Synthetic aperture radar altimeter imaging processing method, system, and storage medium

Abstract

The application relates to the technical field of synthetic aperture radar altimeter, and discloses a synthetic aperture radar altimeter imaging processing method, a system and a storage medium, which comprises the following steps: obtaining a plurality of total delay correction data of each target imaging point according to initial data of a synthetic aperture radar altimeter in imaging processing, and determining a plurality of distance compression data of each target imaging point; obtaining a target MASK graph of each target imaging point based on the plurality of total delay correction data of each target imaging point, and obtaining a target waveform graph of each target imaging point based on the target MASK graph of each target imaging point and the plurality of distance compression data, and generating target data of the synthetic aperture radar altimeter in imaging processing according to the waveform graph. The application improves the quality of multi-view waveforms without increasing the operation amount, can realize high-precision imaging processing of the synthetic aperture radar altimeter, and obtains high-quality L1B data in the imaging processing of the synthetic aperture radar altimeter.

Description

Technical Field

[0001] This invention relates to the field of synthetic aperture radar altimeter technology, and in particular to a synthetic aperture radar altimeter imaging processing method, system, and storage medium. Background Technology

[0002] Synthetic Aperture Radar (SAR) altimeters incorporate synthetic aperture technology compared to traditional radar altimeters, making their data processing methods more complex. The SAR data processing workflow (L1A to L1B product production) generally includes the following steps: 1) Ground imaging point calculation; 2) Track-in-the-loop beam sharpening; 3) Stacking generation; 4) Delay correction; 5) Range compression.

[0003] 6) Masking; 7) Multi-view waveform generation.

[0004] In step 1, the imaging point position of the traditional Synthetic Aperture Radar Altimeter (SARAltimeter) is calculated by extrapolation, resulting in low accuracy. Furthermore, while the accuracy of the processed result obtained in step 2 using the precise processing method of SARAltimeter combined with Stacking is sufficient, precise processing of the radar altimeter is time-consuming. Generally, considering processing efficiency, step 2 usually adopts the traditional SARAltimeter approximation method. However, due to the accumulation of errors in step 2, the approximation error of the traditional SARAltimeter in Stacking generation cannot be ignored, affecting the accuracy of burst energy extraction and leading to certain errors in burst extraction (extraction unit deviation). Therefore, the rapid production of L1B products using the traditional SARAltimeter suffers from unsatisfactory accuracy.

[0005] Therefore, there is an urgent need to provide a technical solution to address the above problems. Summary of the Invention

[0006] To address the issue of low accuracy in L1B rapidly produced products in traditional SAR Altimeter imaging, this invention provides a synthetic aperture radar altimeter imaging processing method, system, and storage medium.

[0007] In a first aspect, the present invention provides a synthetic aperture radar altimeter imaging processing method, the technical solution of which is as follows:

[0008] Based on the initial data from the synthetic aperture radar altimeter in the imaging process, multiple range compression data for each target imaging point are obtained and determined based on multiple total delay correction data for each target imaging point.

[0009] Based on multiple total delay correction data for each target imaging point, a target mask map for each target imaging point is obtained. Based on the target mask map for each target imaging point and multiple range compression data, a target waveform map for each target imaging point is obtained.

[0010] Based on the target waveform diagram of each target imaging point, the target data of the synthetic aperture radar altimeter in the imaging process is generated.

[0011] The beneficial effects of the synthetic aperture radar altimeter imaging processing method of the present invention are as follows:

[0012] The method of the present invention improves the quality of multi-view waveforms without increasing the amount of computation, and can realize high-precision imaging processing of synthetic aperture radar altimeter, thereby obtaining high-quality L1B data in synthetic aperture radar altimeter imaging processing.

[0013] Based on the above scheme, the synthetic aperture radar altimeter imaging processing method of the present invention can be further improved as follows.

[0014] In one alternative approach, the initial data includes: first auxiliary data and multiple first burst data; the step of obtaining multiple total delay correction data for each target imaging point based on the initial data from the synthetic aperture radar altimeter in the imaging process includes:

[0015] The first auxiliary data is subjected to linear interpolation to obtain the second auxiliary data, and multiple target imaging points are determined from the second auxiliary data;

[0016] Doppler center correction and Doppler sharpening are performed sequentially on each first burst data to obtain multiple second burst data. The azimuth frequency energy position of each target burst data corresponding to each target imaging point is determined from all the second burst data.

