Satellite-borne SAR ionosphere effect estimation and correction method and device

Abstract

The invention provides a satellite-borne SAR ionosphere effect estimation and correction method and device, and belongs to the technical field of satellite-borne SAR image processing technology and electromagnetic wave atmospheric transmission effect correction, and the method comprises the steps: carrying out the range Fourier transform of an SAR echo signal, obtaining an azimuth time domain range frequency domain signal, carrying out the azimuth partitioning, and obtaining an azimuth partitioning signal; the azimuth blocking signals after blocking are selected and subjected to coherence stack noise reduction, the azimuth blocking signals after noise reduction are subjected to ionosphere estimation, an ionosphere electron content estimation value is obtained, and the ionosphere electron content is obtained based on probability evaluation; further obtaining ionized layer electron content estimation values corresponding to the blocking signals in different azimuths; ionosphere correction is carried out on the azimuth direction block signals respectively; and combining and outputting the azimuth block signals after ionosphere correction. According to the method, the problem of spatial-variant ionosphere estimation and correction caused by long synthetic aperture time can be solved through azimuth partitioning and ionosphere intensity estimation smoothing.

Description

TECHNICAL FIELD

[0001] The application belongs to the technical field of spaceborne SAR image processing and electromagnetic wave atmospheric transmission effect correction, and particularly relates to a spaceborne SAR ionospheric effect estimation and correction method and device. BACKGROUND

[0002] In the field of remote sensing, synthetic aperture radar (SAR) satellites play a key role in obtaining high-resolution images of the Earth's surface. However, the operational orbit height of SAR satellites (500 km to 800 km) requires the radar signal to pass through the ionosphere twice during transmission - a partially ionized region of the Earth's atmosphere that extends from about 50 km to about 1000 km above the ground. This process causes distortion in the amplitude and phase of the radar signal, which in turn affects the quality of the SAR image. Specifically, the group delay effect of the ionosphere causes the image to shift in the range direction, the dispersion effect reduces the range resolution, and the scintillation effect worsens the azimuth resolution. From a technical perspective, spaceborne SAR ionospheric calibration techniques can be mainly divided into two categories: one is the method of using external devices for multi-point frequency measurement, and the other is the ionospheric estimation method based on SAR echo data processing.

[0003] Technical problems of the prior art:

[0004] Harsh requirements for imaging conditions: Existing ionospheric intensity estimation and compensation methods based on SAR echo data usually require the presence of strong point targets in the imaging scene and require the image to have a high signal-to-noise ratio. However, SAR images that meet these conditions are relatively rare in practical applications, which greatly limits the applicability of this method.

[0005] High computational complexity and low timeliness: Most existing ionospheric estimation methods use non-parametric estimation, which requires multiple iterations to determine whether the SAR image data meets the imaging quality requirements, thereby determining the accuracy of the ionospheric intensity estimation value. This method has high computational complexity and poor timeliness, and is usually only suitable for ground post-processing, making it difficult to meet the needs of future on-board real-time processing. In addition, this method requires data cross-correlation operations and usually requires 2 to 3 iterations of the image formation process, further increasing the computational burden, making it unsuitable for on-board processing procedures.

[0006] Challenge of high resolution and large imaging swath: With the development of SAR technology, high-resolution and large-imaging-swath SAR systems have gradually become the mainstream. However, the amount of data generated by these systems is enormous, and existing ionospheric estimation and compensation methods are difficult to effectively process such a large amount of data, thus being unsuitable for high-resolution, large-imaging-swath spaceborne SAR systems.

[0007] The ionosphere intensity is time-varying and space-varying: the ionosphere intensity varies with time and space during the transmission of SAR radar waves in the ionosphere in the slant geometry of spaceborne SAR imaging and with the change of the azimuth time of flight. In this case, it is difficult to accurately obtain the ionosphere intensity value by relying on the traditional single-frame echo data estimation method. In addition, there are usually multiple peak targets in the SAR image, which will cause randomness in the estimation value during the ionosphere self-focusing estimation process, thereby producing false ionosphere estimation results. Therefore, it is difficult to accurately obtain the actual ionosphere intensity value in a high-resolution spaceborne SAR system by relying on the conventional ionosphere estimation process. SUMMARY

[0008] To solve the above technical problems, the present application proposes a spaceborne SAR ionosphere effect estimation and correction method and device, and the specific technical solutions are as follows:

