] H 2 (t′ a )=exp{jπK a (t′ a ) 2} (6)

[0105] where t′ a Represents the azimuth time after zero filling;

[0106] Step S23, performing azimuth frequency domain phase compensation on the sub-block data obtained in step S22, and the sub-block data after azimuth frequency domain phase compensation is expressed as:

[0107] sig′ 1 (t′ a )=IFFT a {FFT a [sig 1 (t′ a )]*H 3 (f′ a )} (7)

[0108] Among them, IFFT a H stands for inverse azimuthal Fourier transform; 3 (f′ a ) represents the third azimuth reference function, which is used for frequency domain phase compensation in azimuth. Its expression is:

[0109]

[0110] Among them, f′ a Represents the azimuth frequency after zero padding.

[0111] Figure 3 and Figure 4 and Figure 5 and Figure 6The echo data with variable sampling start and the traditional echo data before and after range compression are compared, and it can be seen that the range migration corresponding to the variable sampling start is significantly reduced. Figure 5 , 6 As shown, according to Figure 5 , 6 It can be seen that after the two-step processing, the azimuth frequency domain aliasing has been eliminated.

[0112] Step S3, performing two-dimensional frequency domain matched filtering on the sub-block data after removing azimuth frequency domain aliasing;

[0113] In the step S3, it specifically includes:

[0114] Construct the frequency domain reference function, expressed as

[0115]

[0116] Among them, f c represents the radar carrier frequency, f r Represents the distance frequency, R ref (t′ a ) represents the slope distance obtained by polynomial fitting.

[0117] This embodiment adopts a fourth-order model. Taking the fourth-order model as an example, formula (9) can be expressed as:

[0118]

[0119] Among them, the azimuth time t′ after zero filling a It can be expressed as follows

[0120]

[0121] f e It can be expressed as

[0122]

[0123] k 1 ,k 2 ,k 3 ,k 4 For R ref (t′ a ) at t′ a =t′ a_c Taylor expansion coefficient, t′ a_c represents the zero Doppler moment, and

[0124] Then, after two-dimensional frequency domain matched filtering, the frequency domain signal is

[0125] sig ff (fr ,f′ a )=FFT a {FFT r [sig′ 1 (t′ a ,t r )]}*H 4 (f r ,f′ a ) (13)

[0126] Among them, FFT r Represents the distance to Fourier transform, sig′ 1 (t′ a ,t r ) represents the two-dimensional time domain signal after the azimuth aliasing is removed in two steps.

[0127] Step S4: resample the sub-block data after two-dimensional frequency domain matched filtering.

[0128] Specifically include:

[0129] Step S41, using the interpolation method to perform two-dimensional frequency domain resampling on the sub-block data after matched filtering, arranging a number of reference points along the range direction and the azimuth direction, and calculating the interpolation axis;

[0130] Assume that the azimuth and distance frequency axes after two-dimensional frequency domain resampling are f a_new and f r_new , the resampling process can be expressed as follows:

[0131]

[0132] Step S42: Perform two-dimensional inverse Fourier transform on the resampled data, perform range-frequency domain phase compensation, and obtain a precisely focused SAR image Img, as shown below:

[0133] Img=IFFT a {IFFT r [sig″ ff (f r_new ,f a_new )*H 5 (f r_new )]} (12)

[0134] Among them, H 5 (f r_new )=exp(-j2πf r_new Δ t ) is used to perform time shift in the range direction and eliminate the range misalignment caused by block division. tIt is the time shift caused by the slant range difference between the center slant range of the current block and the corresponding position of the entire slant range axis. The entire slant range axis refers to the slant range axis of the complete echo data before resampling.

[0135] Step S5: splicing the resampled sub-block data to obtain an imaging result of the entire imaging scene.

[0136] Fig. 9 , 10 The imaging results of two simulated point targets are shown. Point targets 1 and 2 are located in the upper right corner and lower right corner of the simulation scene respectively. The vertical direction is the azimuth and the horizontal direction is the distance. In order to observe the focus quality of the point targets, Fig.11 , 12 They were given Fig. 9 , 10 Slices of imaging results of two point targets.

[0137] According to one aspect of the present invention, there is provided an electronic device, comprising: one or more processors, one or more memories, and one or more computer programs; wherein the processor is connected to the memory, and the one or more computer programs are stored in the memory, and when the electronic device is running, the processor executes the one or more computer programs stored in the memory, so that the electronic device performs the above-mentioned method for processing satellite-borne sliding beam mode SAR data based on variable sampling start.

[0138] The processor may be a central processing unit (CPU), or other general-purpose processors, a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field-programmable gate array (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor may be a microprocessor or the processor may be any conventional processor, etc.

