Time series cross-calibration method and system for synthetic aperture radar

Abstract

The present invention relates to a time series cross-calibration method and system for a synthetic aperture radar. The method comprises: screening a target area for time series cross-calibration; generating SAR image data pairs at each moment within a time range; extracting a median matrix of a data slice at a single moment using a window median method, obtaining a median matrix array, performing robust regression fitting with outlier removal, and generating a radiation calibration coefficient array; processing the radiation calibration coefficient array according to a final reference value of the radiation calibration coefficient, and obtaining a final radiation calibration coefficient. By performing robust regression fitting with outlier removal on the median matrix array, interference from outliers is avoided; calculating the radiation calibration coefficient corresponding to each single moment, using the correlation of the radiation calibration coefficients between different moments as a reference, combining the radiation calibration coefficient value measured at the moment to be calibrated and the radiation calibration coefficient value at the previous moment, and determining the final reference value of the radiation calibration coefficient, thereby improving calibration accuracy.

Description

Technical Field

[0001] The present invention relates to the technical field of synthetic aperture radar (SAR) radiation calibration, and in particular to a time series cross calibration method and system for synthetic aperture radar. Background Art

[0002] As an active microwave imaging system, synthetic aperture radar (SAR) can acquire high-resolution surface imagery around the clock and in all weather conditions. It has become a crucial technology for applications such as environmental monitoring, disaster assessment, and marine protection. With the continuous expansion of these applications, traditional qualitative remote sensing methods are no longer sufficient. Accurate ground object scattering information from remote sensing images is required to enable quantitative applications of remote sensing data. The key to achieving quantitative SAR remote sensing applications lies in SAR radiometric calibration, a process that establishes a relationship between the digital quantization value (DN) of a SAR image and the backscatter coefficient of ground objects, enabling quantitative acquisition of surface physical parameters (such as soil moisture and dielectric constant). Radiometric calibration is crucial for the quantitative extraction and accurate interpretation of electromagnetic information about ground object characteristics in SAR images. However, due to factors such as component aging and environmental changes, the radiometric performance of SAR satellite sensors inevitably changes during space operations, especially after their design lifespan. If the radiation calibration coefficient is not updated in time, the acquisition of ground object target characteristic information will be distorted, and the subtle changes in ground objects introduced by changes in external environmental factors may be masked, thereby affecting the accuracy of SAR quantitative remote sensing applications.

[0003] Existing SAR absolute radiometric calibration techniques can be divided into field calibration and cross-radiometric calibration. Field calibration utilizes a manual calibrator deployed at the calibration site. The satellite to be calibrated passes through the calibration site and images the manual calibrator to obtain the response energy. This energy is then combined with the known theoretical value of the calibrator's radar cross section (RCS) to calculate the absolute radiometric calibration coefficient. However, the limited number of deployed manual calibrators and the long revisit period of SAR satellites make frequent calibration difficult. Cross-radiometric calibration is a novel SAR radiometric calibration technique. This technique uses a highly calibrated satellite as a reference satellite. Both the reference satellite and the satellite to be calibrated observe the same stable ground reference target. The satellite to be calibrated obtains the response energy of the reference target and then calculates the absolute radiometric calibration coefficient based on the reference target's backscatter coefficient obtained from the reference satellite. Field calibration uses a manual calibrator as the reference target, while cross-radiometric calibration uses a larger number of stable ground targets, effectively increasing calibration frequency.

[0004] However, existing radiation cross-calibration technical solutions often rarely consider interference, resulting in poor calibration accuracy. Summary of the Invention

[0005] Based on this, in order to solve the above technical problems, a time series cross-calibration method and system for synthetic aperture radar are provided, which can improve the accuracy and efficiency of calibration.

[0006] A time series cross-calibration method for synthetic aperture radar, the method comprising:

[0007] Determining a reference satellite and a satellite to be calibrated, determining a distribution target based on the reference satellite and the satellite to be calibrated, obtaining position information of the distribution target, and performing regional screening within the spatial range of the distribution target based on the position information to obtain a target area for time series cross calibration;

[0008] Acquiring imaging parameters of the reference satellite and the satellite to be calibrated, determining a time range for time series cross calibration based on the imaging parameters and position information, cropping data slices for time series cross calibration based on the position information, and generating SAR image data pairs corresponding to the distributed targets at each moment within the time range;

[0009] The median matrix of the data slices at a single moment is extracted respectively by using the window median method to obtain a median matrix array, and the median matrix array is subjected to robust regression fitting with outliers removed to output the radiation calibration coefficient at the single moment;

[0010] Determining a reference radiation calibration coefficient, and obtaining a final reference value of the radiation calibration coefficient according to the reference radiation calibration coefficient and the radiation calibration coefficient;

[0011] Within the time range, the radiation calibration coefficient corresponding to each single moment is calculated respectively to generate a radiation calibration coefficient array; the radiation calibration coefficient array is error processed according to the final reference value of the radiation calibration coefficient to obtain the final radiation calibration coefficient, thereby completing the time series cross calibration.

[0012] In one embodiment, obtaining the location information of the distribution target and performing area screening within the spatial range of the distribution target based on the location information to obtain a target area for time series cross calibration includes:

[0013] Acquiring time-series SAR data of the reference satellite according to the position information, and preprocessing the time-series SAR data to obtain a time-series RCS value image corresponding to the distributed target;

[0014] Based on the time series RCS value image, regional screening is performed within the spatial range of the distribution target to obtain a target area for time series cross calibration.

[0015] In one embodiment, performing regional screening within the spatial range of the distribution target based on the time-series RCS value image includes:

[0016] Performing a primary screening of regions based on the time-series RCS value image to obtain each primary screening region;

[0017] According to the position information of each of the primary screening areas, the time series RCS value slices are cut respectively;

[0018] Extracting each time series backscatter coefficient corresponding to each time series RCS value slice using a window median method, and calculating an average backscatter coefficient corresponding to the time series backscatter coefficient;

[0019] The target area is screened out from each of the primary screening areas according to the time series backscatter coefficient and the average backscatter coefficient through the root mean square error.