[0009] A spaceborne SAR ionosphere effect estimation and correction method, comprising:

[0010] Step 1: performing distance Fourier transform on the SAR echo signal to obtain a range-time domain and range-frequency domain signal; performing azimuth direction blocking on the range-time domain and range-frequency domain signal to obtain an azimuth direction blocked signal by blocking the range-time domain and range-frequency domain signal according to the azimuth direction;

[0011] Step 2: selecting and coherently superimposing and denoising the blocked azimuth direction blocked signal based on a sliding window to obtain a denoised azimuth direction blocked signal;

[0012] Step 3: performing ionosphere estimation on the denoised azimuth direction blocked signal to obtain an ionosphere electron content estimation value, and obtaining the ionosphere electron content of the azimuth direction blocked signal based on probability estimation;

[0013] Step 4: performing ionosphere electron content estimation on different azimuth direction blocked signals to obtain ionosphere electron content estimation values corresponding to the different azimuth direction blocked signals;

[0014] Step 5: smoothing and fitting the ionosphere electron content estimation values of the blocked sequence, and performing ionosphere correction on the azimuth direction blocked signals, respectively;

[0015] Step 6: merging the ionosphere-corrected azimuth direction blocked signals and performing SAR imaging to output a SAR image.

[0016] A spaceborne SAR ionosphere effect estimation and correction device, comprising:

[0017] The block module performs distance Fourier transform on the SAR echo signal to obtain an azimuth time domain distance frequency domain signal; the azimuth time domain distance frequency domain signal is blocked in the azimuth direction, and the azimuth time domain distance frequency domain signal is blocked in the azimuth direction to obtain an azimuth direction block signal;

[0018] The noise reduction module selects and coherently superimposes the azimuth direction block signal after blocking based on a sliding window to obtain an azimuth direction block signal after noise reduction;

[0019] The evaluation module estimates the ionosphere based on the azimuth direction block signal after noise reduction to obtain an ionosphere electron content estimation value, and obtains the ionosphere electron content of the azimuth direction block signal based on probability evaluation; the ionosphere electron content of different azimuth direction block signals is estimated to obtain the ionosphere electron content estimation value corresponding to the different azimuth direction block signals;

[0020] The correction module smoothes and fits the block sequence ionosphere electron content estimation value, and respectively estimates the ionosphere of the azimuth direction block signal;

[0021] The output module combines the ionosphere corrected azimuth direction block signal and outputs a SAR image through SAR imaging.

[0022] An electronic device, comprising: one or more processors; a memory for storing one or more programs, wherein when the one or more programs are executed by the one or more processors, the one or more processors implement the foregoing method.

[0023] A computer readable storage medium having stored executable instructions, which are executed by a processor to make the processor implement the foregoing method.

[0024] The present application has the following beneficial effects:

[0025] The present application optimizes the data processing flow by using a one-dimensional data processing method, simplifies the originally complex two-dimensional matrix data processing into one-dimensional vector processing, significantly reduces the calculation amount, and greatly improves the efficiency of ionosphere estimation and correction. In addition, the method also solves the problem that the traditional non-three-way ionosphere estimation method based on SAR data cannot be processed on the satellite.

[0026] The present application can improve the signal-to-noise ratio of the satellite-borne SAR echo signal by using sliding window pulse coherent superposition, reduce the dependence of the self-focusing method on strong target scatterers in the scene, and the algorithm has strong adaptability.

[0027] The present application can solve the problem of space-varying ionosphere estimation and correction caused by long synthetic aperture time by blocking in the azimuth direction and estimating the ionosphere intensity smoothing. BRIEF DESCRIPTION OF DRAWINGS

[0028] Figure 1 is a flow chart of the method of the present application;

[0029] Figure 2 is a result plot of sub-band imaging;

[0030] Figure 3 is a result plot of sub-band imaging;

[0031] Figure 4 is a result plot of ionospheric estimation;

[0032] Figure 5 is a histogram distribution plot of ionospheric estimation result;

[0033] Figure 6 is a result plot of sub-band imaging;

[0034] Figure 7 is a result plot of sub-band imaging;

[0035] Figure 8 is a result plot of ionospheric estimation;

[0036] Figure 9 is a histogram distribution plot of ionospheric estimation result. DETAILED DESCRIPTION

[0037] In order to make the objects, technical solutions and advantages of the present application clearer, the present application will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and should not be used to limit the present application. In addition, the technical features involved in the various embodiments of the present application described below can be combined with each other as long as they do not conflict with each other. In order to achieve the above-mentioned purpose, the technical solutions adopted by the present application are as follows.