[0139] According to one aspect of the present invention, a computer-readable storage medium is provided for storing computer instructions. When the computer instructions are executed by a processor, a space-borne sliding spotlight mode SAR data processing method based on variable sampling start is implemented as described above.

[0140] Computer-readable storage media may include any medium capable of storing or transmitting information. Examples of computer-readable storage media include electronic circuits, semiconductor memory devices, ROM, flash memory, erasable ROM (EROM), floppy disks, CD-ROMs, optical disks, hard disks, optical fiber media, radio frequency (RF) links, etc. Code segments may be downloaded via computer networks such as the Internet, intranets, etc.

[0141] In addition, it should be noted that the present invention can be provided as a method, an apparatus or a computer program product. Therefore, the embodiments of the present invention can take the form of a complete hardware embodiment, a complete software embodiment or an embodiment combining software and hardware. Moreover, the embodiments of the present invention can take the form of a computer program product implemented on one or more computer-usable storage media containing computer-usable program code.

[0142] The embodiments of the present invention are described with reference to the flowcharts and / or block diagrams of the methods, terminal devices (systems), and computer program products according to the embodiments of the present invention. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of the processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, an embedded processor, or other programmable data processing terminal device to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing terminal device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0143] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing terminal device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce a manufactured product including an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 These computer program instructions can also be loaded onto a computer or other programmable data processing terminal device, so that a series of operation steps are executed on the computer or other programmable terminal device to produce a computer-implemented process, so that the instructions executed on the computer or other programmable terminal device provide for implementing the process in the process. Figure 1 A process or multiple processes and / or boxes Figure 1 A step that specifies a function in one or more boxes.

[0144] It should also be noted that, in this article, the terms "include", "comprises" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or terminal device including a series of elements includes not only those elements, but also includes other elements not explicitly listed, or also includes elements inherent to such process, method, article or terminal device. In the absence of further restrictions, the elements defined by the sentence "comprises a ..." do not exclude the existence of other identical elements in the process, method, article or terminal device including the elements.

[0145] Finally, it should be noted that the above is a preferred embodiment of the present invention. It should be pointed out that although the preferred embodiment of the present invention has been described, for those skilled in the art, once the basic creative concept of the present invention is known, several improvements and modifications can be made without departing from the principles of the present invention, and these improvements and modifications should also be regarded as the protection scope of the present invention. Therefore, the attached claims are intended to be interpreted as including the preferred embodiment and all changes and modifications that fall within the scope of the embodiments of the present invention.

Claims

1. A method for processing spaceborne sliding spotlight SAR data based on variable sampling start, characterized in that: The following steps are involved: Step S1, dividing the echo data of the variable sampling start into blocks in the range direction, performing Fourier transform on the sub-block data along the range direction, and multiplying them with the range frequency domain azimuth time domain phase compensation function to perform sampling start alignment; The distance-frequency-domain-azimuth-time-domain-phase compensation function is obtained by calculating the distance migration of the center point of the scene within the synthetic aperture time; Step S2, performing two-step azimuth frequency domain aliasing removal on the sub-block data after sampling start alignment; Step S3, performing two-dimensional frequency domain matched filtering on the sub-block data after removing azimuth frequency domain aliasing; Step S4, resampling the sub-block data after two-dimensional frequency domain matched filtering; Step S5: splicing the resampled sub-block data to obtain an imaging result of the entire imaging scene.

2. The method for processing satellite-borne sliding spotlight SAR data based on variable sampling start according to claim 1, characterized in that: In the step S1, it specifically includes: Step S11, dividing the echo data starting from the variable sampling into blocks in the range direction; Step S12: Perform a range-direction Fourier transform on the sub-block data, perform range-direction frequency-domain phase compensation, and achieve sampling start alignment of the sub-block data with variable sampling start. The calculation formula is expressed as: Among them, sig(t a ,t r ) represents the sub-block data at the start of variable sampling, sig0(t a ,t r ) represents the sub-block data after sampling start alignment, IFFT r and FFT r They represent inverse distance to Fourier transform and distance to Fourier transform, respectively, r represents the frequency in the distance direction, c represents the speed of light, and t a and t r They represent the azimuth time and the distance time respectively, j represents the imaginary unit; Δ R (t a ) represents the distance migration that changes with time in azimuth, and its calculation formula is expressed as: Δ R (t a )=R mid -R sp (t a ) (2) Among them, R mid Represents the slant distance between the radar and the beam aiming point at the center of the synthetic aperture, R sp (t a ) represents the azimuth time t a The corresponding slant range of the radar to the beam aiming point.