[0017] Based on the total delay correction of the frequency energy position corresponding to each target imaging point, the delay correction phase corresponding to each target imaging point is obtained. Then, the delay correction phase of each target imaging point is multiplied by the corresponding second burst data to obtain multiple total delay correction data for each target imaging point.

[0018] In one alternative approach, the step of determining multiple range-direction compressed data for each target imaging point based on multiple total delay correction data for each target imaging point includes:

[0019] Perform a range-direction fast Fourier transform on each total delay correction data of any target imaging point to obtain multiple range-direction compressed data of the target imaging point, until multiple range-direction compressed data of each target imaging point are obtained.

[0020] In one alternative approach, the step of obtaining the target mask map for each target imaging point based on multiple total delay correction data for each target imaging point includes:

[0021] Each total delay correction corresponding to any target imaging point is calculated with the minimum total delay correction corresponding to that target imaging point to generate a first MASK image of that target imaging point. Then, based on the loss location of each missing second burst data corresponding to that target imaging point, a second MASK image of that target imaging point is generated. Finally, the first MASK image and the second MASK image of that target imaging point are multiplied to obtain the target MASK image of that target imaging point. This process is repeated until the target MASK image of each target imaging point is obtained.

[0022] In one alternative approach, the step of obtaining the target waveform map for each target imaging point based on the target MASK map for each target imaging point and multiple range-compressed data includes:

[0023] Based on the target MASK map of any target imaging point and the matrix corresponding to multiple range-direction compressed data, a first waveform map containing multiple waveforms corresponding to the target imaging point is obtained. The multiple waveforms in the first waveform map of the target imaging point are then subjected to modulus and squaring processing, and all processed waveforms are accumulated to obtain the target waveform map of the target imaging point, until the target waveform map of each target imaging point is obtained.

[0024] In one alternative approach, the step of generating target data of the synthetic aperture radar altimeter in imaging processing based on the target waveform map of each target imaging point includes:

[0025] Based on the second auxiliary data and the target waveform diagram of each target imaging point, the target data of the synthetic aperture radar altimeter in the imaging process is generated.

[0026] Secondly, the present invention provides a synthetic aperture radar altimeter imaging processing system, the technical solution of which is as follows:

[0027] It includes: a first processing module, a second processing module, and a third processing module;

[0028] The first processing module is used to: obtain and determine multiple range compression data for each target imaging point based on the initial data of the synthetic aperture radar altimeter in the imaging process;

[0029] The second processing module is used to: obtain a target MASK image for each target imaging point based on multiple total delay correction data for each target imaging point, and obtain a target waveform image for each target imaging point based on the target MASK image for each target imaging point and multiple range compression data;

[0030] The third processing module is used to generate target data of the synthetic aperture radar altimeter in imaging processing based on the target waveform diagram of each target imaging point.

[0031] The beneficial effects of the synthetic aperture radar altimeter imaging processing system of the present invention are as follows:

[0032] The system of the present invention improves the quality of multi-view waveforms without increasing the amount of computation, and can realize high-precision imaging processing of synthetic aperture radar altimeter, thereby obtaining high-quality L1B data in synthetic aperture radar altimeter imaging processing.

[0033] Based on the above scheme, the synthetic aperture radar altimeter imaging processing system of the present invention can be further improved as follows.

[0034] In one alternative approach, the initial data includes: first auxiliary data and multiple first burst data; the first processing module is specifically used for:

[0035] The first auxiliary data is subjected to linear interpolation to obtain the second auxiliary data, and multiple target imaging points are determined from the second auxiliary data;

[0036] Doppler center correction and Doppler sharpening are performed sequentially on each first burst data to obtain multiple second burst data. The azimuth frequency energy position of each target burst data corresponding to each target imaging point is determined from all the second burst data.

[0037] Based on the total delay correction of the frequency energy position corresponding to each target imaging point, the delay correction phase corresponding to each target imaging point is obtained. Then, the delay correction phase of each target imaging point is multiplied by the corresponding second burst data to obtain multiple total delay correction data for each target imaging point.

[0038] In an alternative embodiment, the first processing module is further configured to:

[0039] Perform a range-direction fast Fourier transform on each total delay correction data of any target imaging point to obtain multiple range-direction compressed data of the target imaging point, until multiple range-direction compressed data of each target imaging point are obtained.

[0040] Thirdly, the technical solution for a storage medium provided by the present invention is as follows:

[0041] The storage medium stores instructions that, when read by a computer, cause the computer to execute the steps of a synthetic aperture radar altimeter imaging processing method according to the present invention.