[0038] The present application proposes a spaceborne SAR ionospheric effect estimation and correction method, as shown in Figure 1 , comprising:

[0039] Step 1: performing distance Fourier transform on the SAR echo signal to obtain a range-time domain and range-frequency domain signal; performing range-time domain and range-frequency domain signal block processing in the azimuth direction to obtain an azimuth-direction block signal;

[0040] Step 2: selecting and performing coherent superposition noise reduction on the block-processed azimuth-direction block signal based on a sliding window to obtain a noise-reduced azimuth-direction block signal;

[0041] Step 3: performing ionospheric estimation on the noise-reduced azimuth-direction block signal by a self-focusing method to obtain an ionospheric electron content estimation value, and obtaining the ionospheric electron content of the azimuth-direction block signal based on a probability evaluation;

[0042] Step 4: Ionospheric electron content estimation is performed on the different azimuth direction block signals to obtain ionospheric electron content estimation values corresponding to the different azimuth direction block signals;

[0043] Step 5: The block sequence ionospheric electron content estimation values are smoothed and fitted, and ionospheric correction is performed on the azimuth direction block signals respectively;

[0044] Step 6: The azimuth direction block signals after ionospheric correction are combined, and SAR imaging is performed to output a SAR image.

[0045] Step 1 is specifically to perform a Fourier transform FFT on the SAR echo signal to obtain an azimuth time domain and range frequency domain signal , wherein is a one-dimensional frequency vector in the range direction, , denotes a range direction Fourier transform; after the azimuth direction block of the azimuth time domain and range frequency domain signal is performed, an azimuth direction block signal is obtained , wherein is an azimuth direction block sequence, , is the number of azimuth direction blocks; is a spaceborne SAR echo signal, wherein is a two-dimensional complex data matrix of , is the number of azimuth direction points, is the number of range direction points;

[0046] Step 2 is specifically to select consecutive one-dimensional signals in the range direction from the signal , coherently combine and superimpose to obtain a coherently denoised range direction one-dimensional signal, marked as , wherein is a coherent superposition signal sequence number, is the number of iterations of the estimation algorithm, ;

[0047] Step 3 further comprises:

[0048] Step 31, the denoised range direction one-dimensional signal is respectively passed through a band-pass filter with a sub-band bandwidth of , and the center frequency positions are and , to obtain two sub-band one-dimensional spectrum signals and , the sub-band center frequency points correspond to wavelengths and , wherein ; wherein the signal bandwidth of the spaceborne SAR system in the range direction is ;

[0049] Step 32, the conjugate multiplication is performed on two sub-band one-dimensional spectrum signals and , and inverse Fourier transform (IFFT) is performed, the inverse Fourier transform result is up-sampled by times, and the peak sampling point position is obtained by evaluation and is recorded as , which satisfies:

[0050] ;

[0051] Step 33, the position offset is calculated, which satisfies:

[0052] , wherein is the speed of light; is the sampling rate of the spaceborne SAR system in the range direction;

[0053] Step 34, the ionospheric total electron content (TEC) in the current iteration is calculated:

[0054] ;

[0055] , wherein is a constant, .

[0056] Step 35, the ionospheric phase correction term is generated:

[0057] ;

[0058] Step 36, the frequency domain phase multiplication is performed on the noise-reduced range one-dimensional signal in step 2, and is obtained.

[0059] Step 37, steps 31 to 36 are iteratively repeated until the ionospheric total electron content (TEC) estimated this time satisfies , is the residual total electron content value of the target, or the iteration number reaches the set iteration number , and the total TEC estimation value is .

[0060] Step 38, the window position is slid, the new range one-dimensional signal is selected in step 2, and the above steps are repeatedly performed, so that the ionospheric estimation value vector is obtained, and the sliding window number is recorded as .