[0020] In one embodiment, cutting data slices for time series cross-calibration based on the position information and generating SAR image data pairs corresponding to the distribution targets at each moment within the time range include:

[0021] Cut out reference satellite RCS value data slices and to-be-calibrated satellite DN value data slices of the target area based on the position information;

[0022] determining a radiation calibration requirement, and filtering out SAR image data from the data slices within the time range according to the radiation calibration requirement;

[0023] Data cropping is performed on the SAR image data to obtain SAR image data pairs corresponding to the distribution targets.

[0024] In one embodiment, a window median method is used to extract the median matrix of the data slices at a single moment, to obtain a median matrix array, including:

[0025] Get the set window size;

[0026] According to the window size, a median matrix is ​​extracted from the RCS value data slice and the DN value data slice using a window median method to obtain an RCS value median matrix and a DN value median matrix;

[0027] The RCS value median matrix and the DN value median matrix at each single moment in the time range are collected to obtain an RCS value median matrix array and a DN value median matrix array.

[0028] In one embodiment, performing robust regression fitting with outlier removal on the median matrix array and outputting the radiation calibration coefficient at the single moment includes:

[0029] Perform robust regression fitting using all data points in the DN value median matrix as independent variables and all data points in the RCS value median matrix array as dependent variables to obtain fitting results;

[0030] Calculating a residual array of the data points of the fitting result, and calculating a residual control interval based on the residual array;

[0031] Data points outside the residual control interval are treated as outliers and removed, and the median matrix array after removing the outliers is subjected to robust regression fitting again until all data points are within the residual control interval;

[0032] The fitting result corresponding to all data points being within the residual control interval is used as the radiation calibration coefficient at the single moment.

[0033] In one embodiment, obtaining a final reference value of the radiation calibration coefficient according to the reference radiation calibration coefficient and the radiation calibration coefficient includes:

[0034] Calculate the reference radiation calibration coefficient and the average of the radiation calibration coefficients, and use the average as a final reference value of the radiation calibration coefficient.

[0035] In one embodiment, performing error processing on the radiation calibration coefficient array according to the final reference value of the radiation calibration coefficient to obtain the final radiation calibration coefficient includes:

[0036] Calculating the difference between each radiation calibration coefficient in the radiation calibration coefficient array and the reference radiation calibration coefficient respectively;

[0037] Based on the gap value, several target radiation calibration coefficients are selected and weighted summed to obtain a final radiation calibration coefficient.

[0038] In one embodiment, the method further comprises:

[0039] Obtaining the radiation calibration coefficient at each moment, and generating a SAR radiation cross calibration coefficient time series curve according to the radiation calibration coefficient;

[0040] A satellite sensor attenuation model is constructed according to the timing curve.

[0041] A time series cross-calibration system for synthetic aperture radar, comprising:

[0042] an area screening module, configured to determine a reference satellite and a satellite to be calibrated, determine a distribution target based on the reference satellite and the satellite to be calibrated, obtain position information of the distribution target, and perform area screening within the spatial range of the distribution target based on the position information to obtain a target area for time series cross calibration;

[0043] a data pair acquisition module, configured to acquire imaging parameters of the reference satellite and the satellite to be calibrated, determine a time range for time series cross calibration based on the imaging parameters and position information, crop data slices for time series cross calibration based on the position information, and generate SAR image data pairs corresponding to the distributed targets at each moment within the time range;

[0044] A single moment radiation calibration coefficient acquisition module is used to extract the median matrix of the data slice at a single moment using the window median method to obtain a median matrix array, and perform robust regression fitting on the median matrix array to eliminate outliers, and output the radiation calibration coefficient at the single moment;

[0045] A calibration coefficient adjustment module is used to determine a reference radiation calibration coefficient, and obtain a final reference value of the radiation calibration coefficient according to the reference radiation calibration coefficient and the radiation calibration coefficient;

[0046] The cross calibration module is used to calculate the radiation calibration coefficient corresponding to each single moment within the time range and generate a radiation calibration coefficient array; perform error processing on the radiation calibration coefficient array according to the final reference value of the radiation calibration coefficient to obtain the final radiation calibration coefficient, thereby completing the time series cross calibration.

[0047] The above-mentioned synthetic aperture radar time series cross-calibration method and system avoids the interference of outliers and improves the accuracy of radiation calibration coefficients by performing robust regression fitting on the median matrix array to eliminate outliers. By generating SAR image data pairs at each moment within a time range, and then calculating the radiation calibration coefficient corresponding to each single moment, the correlation of the radiation calibration coefficients at different moments is used as a reference. The radiation calibration coefficient value measured at the time to be calibrated and the radiation calibration coefficient value at the previous moment are combined to determine the final reference value of the radiation calibration coefficient, thereby improving the accuracy of calibration and effectively reducing the uncertainty of a single calibration. BRIEF DESCRIPTION OF THE DRAWINGS

[0048] Figure 1 FIG. 1 is an application environment diagram of a time series cross-calibration method for a synthetic aperture radar according to an embodiment;

[0049] Figure 2 1 is a flow chart of a time series cross-calibration method for a synthetic aperture radar according to an embodiment;

[0050] FIG3( a ) is a schematic diagram showing the position distribution of nine target areas in one embodiment;

[0051] FIG3( b ) is a schematic diagram of the histogram distribution of 9 target areas in one embodiment;

[0052] Figure 4 A schematic diagram of a time series cross-reference target data pair composition for time series cross-calibration in one embodiment;

[0053] Figure 5 A schematic diagram of a process for obtaining a median matrix array in a target area using a window median method in one embodiment;

[0054] Figure 6 A result diagram of a time series curve of a SAR radiation cross-calibration coefficient in one embodiment;

[0055] Figure 7 1 is a flow chart of a time series cross-calibration method for synthetic aperture radar according to another embodiment;

[0056] Figure 8 is a structural block diagram of a time series cross-calibration system for a synthetic aperture radar in one embodiment;

[0057] Figure 9 FIG. 1 is a diagram showing the internal structure of a computer device in one embodiment. DETAILED DESCRIPTION

[0058] In order to make the purpose, technical solutions and advantages of this application more clear, the following further describes this application in detail with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain this application and are not intended to limit this application.