3. The method for processing satellite-borne sliding spotlight SAR data based on variable sampling start according to claim 2, characterized in that: In the step S2, it specifically includes: Step S21: construct a first orientation reference function, wherein the formula of the first orientation reference function is: Among them, K a represents the azimuth frequency modulation slope, and its calculation formula is: Among them, R rot represents the shortest slant distance from the beam aiming point to the radar track, λ represents the wavelength of the radar transmission signal, and v r Indicates the effective satellite speed; Step S22, performing azimuth de-skewing, zero padding, Fourier transform and time domain phase compensation on the sub-block data after sampling start alignment, which is expressed as: sig1(t′ a )=FFT a {Z a [sig(t a )*H1(t a )]}*H2(t′ a ) (5) Among them, Z a [·] represents the zero-filling operator in the azimuth direction, sig1(t′ a ) represents the signal after anti-aliasing in azimuth, t a ′ represents the azimuth time after zero padding, FFT a {·} represents the azimuth Fourier transform; H2(t′ a ) represents the second azimuth reference function, which is used for phase compensation and its expression is: H2(t′ a )=exp{jπK a (t′ a ) 2 } (6); Step S23, performing azimuth frequency domain phase compensation on the sub-block data obtained in step S22, and the sub-block data after azimuth frequency domain phase compensation is expressed as: sig1′(t a ′)=IFFT a {FFT a [sig1(t a ′)]*H3(f a ′)} (7) Among them, IFFT a represents the inverse azimuth Fourier transform; H3(f′ a ) represents the third azimuth reference function, which is used for frequency domain phase compensation in azimuth. Its expression is: Among them, f a ′ represents the azimuth frequency after zero padding.

4. The method for processing satellite-borne sliding spotlight SAR data based on variable sampling start according to claim 3, characterized in that: In step S3, two-dimensional frequency domain matched filtering is performed using a frequency domain reference function, where the frequency domain reference function is expressed as Among them, f c represents the radar carrier frequency, f r Represents the distance frequency, R ref (t′ a ) represents the slope distance obtained by polynomial fitting.

5. The method for processing spaceborne sliding spotlight SAR data based on variable sampling start according to claim 4, characterized in that: In step S3, when the polynomial is a fourth-order model, equation (9) is expressed as: Among them, the azimuth time after zero filling is t a The expression of ′ is f e represents the Doppler frequency, and its expression is k1, k2, k3, k4 are R ref (t′ a ) at t′ a =t′ a_c Taylor expansion coefficient, t′ a_c represents the zero Doppler moment, and Then the sub-block data after two-dimensional frequency domain matched filtering is expressed as sig ff (f r ,f a ′)=FFT a {FFT r [sig1′(t a ′,t r )]}*H4(f r ,f a ′) (13) Among them, FFT r Represents the distance to Fourier transform, sig1′(t a ′,t r ) represents the two-dimensional time domain signal after the azimuth aliasing is removed in two steps.

6. The method for processing satellite-borne sliding spotlight SAR data based on variable sampling start according to claim 4, characterized in that: In the step S4, it specifically includes: Step S41, using the interpolation method to perform two-dimensional frequency domain resampling on the sub-block data after matched filtering, arranging a number of reference points along the range direction and the azimuth direction, and calculating the interpolation axis; Assume that the azimuth frequency axis and the distance frequency axis after two-dimensional frequency domain resampling are f a_new and f r_new , then the two-dimensional frequency domain resampling can be expressed as follows: Step S42: Perform range frequency domain phase compensation and two-dimensional inverse Fourier transform on the resampled sub-block data to obtain a precisely focused SAR image Img, which is expressed as: Img=IFFT a {IFFT r [sig′ f ′ f (f r_new ,f a_new )*H5(f r_new )]} (15) Among them, H5(f r_new )=exp(-j2πf r_new Δ t ), used for time shift in range to eliminate the range misalignment caused by block segmentation; Δ t It is the time shift caused by the slant distance difference between the central slant distance of the sub-block data and the slant distance of the corresponding position of the entire slant distance axis.

7. An electronic device, characterized in that: include: One or more processors, one or more memories, and one or more computer programs; wherein the processor is connected to the memory, and the one or more computer programs are stored in the memory. When the electronic device is running, the processor executes the one or more computer programs stored in the memory, so that the electronic device executes the space-borne sliding spotlight SAR data processing method based on variable sampling start as described in any one of claims 1 to 6.

8. A computer-readable storage medium, characterized in that: Used to store computer instructions, which, when executed by a processor, implement the space-borne sliding spotlight SAR data processing method based on variable sampling start according to any one of claims 1 to 6.

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