[0061] Step 39, the vector value estimated in step 38 is subjected to probability evaluation, and the ionospheric TEC value at the maximum probability is selected as the ionospheric total electron content of the current azimuth block time range ;

[0062] Step 4 is specifically that the above steps are repeated to obtain a sequence of ionospheric TEC values corresponding to the azimuth block signals of the spaceborne SAR echo, and a numerical smoothing fitting operation is performed on the TEC sequence values to obtain the azimuth block ionospheric estimation value , is the azimuth block number;

[0063] Step 5 further comprises:

[0064] Step 51, the azimuth block signals of the spaceborne SAR echo are subjected to frequency domain ionospheric phase correction, and the correction phase is :

[0065] ;

[0066] wherein, is the carrier frequency of the spaceborne SAR system;

[0067] Step 52, the azimuth block signals are spliced and the spaceborne SAR echo is imaged.

[0068] Specific embodiments of the technical scheme of the application:

[0069] Taking the spaceborne SAR echo data processing process of a domestic urban area as an example, the parameters are shown in the following table:

[0070]

[0071] Part of the simulation images are as follows, Figure 2 is a spectral relationship diagram of the sub-band self-focusing method after coherent superposition frame, Figure 3 is a spectral one-dimensional imaging result diagram corresponding to Figure 2 , Figure 4 is the ionospheric total electron content TEC value estimation result corresponding to the 901 merged frames obtained after the steps of the application are executed, Figure 5 is a probability distribution statistical result diagram based on the 901 frame ionospheric TEC estimation result in Figure 4 , wherein the peak position corresponds to a TEC range of TECU.

[0072] According to Figure 4 ​The distribution of the ionospheric TEC estimation result can find that the ionospheric TEC estimation result will change dynamically, and a single estimation value will deviate from the true ionospheric intensity. At this time, based on the Figure 5 The ionospheric evaluation result can determine that the final ionospheric TEC is 53TECU, and the accurate estimation of the ionospheric intensity is realized.

[0073] Here, the results of the control group are also given as shown in Figures 6-9 The control group experiment is based on the same spaceborne SAR echo data, and the azimuth sliding window is not used for azimuth frame coherent stacking operation. It can be seen from the comparison that in the control group experiment, the ionospheric intensity TEC estimation value fluctuates sharply, which will seriously affect the final ionospheric TEC estimation result, as shown in Figure 8 , Figure 9 In comparison, the technical method of the application can greatly improve the effectiveness of ionospheric estimation.

[0074] The azimuth blocking method in step 1 has different blocking strategies and blocking methods according to different space-variant states, which can be replaced, for example, in general long synthetic aperture imaging, the azimuth is blocked according to the quadratic phase coefficient, dense blocking is performed at the moment of high curvature of range migration, and sparse blocking is performed at the moment of low curvature of range migration.

[0075] Steps 31 to 37 are a variant of the ionospheric estimation method based on the sub-band correlation method self-focusing algorithm, which improves the two-dimensional image self-focusing to one-dimensional data self-focusing, which belongs to the improvement in the amount of calculation. In addition to the ionospheric estimation method of the sub-band correlation method, it can be extended to other ionospheric estimation methods, such as the maximum contrast image self-focusing method (Phase Adjustment by Contrast Enhancement, PACE), the maximum entropy self-focusing method, the maximum image sharpness self-focusing method, the deep network estimation method based on metric optimization, the image self-focusing method based on Discrete Cosine Transform (DCT), the Phase Gradient Autofocus (PGA) algorithm, the MapDrift image phase estimation method, and other ionospheric estimation methods based on the above methods.

[0076] The application further provides a spaceborne SAR ionospheric effect estimation and correction device, which comprises:

[0077] The blocking module performs distance Fourier transform on the SAR echo signal to obtain an azimuth time domain distance frequency signal; and performs azimuth blocking on the azimuth time domain distance frequency signal, and performs blocking processing on the azimuth time domain distance frequency signal according to the azimuth direction to obtain an azimuth blocking signal.

[0078] The noise reduction module selects and coherently superimposes the azimuth direction block signals after blocking based on a sliding window to obtain the azimuth direction block signals after noise reduction;

[0079] The evaluation module estimates the ionosphere of the azimuth direction block signals after noise reduction to obtain the ionosphere electron content estimation value, and obtains the ionosphere electron content of the azimuth direction block signals based on probability evaluation; the ionosphere electron content of different azimuth direction block signals is estimated to obtain the ionosphere electron content estimation value corresponding to different azimuth direction block signals;

[0080] The correction module smoothes and fits the ionosphere electron content estimation value of the block sequence, and performs ionosphere correction on the azimuth direction block signals respectively;

[0081] The output module combines the azimuth direction block signals after ionosphere correction and performs SAR imaging to output a SAR image.