[0059] The time series cross calibration method of synthetic aperture radar provided in the embodiment of the present application can be applied to Figure 1 In the application environment shown. Figure 1As shown, the application environment includes a computer device 110. The computer device 110 can determine the reference satellite and the satellite to be calibrated, determine the distribution target based on the reference satellite and the satellite to be calibrated, obtain the position information of the distribution target, and perform regional screening within the spatial range of the distribution target based on the position information to obtain the target area for time series cross calibration; the computer device 110 can obtain the imaging parameters of the reference satellite and the satellite to be calibrated, determine the time range for time series cross calibration based on the imaging parameters and position information, crop the data slices for time series cross calibration based on the position information, and generate SAR image data pairs corresponding to the distribution target at each moment within the time range; the computer device 110 can use The window median method extracts the median matrix of the data slices at a single moment to obtain a median matrix array, and then performs a robust regression fitting on the median matrix array to eliminate outliers, outputting the radiation calibration coefficient at a single moment. The computer device 110 can determine a reference radiation calibration coefficient and obtain a final reference value of the radiation calibration coefficient based on the reference radiation calibration coefficient and the radiation calibration coefficient. The computer device 110 can calculate the radiation calibration coefficient corresponding to each single moment within a time range to generate a radiation calibration coefficient array. The radiation calibration coefficient array is error-processed based on the final reference value of the radiation calibration coefficient to obtain the final radiation calibration coefficient, thereby completing the time series cross-calibration. The computer device 110 can be, but is not limited to, various personal computers, laptops, smartphones, robots, unmanned aerial vehicles, and other devices.

[0060] In one embodiment, Figure 2 As shown, a time series cross-calibration method for synthetic aperture radar is provided, comprising the following steps:

[0061] Step 202: Determine the reference satellite and the satellite to be calibrated, determine the distribution target based on the reference satellite and the satellite to be calibrated, obtain the location information of the distribution target, and perform regional screening within the spatial range of the distribution target based on the location information to obtain the target area for time series cross calibration.

[0062] First, the computer can screen target areas for time series cross-calibration, preparing the location information for multiple target areas for subsequent calibration. The target area selection is primarily based on the statistical characteristics of the SAR image histogram distribution and temporal scattering stability of the target area. The operator can use the computer to select the reference satellite and the satellite to be calibrated. Specifically, the operator can select a calibrated high-radiometric SAR satellite as the reference satellite to perform radiometric calibration on the satellite to be calibrated.

[0063] In this embodiment, the image data used can be images from the Sentinel-1 series of satellites. As part of the European Space Agency's Copernicus Earth Observation Program, the Sentinel-1 series of satellites can ensure higher revisit efficiency and coverage, and continuously provide SAR satellite image data for a long time, facilitating the subsequent time series cross-calibration experiments. For example, a user can use a computer device to select the Sentinel-1A satellite as the reference satellite and the Sentinel-1B satellite as the satellite to be calibrated. The user can then select distributed targets on the ESA official website that are repeatedly illuminated by both satellites and have a short imaging time interval, and ultimately select the Los Angeles urban area for subsequent experiments.

[0064] In one embodiment, a time series cross-calibration method for a synthetic aperture radar is provided, which may further include a process of performing regional screening to obtain a target area. The specific process includes: acquiring time series SAR data of a reference satellite based on position information, and preprocessing the time series SAR data to obtain a time series RCS value image corresponding to a distributed target; and performing regional screening within the spatial range of the distributed target based on the time series RCS value image to obtain a target area for time series cross-calibration.

[0065] The computer device can select a distributed target that is repeatedly illuminated by both satellites and has a short imaging time interval to increase the frequency of time series cross-calibration. In this embodiment, the computer device can obtain time-series SAR data of the reference satellite in different months within a year based on the location information of the distributed target, wherein the data set is required to have the same ascending and descending orbits, polarization modes and illumination areas and similar incident angles, and the imaging interval is no more than 60 days. Then, after pre-processing such as orbit correction, radiation calibration, coherent speckle filtering, and geocoding, the time-series RCS value image of the distributed target is obtained. Specifically, taking the Los Angeles urban area as an example of the selected target area, the time-series SAR data of the Sentinel-1A satellite in different months within a year is obtained based on the location information of the Los Angeles urban area. The data set has similar incident angles, the same ascending and descending orbits, polarization modes and illumination areas, and the imaging interval is no more than 60 days. The specific information is shown in the following table:

[0066]

[0067]

[0068] Then, the computer equipment can perform orbit correction, radiation calibration, coherent speckle filtering, geocoding and other pre-processing on this set of data to obtain a time-series RCS value image of the Los Angeles urban area.

[0069] In one embodiment, a time series cross-calibration method for a synthetic aperture radar is provided, which may also include a region screening process, the specific process including: performing initial screening of regions based on a time series RCS value image to obtain each preliminary screening region; cropping the time series RCS value slices according to the position information of each preliminary screening region; using a window median method to extract each time series backscatter coefficient corresponding to each time series RCS value slice, and calculating the average backscatter coefficient corresponding to the time series backscatter coefficient; and screening out the target region from each preliminary screening region according to the time series backscatter coefficient and the average backscatter coefficient through the root mean square error.

[0070] The computer equipment can perform a preliminary screening of the target area within the spatial range of the obtained distribution target. In order to reduce the generation of outliers in the subsequent calibration process, the area with uniform RCS value image brightness, no abnormal bright spots, a single-peak distribution of the image histogram, approximately symmetrical left and right, and a short-tail distribution is selected as the preliminary screening area. Then, according to the position information of each preliminary screening area, the time series RCS value slices are cut and produced respectively, and the time series backscatter coefficient is extracted using the window median method. The scattering stability of the preliminary screening area is judged by the root mean square error (RMSE). The calculation formula of the root mean square error can be expressed as: Among them, σ i and are the backscatter coefficient value of the target area time series RCS value slice and the average backscatter coefficient value of all slices, respectively, and N is the number of time series slices.