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

[0043] The accompanying drawings are for illustrative purposes only and are not intended to limit the invention. Furthermore, the same reference numerals denote the same parts throughout the drawings. In the drawings:

[0044] Figure 1 A schematic flowchart of an embodiment of a synthetic aperture radar altimeter imaging processing method provided by the present invention is shown;

[0045] Figure 2 This illustration shows a schematic diagram of the calculation principle of the target imaging point in an embodiment of a synthetic aperture radar altimeter imaging processing method provided by the present invention;

[0046] Figure 3 The diagram shows the burst migration curve after Doppler sharpening in an embodiment of a synthetic aperture radar altimeter imaging processing method provided by the present invention.

[0047] Figure 4 This illustration shows a schematic diagram of the search for target burst data corresponding to the target imaging point in an embodiment of a synthetic aperture radar altimeter imaging processing method provided by the present invention.

[0048] Figure 5 The diagram illustrates the MASK image generation principle in an embodiment of a synthetic aperture radar altimeter imaging processing method provided by the present invention.

[0049] Figure 6 A comparative schematic diagram of two-dimensional target waveform results in an embodiment of a synthetic aperture radar altimeter imaging processing method provided by the present invention is shown.

[0050] Figure 7 A comparative schematic diagram of target waveform results is shown in an embodiment of a synthetic aperture radar altimeter imaging processing method provided by the present invention;

[0051] Figure 8A schematic diagram of an embodiment of a synthetic aperture radar altimeter imaging processing system provided by the present invention is shown. Detailed Implementation

[0052] Exemplary embodiments of the invention will now be described in more detail with reference to the accompanying drawings. While exemplary embodiments of the invention are shown in the drawings, it should be understood that the invention can be implemented in various forms and should not be limited to the embodiments set forth herein.

[0053] Figure 1 A schematic flowchart of an embodiment of a synthetic aperture radar altimeter imaging processing method provided by the present invention is shown. Figure 1 As shown, it includes the following steps:

[0054] Step 110: Based on the initial data from the synthetic aperture radar altimeter in the imaging process, obtain and determine multiple range-oriented compressed data for each target imaging point based on multiple total delay correction data for each target imaging point. Wherein:

[0055] ① A synthetic aperture radar altimeter is a radar altimeter that combines traditional radar altimeter technology with aperture synthesis technology. It was first proposed by the Johns Hopkins University Applied Physics Laboratory and initially named the "Delay Doppler Radar Altimeter." The concept of a synthetic aperture radar altimeter is to introduce aperture synthesis technology along the orbital direction into a traditional bottom-view satellite-borne radar altimeter to improve echo utilization efficiency, increase spatial resolution along the orbital direction, and improve measurement accuracy.

[0056] ②The initial data is: L1A data (product), which includes all Ku-band burst echoes (multiple first burst data) and auxiliary data (first auxiliary data) for geographic calibration; L1A data is usually stored in nc files.

[0057] ③The target imaging point is: the ground imaging point.

[0058] ④ One target imaging point corresponds to multiple total delay correction data points, and one target imaging point corresponds to multiple range compression data points. The number of total delay correction data points and range compression data points are the same and correspond one-to-one.

[0059] It should be noted that introducing synthetic aperture technology into traditional radar altimeters can reduce the peak power of the transmitted signal by 10 dB, decrease the resolvable footprint along the flight path from 2 km to 300 m, and improve the altimeter accuracy to 1 cm (4 m significant wave height). These features are significant for improving the ability of traditional altimeters to measure mesoscale ocean phenomena, as well as their ability to measure coastal zones and sea ice. Furthermore, synthetic aperture altimeters can achieve 1 urad sea surface slope measurement, which is particularly important for measuring seabed topography.

[0060] Step 120: Based on multiple total delay correction data for each target imaging point, obtain the target mask map for each target imaging point. Then, based on the target mask map for each target imaging point and multiple range compression data, obtain the target waveform map for each target imaging point. Wherein:

[0061] ① Multiple total delay correction data correspond to one target MASK map.

[0062] ② Multiple distance-oriented compressed data and one target mask map correspond to one target waveform map.

[0063] Step 130: Based on the target waveform diagram of each target imaging point, generate the target data of the synthetic aperture radar altimeter in the imaging processing. Wherein:

[0064] The target data is L1B data (product), which includes the waveform (target waveform) after geographic calibration and multi-view processing, as well as auxiliary data (secondary auxiliary data); L1B data is also stored in nc files.