[0082] The present application also provides an electronic device, comprising: one or more processors; a memory for storing one or more programs, wherein when the one or more programs are executed by the one or more processors, the one or more processors implement the foregoing method.

[0083] The present application also provides a computer readable storage medium having stored executable instructions, which are executed by a processor to implement the foregoing method.

[0084] Those skilled in the art should understand that the embodiments of the present application can be provided as a method, a system, or a computer program product. Therefore, the present application can take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware aspects. Moreover, the present application can take the form of a computer program product implemented on one or more computer usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer usable program code. The solutions in the embodiments of the present application can be implemented in various computer languages, such as object-oriented programming language Java and interpreted scripting language JavaScript.

[0085] The present application is described with reference to flowcharts and / or block diagrams according to the method, device (system) and computer program product of the embodiments of the present application. It should be understood that each flow and / or block in the flowcharts and / or block diagrams, and the combination of the flows and / or blocks in the flowcharts and / or block diagrams can be implemented by computer program instructions. These computer program instructions can be provided to the processor of a general-purpose computer, a special-purpose computer, an embedded processor or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device produce a device for implementing the functions described in the flowcharts and / or block diagrams.Figure 1 one or more processes and / or functions specified in the block or blocks. Figure 1 one or more processes and / or functions specified in the block or blocks.

[0086] These computer program instructions can also be stored in a computer readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer readable memory produce an article of manufacture including instructions which implement the Figure 1 one or more processes and / or functions specified in the block or blocks. Figure 1 one or more processes and / or functions specified in the block or blocks.

[0087] These computer program instructions can also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the Figure 1 one or more processes and / or functions specified in the block or blocks. Figure 1 one or more processes and / or functions specified in the block or blocks.

[0088] While the preferred embodiments of the application have been described, additional variations and modifications can be made to the embodiments by those skilled in the art once they learn of the basic inventive concepts. Therefore, the appended claims are intended to encompass within their scope all possible variations and modifications of the preferred embodiments.

[0089] Obviously, numerous modifications and variations of the present application are possible in light of the above teachings. It is therefore to be understood that within the scope of the appended claims and their equivalents, the application can be practiced otherwise than as specifically described.

Claims

1. A method for estimating and correcting ionospheric effects in spaceborne SAR, characterized in that, include: Step 1: Perform range Fourier transform on the SAR echo signal to obtain the azimuth time-domain range-frequency domain signal; divide the azimuth time-domain range-frequency domain signal into blocks according to the azimuth direction to obtain the azimuth block signal. Step 2: Select the azimuth block signal after segmentation based on the sliding window and perform coherent superposition and noise reduction to obtain the noise-reduced azimuth block signal; Step 3: Perform ionospheric estimation on the denoised azimuth block signal to obtain the estimated ionospheric electron content, and obtain the ionospheric electron content of the azimuth block signal based on probability assessment. Step 4: Estimate the ionospheric electron content of the segmented signals in different azimuth directions to obtain the estimated ionospheric electron content corresponding to the segmented signals in different azimuth directions; Step 5: Smooth the estimated ionospheric electron content of the segmented sequence and perform ionospheric correction on the oriented segmented signals respectively; Step 6: Merge the azimuth block signals after ionospheric correction and perform SAR imaging to output SAR images.

2. The method for estimating and correcting ionospheric effects of spaceborne SAR according to claim 1, characterized in that, Step 1 specifically involves processing the SAR echo signal. Perform a Fourier transform (FFT) in the range direction to obtain the azimuth time-domain and range-frequency domain signals. ,in, It is a one-dimensional frequency vector in the range direction. , This is represented as a range-direction Fourier transform; after performing azimuth-direction block division on the azimuth time-domain and range-frequency-domain signals, the azimuth-direction block signals are obtained as follows: ,in This is a directional block sequence. , Number of blocks in the directional direction; This is a spaceborne SAR echo signal, in which, for Two-dimensional complex data matrix, For the direction of the point, This represents the distance to the points.

3. The method for estimating and correcting spaceborne SAR ionospheric effects according to claim 2, characterized in that, Step 2 specifically involves selecting a signal. Chinese direction continuous A range-oriented one-dimensional signal is coherently combined and superimposed to obtain a coherently denoised range-oriented one-dimensional signal, denoted as . ,in Numbering of coherent superimposed signal sequences, , To estimate the number of algorithm iterations, .