[0071] In this embodiment, a temporal root mean square error (RMSE) of less than 0.5 dB can be used as the screening criterion. If the RMSE of the initial screening area is less than 0.5 dB, it is determined to be a scattering stable region and used as the target region for subsequent time series cross-calibration. In this embodiment, a total of nine target regions were ultimately screened, with their specific locations shown in Figure 3(a) and their distribution histogram shown in Figure 3(b).

[0072] Step 204: Obtain imaging parameters of the reference satellite and the satellite to be calibrated, determine the time range for time series cross-calibration based on the imaging parameters and position information, crop data slices for time series cross-calibration based on the position information, and generate SAR image data pairs corresponding to the distributed targets at each moment within the time range.

[0073] Among them, the acquisition of SAR image data pairs is used to obtain data for time series cross-calibration. It is a set of cross-reference target data pairs in the time dimension. The data pairs at each moment include RCS value data slices of the reference star and DN value data slices of the star to be calibrated in multiple target areas, which can be used to obtain the radiation calibration coefficient at a single moment.

[0074] Specifically, the computer device can determine the time range for implementing time series calibration based on information such as the imaging time of the reference satellite and the satellite to be calibrated, the obtained target area location and imaging parameters. In this embodiment, taking the Los Angeles urban area as an example, the computer device can screen the Los Angeles urban area data provided by the Sentinel-1A satellite and the Sentinel-1B satellite on the official website of the European Space Agency, and select the Sentinel-1A satellite VV polarimetric image from August 21, 2019 to December 8, 2021 as the Sentinel-1B satellite VV polarimetric image from August 15, 2019 to December 2, 2021 for time series cross-calibration based on conditions such as the imaging time, imaging parameters, and target area location information.

[0075] In one embodiment, a time series cross-calibration method for a synthetic aperture radar is provided, which may further include a process of generating data pairs. The specific process includes: cropping reference satellite RCS value data slices and to-be-calibrated satellite DN value data slices of a target area based on location information; determining radiometric calibration requirements, and filtering SAR image data from the data slices within a time range according to the radiometric calibration requirements; and cropping the SAR image data separately to obtain SAR image data pairs corresponding to distributed targets.

[0076] Within a predetermined timeframe, the computer equipment can sequentially acquire SAR image data pairs of distributed targets from reference satellites and satellites to be calibrated. Each pair of data must have identical satellite orbits, polarization modes, and illumination areas, with similar incidence angles, and the imaging interval must not exceed 10 days. Specifically, operations performed on each reference satellite and calibrated satellite data pair at each moment include: preprocessing the reference and calibrated satellite data; cropping data slices for time series cross-calibration based on the location information of multiple selected target areas; and ultimately obtaining time series cross-reference target data pairs for time series cross-calibration. Each data pair represents a single moment and contains RCS value slices for the reference satellite and DN value slices for the calibrated satellite for multiple target areas.

[0077] Specifically, in this embodiment, based on the determined time range, the computer device can sequentially select SAR image data pairs that meet the radiometric cross-calibration requirements. The specific requirements are: each pair of data has similar incidence angles, the same satellite orbit, polarization mode, and illumination area, and the imaging interval does not exceed 10 days. Finally, a total of 69 pairs of images were screened within this time range, with some image data information shown in the following table:

[0078]

[0079]

[0080] Then, the computer equipment can operate on these 69 pairs of images one by one, including: pre-processing the reference satellite and the satellite to be calibrated data; cropping the data pairs according to the location information of the 9 target areas to obtain data slices for time series cross calibration; finally, 69 pairs of time series cross reference target data pairs are obtained, the composition diagram of which is shown in the figure below. Figure 4 Each data pair is for a single moment and contains data slices of the reference satellite and the satellite to be calibrated in 9 target areas.

[0081] Step 206 , using the window median method to extract the median matrix of the data slices at a single moment, obtaining a median matrix array, and performing robust regression fitting to remove outliers on the median matrix array, and outputting the radiation calibration coefficient at a single moment.

[0082] The computer device operates on the RCS value slice and DN value slice data pairs at a single moment to obtain the radiation calibration coefficient at a single moment to achieve SAR radiation calibration at a single moment.

[0083] In one embodiment, a time series cross-calibration method for a synthetic aperture radar is provided that may further include a process of obtaining a median matrix. The specific process includes: obtaining a set window size; extracting a median matrix from RCS value data slices and DN value data slices using a window median method according to the window size to obtain an RCS value median matrix and a DN value median matrix; and collecting the RCS value median matrix and the DN value median matrix at each single moment within a time range to obtain an RCS value median matrix array and a DN value median matrix array.

[0084] The computer equipment can use the data slices of multiple target areas at a single moment to perform radiometric calibration. First, set the window size to 50*50, and use the window median method to extract the median matrix of the 9 target area images of the reference satellite and the satellite to be calibrated in the data pair, a total of 18 data slices, including RCS value slices and DN value slices, using the equal interval median method. The schematic diagram is as follows: Figure 5 Finally, the median matrix array R of the RCS values ​​of multiple target areas at the time of calibration is obtained. m and DN value median matrix array D m Among them, the same index positions of the two median matrix arrays are the RCS value median matrix and the DN value median matrix of the same target area.

[0085] In one embodiment, a time series cross-calibration method for a synthetic aperture radar is provided that may further include a robust regression fitting process, specifically comprising: performing robust regression fitting using all data points in a DN value median matrix as independent variables and all data points in an RCS value median matrix array as dependent variables to obtain a fitting result; calculating a residual array of data points of the fitting result, and calculating a residual control interval based on the residual array; treating data points outside the residual control interval as outliers and removing them, and performing robust regression fitting again on the median matrix array after removing the outliers until all data points are within the residual control interval; and using the fitting result corresponding to all data points being within the residual control interval as the radiation calibration coefficient at a single moment.

[0086] The computer device can output the result R m and D m Perform robust regression fitting based on outlier removal. The specific steps include: m All data points are independent variables, R m All data points are used as dependent variables for robust regression fitting, and then the residual array of the data points, the upper control limit (UpperControlLimit, UCL) and the lower control limit (LowerControlLimit, LCL) of the fitting results are calculated. The calculation formula can be expressed as: UCL=μ R +2σ R ;LCL=μ R -2σ R ; Among them, R is the residual array of data points, y i is the fitted value of the i-th data point, is the actual value of the i-th data point, UCL and LCL are the upper and lower limits of the residual control, μ R is the residual mean, σ R In this embodiment, [UCL, LCL] is used as the residual control interval, and the data points outside the interval are eliminated and then robust regression fitting is performed again. It is repeated until all data points are within the residual control interval. The output fitting radiation calibration coefficient is K t .

[0087] Step 208: Determine a reference radiation calibration coefficient, and obtain a final reference value of the radiation calibration coefficient according to the reference radiation calibration coefficient and the radiation calibration coefficient.

[0088] The existing radiometric cross-calibration method only uses a single-time image during calibration, and does not consider the possible distortion of the ground object scattering characteristics in the image due to changes in external environmental factors such as weather, which leads to the uncertainty of the calibration results at a single time. Therefore, it is necessary to comprehensively refer to the radiometric calibration coefficients of the previous time and the calibration results at the time to be calibrated. Therefore, the radiometric calibration coefficient with the smallest calibration error within a fixed time range (36 days) before the time to be calibrated is selected as the reference radiometric calibration coefficient K. o , providing a reference for the time to be calibrated.

[0089] In one embodiment, a time series cross-calibration method for a synthetic aperture radar is provided that may further include a process of determining a reference value, specifically comprising: calculating a reference radiation calibration coefficient and an average of the radiation calibration coefficients, and using the average as a final reference value of the radiation calibration coefficient.

[0090] In this embodiment, if only the reference radiation calibration coefficient K o As a reference, the actual radiation performance changes at the current moment may be ignored, so the final reference value K of the radiation calibration coefficient is set r Set as reference radiation calibration factor K o and radiation calibration factor K t The mean of is calculated as:

[0091] In step 210, the radiation calibration coefficients corresponding to each single moment are calculated within the time range to generate a radiation calibration coefficient array; the radiation calibration coefficient array is error processed according to the final reference value of the radiation calibration coefficient to obtain the final radiation calibration coefficient, thereby completing the time series cross calibration.

[0092] Then, the 9 target areas can be calibrated separately to obtain the R m and D m Each corresponding index position is the RCS value slice and DN value slice of the same target area, so a robust regression fitting based on outlier removal is performed on each index position, and finally the radiation calibration coefficient array K of each area is obtained. v , which contains the radiation cross calibration results of 9 target areas. The formula can be expressed as: K v =[K1,K2,K3···K n ]; among them, K i is the radiation calibration coefficient of the i-th region; due to the different quality of the target area, the calibration results of each area are not completely accurate, so K o and K t As a benchmark, in K v The same number of elements with the smallest errors between the two are selected as the radiation calibration coefficient array K for the final weighted summation.

[0093] In one embodiment, a time series cross-calibration method for a synthetic aperture radar is provided that may further include an error processing process, specifically comprising: respectively calculating the difference between each radiation calibration coefficient in the radiation calibration coefficient array and a reference radiation calibration coefficient; and selecting a number of target radiation calibration coefficients based on the difference values, performing weighted summation calculation, and obtaining a final radiation calibration coefficient.

[0094] Among them, K v Although the array contains the radiation cross calibration results of 9 target areas, the quality of the target areas is different, so not every area’s calibration result is accurate. Therefore, 3 areas with K o The elements with the smallest error, 3 and K t The element with the smallest error is used as the final radiation calibration coefficient array K for weighted summation. Calculate the difference between each element in K and K r The error is given, and the elements in K are weighted one by one according to the size of the error. If the error is large, the weight is low, and if the error is small, the weight is high. The final radiation calibration coefficient K at that moment is obtained by weighted summation. f .

[0095] Specifically, the computer device can calculate the correlation between each element in the radiation calibration coefficient array K and the radiation calibration coefficient reference value K r The error is weighted according to the size of the error. The elements in K are weighted one by one. The elements with large errors are given low weights, and the elements with small errors are given high weights. The weighted sum is used to obtain the final radiation calibration coefficient K at that moment. f , the specific calculation formula can be expressed as: E i =|K i -K r |; Among them, K i is the element in the i-th radiation calibration coefficient array K, E i K i With K r The absolute value of the error, W i is the normalized weight, and K i The final result K is obtained after weighted summation f .

[0096] In one embodiment, a time series cross-calibration method for a synthetic aperture radar is provided, which may also include a process of constructing an attenuation model. The specific process includes: obtaining a radiation calibration coefficient at each moment, and generating a SAR radiation cross-calibration coefficient time series curve based on the radiation calibration coefficient; and constructing a satellite sensor attenuation model based on the time series curve.

[0097] In this embodiment, the computer device can obtain the radiation calibration coefficient of each moment in the time dimension for each of the 69 pairs of time series calibration data obtained, and finally obtain the SAR radiation cross calibration coefficient time series curve and construct the satellite sensor attenuation model based on the curve. The schematic diagram of the SAR radiation cross calibration coefficient time series curve is shown in FIG. Figure 6 shown.