4. The method for estimating and correcting spaceborne SAR ionospheric effects according to claim 3, characterized in that, Step 3 further includes: Step 31, process the denoised one-dimensional range signal. Each through subband bandwidth is The center frequency points are respectively and The bandpass filter yields two sub-band one-dimensional spectral signals. and The sub-band center frequency corresponds to the wavelength and ,in Among them, the range signal bandwidth of the spaceborne SAR system is ; Step 32, for the two sub-band one-dimensional spectrum signals and Perform conjugate multiplication and inverse Fourier transform (IFFT), then process the IFFT result. The peak sampling point location obtained by doubling the sampling rate is denoted as . ,satisfy: ； Step 33, calculate the position offset. ,satisfy: ,in The speed of light; The range signal sampling rate of the spaceborne SAR system; Step 34, calculate the current The total electron content (TEC) of the ionosphere in the next iteration: ； in, It is a constant; Step 35: Generate ionospheric phase correction terms : ； Step 36, for the denoised one-dimensional range signal from step 2 Perform frequency domain phase multiplication to obtain ; Step 37: Iterate and repeat steps 31 to 36 until the estimated total ionospheric electron content TEC meets the requirements. , The target residual total electron content value, or the number of iterations. Reaching the set number of iterations The total TEC estimate is ; Step 38, slide the window position, repeat step 2 to select a new position. Given a range-directed one-dimensional signal, repeat the above steps to obtain the ionospheric estimate vector. The number of sliding window attempts is recorded as follows: ; Step 39, the estimated value obtained in step 38 The vector values ​​are used for probability assessment, and the ionospheric TEC value at the point of highest probability is selected as the total ionospheric electron content for the current azimuth block time range. .

5. The method for estimating and correcting ionospheric effects of spaceborne SAR according to claim 4, characterized in that, Step 4 specifically involves repeating step 3 above to obtain the ionospheric TEC value sequence corresponding to the azimuth block signal of the spaceborne SAR echo. A numerical smoothing fitting operation is then performed on the TEC sequence values ​​to obtain the estimated azimuth block ionospheric values. , This represents the number of blocks in the directional direction.

6. The method for estimating and correcting ionospheric effects of spaceborne SAR according to claim 5, characterized in that, Step 5 includes: Step 51: Perform frequency domain ionospheric phase correction on the azimuth block signal of the spaceborne SAR echo. The correction phase is... : ； in, For the carrier frequency of the spaceborne SAR system; Step 52: Perform azimuth-oriented block signal stitching and spaceborne SAR echo imaging.

7. The method for estimating and correcting ionospheric effects of spaceborne SAR according to claim 1, characterized in that, The azimuth partitioning in step 1 is specifically as follows: The orientation is divided into blocks based on the quadratic phase coefficient. Dense blocks are used when the distance migration is at high curvature, and sparse blocks are used when the distance migration is at low curvature.

8. A spaceborne SAR ionospheric effect estimation and correction device, characterized in that, include: The block module performs range-direction Fourier transform on the SAR echo signal to obtain the azimuth time-domain range-frequency domain signal; and performs azimuth-direction block processing on the azimuth time-domain range-frequency domain signal to obtain the azimuth-direction block signal. The noise reduction module selects the azimuth block signal after segmentation based on a sliding window and performs coherent superposition noise reduction to obtain the noise-reduced azimuth block signal. The evaluation module performs ionospheric estimation on the denoised azimuth block signal to obtain an estimated value of ionospheric electron content, and obtains the ionospheric electron content of the azimuth block signal based on probability evaluation; it also performs ionospheric electron content estimation on different azimuth block signals to obtain the estimated values ​​of ionospheric electron content corresponding to different azimuth block signals. The correction module performs smooth fitting on the estimated ionospheric electron content of the segmented sequence and performs ionospheric correction on the oriented segmented signals respectively. The output module merges the azimuth block signals after ionospheric correction and performs SAR imaging to output SAR images.

9. An electronic device, characterized in that, include: One or more processors; A memory for storing one or more programs, wherein when the one or more programs are executed by the one or more processors, the one or more processors cause the one or more processors to implement the method of any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that, It stores executable instructions that, when executed by a processor, cause the processor to perform the method described in any one of claims 1 to 7.

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