[0098] In one embodiment, Figure 7 As shown in the figure, a time series cross-calibration method for synthetic aperture radar is provided, which mainly includes four parts: determining the target area range, obtaining time series calibration data pairs, obtaining single-time radiation calibration coefficients, and SAR time series cross-calibration. Among them:

[0099] Determination of target area scope: The target area for subsequent time series cross calibration is screened based on the statistical characteristics of the SAR image histogram distribution and the time series scattering stability of the target area;

[0100] Time series calibration data pair acquisition: mainly realizes the production of time series cross-reference target data pairs for time series cross-calibration, and performs SAR satellite time series data acquisition, preprocessing and slice cutting;

[0101] Acquisition of radiation calibration coefficient at a single moment: This mainly involves radiation cross-calibration of slices using cross-reference target data at a single moment obtained during the acquisition of time series calibration data. First, the median method is used to extract stable pixel points in all target areas. Then, all stable pixel points are used to perform robust regression fitting based on outlier removal to obtain the initial radiation calibration coefficient at the current moment. The radiation calibration coefficient reference value is determined by combining the radiation calibration coefficient values ​​at the current moment and the previous moment. Robust regression fitting based on outlier removal is then performed on each region to obtain the radiation calibration coefficient value for a single region. The radiation calibration coefficient value for each region is weighted one by one by calculating the error between the radiation calibration coefficient value and the radiation calibration coefficient reference value. Finally, the weighted sum of the radiation calibration coefficient values ​​for each region is taken to obtain the final radiation calibration coefficient for that moment.

[0102] SAR time series cross calibration: It mainly completes the iteration of step S3 in the time dimension, uses the time series cross-reference target data obtained in step S2 to slice, and obtains the radiation calibration coefficient of S3 in the time dimension. Finally, the SAR radiation calibration coefficient time series curve can be obtained and the satellite sensor attenuation model can be constructed based on this curve.

[0103] In this embodiment, a computer device first selects target regions for time series cross-calibration based on the statistical characteristics of the distributed target image histogram and time series scattering stability. After preprocessing and slicing, it obtains time series cross-calibration data pairs. Next, it obtains the radiometric calibration coefficients for a single moment. To address the issues of outlier interference and uncertainty in the calibration results for a single moment, as extracted by existing solutions, the following approach is adopted: A robust regression fit based on outlier removal is performed on all pixels to obtain the initial radiometric calibration coefficient for the current moment. This value is then combined with the radiometric calibration coefficient values ​​from the previous moment to determine a reference radiometric calibration coefficient value. A robust regression fit based on outlier removal is then performed on each region to obtain a single-region radiometric calibration coefficient value. The error between each region's radiometric calibration coefficient value and the reference radiometric calibration coefficient value is calculated and weighted accordingly. The weighted summation is then performed to obtain the final radiometric calibration coefficient for that moment. Next, the radiometric calibration coefficients are obtained moment by moment according to the above approach, ultimately generating a time series curve of the SAR radiometric calibration coefficients, which is then used to construct a satellite sensor attenuation model. The main implementation object of this application is the spaceborne synthetic aperture radar image to be calibrated, and the main work is to perform time series cross-calibration on it.

[0104] In this embodiment, after the existing radiometric cross-calibration method uses the median method or the mean method to complete the extraction of scattering stable pixels, the ordinary least squares method is immediately used to establish a calibration model to obtain the radiometric calibration coefficient of the satellite to be calibrated. The problem of outlier interference in the scattering stable pixels is not considered. A robust regression method based on outlier elimination is proposed for fitting the radiometric calibration coefficient. In the existing method, the calibration at each time point only uses a single-time image. However, the scattering characteristics of the ground objects in the single-time image may have errors, resulting in uncertainty in the calibration result at a single time. The correlation of the radiometric calibration coefficients between different times is used as a reference. The radiometric calibration coefficient value measured at the time to be calibrated and the radiometric calibration coefficient value at the previous time are combined to determine the final reference value of the radiometric calibration coefficient, and then the final radiometric calibration coefficient is obtained by weighting and weighted summation.

[0105] A time series cross-calibration method for a synthetic aperture radar is provided in the present application. To address the problem of outlier interference in the distributed target scattering stable pixel points extracted by the existing technical solution, a robust regression method based on outlier elimination is used to fit the radiation calibration coefficient. To address the problem of uncertainty in the calibration results at a single moment in the existing technical solution, the present application uses the correlation of the radiation calibration coefficients between different moments as a reference, combines the radiation calibration coefficient value measured at the time to be calibrated and the radiation calibration coefficient value at the previous moment, determines the final reference value of the radiation calibration coefficient, and then obtains the final radiation calibration coefficient through weighting and weighted summation.

[0106] It should be understood that, although the various steps in the above-mentioned flowcharts are shown in sequence according to the instructions of the arrows, these steps are not necessarily performed in sequence in the order indicated by the arrows. Unless otherwise specified herein, there is no strict order restriction on the execution of these steps, and these steps can be performed in other orders. Moreover, at least a portion of the steps in the above-mentioned flowcharts may include multiple sub-steps or multiple stages, and these sub-steps or stages are not necessarily performed at the same time, but can be performed at different times, and the execution order of these sub-steps or stages is not necessarily performed in sequence, but can be performed in turn or alternately with at least a portion of other steps or sub-steps or stages of other steps.

[0107] In one embodiment, Figure 8 As shown, a time series cross-calibration system for a synthetic aperture radar is provided, comprising: an area screening module 810, a data pair acquisition module 820, a single moment radiation calibration coefficient acquisition module 830, a calibration coefficient adjustment module 840, and a cross-calibration module 850, wherein:

[0108] The region screening module 810 is configured to determine reference satellites and satellites to be calibrated, determine distribution targets based on the reference satellites and the satellites to be calibrated, obtain location information of the distribution targets, and perform region screening within the spatial range of the distribution targets based on the location information to obtain a target region for time series cross calibration.

[0109] The data pair acquisition module 820 is used to obtain the imaging parameters of the reference satellite and the satellite to be calibrated, determine the time range for time series cross calibration based on the imaging parameters and position information, crop the data slices used for time series cross calibration based on the position information, and generate SAR image data pairs corresponding to the distributed targets at each moment within the time range;

[0110] The single moment radiation calibration coefficient acquisition module 830 is used to extract the median matrix of the single moment data slices using the window median method to obtain a median matrix array, and perform robust regression fitting on the median matrix array to eliminate outliers, and output the single moment radiation calibration coefficient;

[0111] The calibration coefficient adjustment module 840 is used to determine the reference radiation calibration coefficient and obtain the final reference value of the radiation calibration coefficient according to the reference radiation calibration coefficient and the radiation calibration coefficient;

[0112] The cross-calibration module 850 is used to calculate the radiation calibration coefficient corresponding to each single moment within the time range and generate a radiation calibration coefficient array; perform error processing on the radiation calibration coefficient array according to the final reference value of the radiation calibration coefficient to obtain the final radiation calibration coefficient, thereby completing the time series cross-calibration.

[0113] In one embodiment, the area screening module 810 is also used to obtain time-series SAR data of a reference satellite based on the position information, and pre-process the time-series SAR data to obtain a time-series RCS value image corresponding to the distribution target; based on the time-series RCS value image, area screening is performed within the spatial range of the distribution target to obtain a target area for time series cross-calibration.

[0114] In one embodiment, the region screening module 810 is also used to perform initial screening of regions based on the time series RCS value image to obtain various preliminary screening regions; according to the position information of each preliminary screening region, the time series RCS value slices are cropped respectively; the time series backscatter coefficients corresponding to each time series RCS value slice are extracted respectively using the window median method, and the average backscatter coefficient corresponding to the time series backscatter coefficient is calculated; the target region is screened out from each preliminary screening region according to the time series backscatter coefficient and the average backscatter coefficient through the root mean square error.

[0115] In one embodiment, the data pair acquisition module 820 is further used to crop reference satellite RCS value data slices and to-be-calibrated satellite DN value data slices of the target area based on the location information; determine the radiation calibration requirements, and filter out SAR image data from the data slices within a time range according to the radiation calibration requirements; and perform data cropping on the SAR image data to obtain SAR image data pairs corresponding to the distributed targets.

[0116] In one embodiment, the single-moment radiation calibration coefficient acquisition module 830 is also used to obtain a set window size; according to the window size, the window median method is used to extract the median matrix of the RCS value data slices and the DN value data slices to obtain the RCS value median matrix and the DN value median matrix; the RCS value median matrix and the DN value median matrix of each single moment in the collection time range are collected to obtain the RCS value median matrix array and the DN value median matrix array.

[0117] In one embodiment, the single-moment radiation calibration coefficient acquisition module 830 is also used to perform robust regression fitting with all data points in the DN value median matrix as independent variables and all data points in the RCS value median matrix array as dependent variables to obtain a fitting result; calculate the data point residual array of the fitting result, and calculate the residual control interval based on the residual array; treat the data points outside the residual control interval as outliers and eliminate them, and perform robust regression fitting again on the median matrix array after eliminating the outliers until all data points are within the residual control interval; and use the fitting result corresponding to all data points being within the residual control interval as the radiation calibration coefficient for a single moment.

[0118] In one embodiment, the calibration coefficient adjustment module 840 is further configured to calculate the reference radiation calibration coefficient and the average of the radiation calibration coefficients, and use the average as the final reference value of the radiation calibration coefficient.

[0119] In one embodiment, the calibration coefficient adjustment module 840 is further used to respectively calculate the difference between each radiation calibration coefficient in the radiation calibration coefficient array and the reference radiation calibration coefficient; based on the difference value, several target radiation calibration coefficients are selected for weighted summation calculation to obtain the final radiation calibration coefficient.

[0120] In one embodiment, the cross calibration module 850 is further configured to obtain a radiation calibration coefficient at each moment, and generate a SAR radiation cross calibration coefficient time series curve based on the radiation calibration coefficient; and construct a satellite sensor attenuation model based on the time series curve.

[0121] In one embodiment, a computer device is provided. The computer device may be a terminal, and its internal structure diagram may be as follows: Figure 9 As shown. The computer device includes a processor, memory, network interface, display screen, and input device connected via a system bus. The processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of the operating system and computer program in the non-volatile storage medium. The network interface of the computer device is used to communicate with an external terminal via a network connection. When the computer program is executed by the processor, a time series cross-calibration method for a synthetic aperture radar is implemented. The display screen of the computer device can be a liquid crystal display or an electronic ink display screen. The input device of the computer device can be a touch layer covering the display screen, or a key, trackball, or touchpad provided on the computer device housing, or an external keyboard, touchpad, or mouse.

[0122] Those skilled in the art will understand that Figure 9 The structure shown in the figure is only a block diagram of a part of the structure related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computer device may include more or fewer components than shown in the figure, or combine certain components, or have a different component arrangement.

[0123] In one embodiment, a computer device is provided, including a memory and a processor. The memory stores a computer program, and the processor implements the steps of a time series cross-calibration method for a synthetic aperture radar when executing the computer program.

[0124] In one embodiment, a computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed by a processor, the computer program implements the steps of a time series cross-calibration method for a synthetic aperture radar.

[0125] Those skilled in the art will appreciate that all or part of the processes in the above-mentioned embodiments can be implemented by instructing the relevant hardware through a computer program. The computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to memory, storage, database or other media used in the embodiments provided in this application can include non-volatile and / or volatile memory. Non-volatile memory can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM) or flash memory. Volatile memory can include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in various forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link (Synchlink) DRAM (SLDRAM), memory bus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM).

[0126] The technical features of the above embodiments can be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0127] The above-described embodiments merely represent several implementation methods of the present application. While the descriptions are relatively specific and detailed, they should not be construed as limiting the scope of the present invention. It should be noted that a person skilled in the art could make various modifications and improvements without departing from the spirit of the present application, all of which fall within the scope of protection of the present application. Therefore, the scope of protection of the present patent application shall be determined by the appended claims.

Claims

1. A time series cross calibration method for synthetic aperture radar, characterized in that: The method comprises: Determining a reference satellite and a satellite to be calibrated, determining a distribution target based on the reference satellite and the satellite to be calibrated, obtaining position information of the distribution target, and performing regional screening within the spatial range of the distribution target based on the position information to obtain a target area for time series cross calibration; Acquiring imaging parameters of the reference satellite and the satellite to be calibrated, determining a time range for time series cross calibration based on the imaging parameters and position information, cropping data slices for time series cross calibration based on the position information, and generating SAR image data pairs corresponding to the distributed targets at each moment within the time range; The median matrix of the data slices at a single moment is extracted respectively by using the window median method to obtain a median matrix array, and the median matrix array is subjected to robust regression fitting with outliers removed to output the radiation calibration coefficient at the single moment; Determining a reference radiation calibration coefficient, and obtaining a final reference value of the radiation calibration coefficient according to the reference radiation calibration coefficient and the radiation calibration coefficient; Within the time range, the radiation calibration coefficient corresponding to each single moment is calculated respectively to generate a radiation calibration coefficient array; the radiation calibration coefficient array is error processed according to the final reference value of the radiation calibration coefficient to obtain the final radiation calibration coefficient, thereby completing the time series cross calibration.

2. The time series cross calibration method for synthetic aperture radar according to claim 1, characterized in that: Acquiring location information of the distribution target, and performing regional screening within the spatial range of the distribution target according to the location information to obtain a target area for time series cross-calibration, including: Acquiring time-series SAR data of the reference satellite according to the position information, and preprocessing the time-series SAR data to obtain a time-series RCS value image corresponding to the distributed target; Based on the time series RCS value image, regional screening is performed within the spatial range of the distribution target to obtain a target area for time series cross calibration.

3. The time series cross calibration method for synthetic aperture radar according to claim 2, characterized in that: Performing regional screening within the spatial range of the distribution target based on the time series RCS value image includes: Performing a primary screening of regions based on the time-series RCS value image to obtain each primary screening region; According to the position information of each of the primary screening areas, the time series RCS value slices are cut respectively; Extracting each time series backscatter coefficient corresponding to each time series RCS value slice using a window median method, and calculating an average backscatter coefficient corresponding to the time series backscatter coefficient; The target area is screened out from each of the primary screening areas according to the time series backscatter coefficient and the average backscatter coefficient through the root mean square error.

4. The time series cross calibration method for synthetic aperture radar according to claim 1, characterized in that: The method includes: cutting data slices for time series cross-calibration based on the position information, and generating SAR image data pairs corresponding to the distribution targets at each moment within the time range, including: Cut out reference satellite RCS value data slices and to-be-calibrated satellite DN value data slices of the target area based on the position information; determining a radiation calibration requirement, and filtering out SAR image data from the data slices within the time range according to the radiation calibration requirement; Data cropping is performed on the SAR image data to obtain SAR image data pairs corresponding to the distribution targets.

5. The time series cross calibration method for synthetic aperture radar according to claim 4, characterized in that: The median matrix of the data slices at a single moment is extracted respectively using the window median method to obtain a median matrix array, including: Get the set window size; According to the window size, a median matrix is ​​extracted from the RCS value data slice and the DN value data slice using a window median method to obtain an RCS value median matrix and a DN value median matrix; The RCS value median matrix and the DN value median matrix at each single moment in the time range are collected to obtain an RCS value median matrix array and a DN value median matrix array.

6. The time series cross calibration method for synthetic aperture radar according to claim 5, characterized in that: Performing a robust regression fitting with outlier removal on the median matrix array and outputting the radiation calibration coefficient at the single moment includes: Perform robust regression fitting using all data points in the DN value median matrix as independent variables and all data points in the RCS value median matrix array as dependent variables to obtain fitting results; Calculating a residual array of the data points of the fitting result, and calculating a residual control interval based on the residual array; Data points outside the residual control interval are treated as outliers and removed, and the median matrix array after removing the outliers is subjected to robust regression fitting again until all data points are within the residual control interval; The fitting result corresponding to all data points being within the residual control interval is used as the radiation calibration coefficient at the single moment.

7. The time series cross calibration method for synthetic aperture radar according to claim 1, characterized in that: Obtaining a final reference value of the radiation calibration coefficient according to the reference radiation calibration coefficient and the radiation calibration coefficient includes: Calculate the reference radiation calibration coefficient and the average of the radiation calibration coefficients, and use the average as a final reference value of the radiation calibration coefficient.

8. The time series cross calibration method for synthetic aperture radar according to claim 1, characterized in that: Performing error processing on the radiation calibration coefficient array according to the final reference value of the radiation calibration coefficient to obtain the final radiation calibration coefficient, including: Calculating the difference between each radiation calibration coefficient in the radiation calibration coefficient array and the reference radiation calibration coefficient respectively; Based on the gap value, several target radiation calibration coefficients are selected and weighted summed to obtain a final radiation calibration coefficient.

9. The time series cross calibration method for synthetic aperture radar according to claim 1, characterized in that: The method further comprises: Obtaining the radiation calibration coefficient at each moment, and generating a SAR radiation cross calibration coefficient time series curve according to the radiation calibration coefficient; A satellite sensor attenuation model is constructed according to the timing curve.

10. A time series cross-calibration system for synthetic aperture radar, characterized in that: The system comprises: an area screening module, configured to determine a reference satellite and a satellite to be calibrated, determine a distribution target based on the reference satellite and the satellite to be calibrated, obtain position information of the distribution target, and perform area screening within the spatial range of the distribution target based on the position information to obtain a target area for time series cross calibration; a data pair acquisition module, configured to acquire imaging parameters of the reference satellite and the satellite to be calibrated, determine a time range for time series cross calibration based on the imaging parameters and position information, crop data slices for time series cross calibration based on the position information, and generate SAR image data pairs corresponding to the distributed targets at each moment within the time range; A single moment radiation calibration coefficient acquisition module is used to extract the median matrix of the data slice at a single moment using the window median method to obtain a median matrix array, and perform robust regression fitting on the median matrix array to eliminate outliers, and output the radiation calibration coefficient at the single moment; A calibration coefficient adjustment module is used to determine a reference radiation calibration coefficient, and obtain a final reference value of the radiation calibration coefficient according to the reference radiation calibration coefficient and the radiation calibration coefficient; The cross calibration module is used to calculate the radiation calibration coefficient corresponding to each single moment within the time range and generate a radiation calibration coefficient array; perform error processing on the radiation calibration coefficient array according to the final reference value of the radiation calibration coefficient to obtain the final radiation calibration coefficient, thereby completing the time series cross calibration.

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