[0065] Preferably, step 110 includes:

[0066] Step 110: Perform linear interpolation on the first auxiliary data to obtain second auxiliary data, and determine multiple target imaging points from the second auxiliary data. Wherein:

[0067] ① The first auxiliary data includes: multiple first satellite nadir coordinates, multiple first satellite coordinates, and multiple first satellite velocities. The number of first satellite nadir coordinates, first satellite coordinates, and first satellite velocities are the same (n) and correspond one-to-one.

[0068] ②For example Figure 2 As shown, the linear interpolation process is as follows: the coordinates of the first nadir point, the coordinates of the first satellite, and the velocity of the first satellite are interpolated by multiple times (e.g., 10 times interpolation) to obtain more dense nadir point coordinates (second nadir point coordinates), satellite coordinates (second satellite coordinates), and satellite velocities (second satellite velocities).

[0069] ③ The second auxiliary data includes: multiple second satellite nadir coordinates, multiple second satellite coordinates, and multiple second satellite velocities. The number of second satellite nadir coordinates, second satellite coordinates, and second satellite velocities are the same (10^n) and correspond one-to-one.

[0070] ④ The process of determining multiple target imaging points from the second auxiliary data is as follows:

[0071] 1) Based on the first preset formula, and according to the coordinates of the first second satellite nadir and the velocity of the first second satellite, the first connecting angle is obtained, and the target imaging point is determined within the preset range corresponding to the coordinates of the first second satellite nadir.

[0072] The first preset formula is: λ is the wavelength, |V s_i | represents the magnitude of the velocity of the i-th second satellite, N a Where is the number of samples along the track direction for burst, PRF is the pulse repetition frequency, and α is the number of samples along the track direction. i Let be the included angle of the i-th connecting line.

[0073] The preset range is: (N) jump_i / 2,3N jump_i / 2), Δx i =α i ·alt i alt i Let ΔS be the satellite orbital altitude corresponding to the i-th second satellite coordinate. intp This represents the distance between the coordinates of the two second satellites.

[0074] 2) Take the target imaging point within the preset range corresponding to the first second satellite nadir coordinate as the first second satellite nadir coordinate, and return to execute the step of obtaining the first connecting angle based on the first preset formula and the first second satellite nadir coordinate and the first second satellite velocity, until each target imaging point in all interpolated satellite nadir coordinates is obtained.

[0075] It should be noted that, similarly for α i Sampling delay Δt i Linear interpolation is performed. First, the coordinates T1 of the first second satellite nadir point are set, and this second satellite nadir point coordinates are determined as the first target imaging point. Then, based on the T1 position, S1 position (the first second satellite coordinates), and velocity (the first second satellite velocity), subsequent images from N... jump_i / 2 to 3N jump_i / 2 interpolation results in the sub-star point ( Figure 2 Search within the circle to find the closest α iThe second nadir point of the angle is the next target imaging point T2. Store the target imaging point number and the corresponding second satellite coordinate number after interpolation. Find the second satellite coordinates and velocity at point S2. Then, use this method to find T3 and S3, and so on, until T is found. n S n Afterwards, they searched for T again. n+1 When the position of the sub-star is obtained beyond all interpolation values ​​( Figure 2 (The final dashed line indicates that all target imaging points have been found, thus completing the imaging point calculation and recursion.) Then, the vector between each target imaging point T and its corresponding target satellite S is calculated and stored.

[0076] Step 112: Perform Doppler center correction and Doppler sharpening sequentially on each first burst data to obtain multiple second burst data. Then, determine the azimuth frequency energy position of each target burst data corresponding to each target imaging point from all the second burst data. Wherein:

[0077] ① Doppler center correction, or FDC correction for short, is as follows: First, each first burst data point is treated as a two-dimensional matrix: the vertical orientation dimension N a Horizontal distance in dimension N r Secondly, based on the second preset formula, Doppler center correction is performed on each two-dimensional matrix of the first burst data to obtain the corrected burst data of the first burst data. The second preset formula is: S i (t a )=exp(-j2π·f dc_i ·t a ), S i (t a ) represents the i-th corrected burst data, V s_i W is the satellite velocity vector corresponding to the i-th first burst data. sat_surf_i Let t be the satellite beam pointing vector corresponding to the i-th first burst data. a The time axis is defined with intervals of 1 / PRF.

[0078] ② Doppler sharpening is converted into azimuth-directed Fast Fourier Transform (FFT). The specific process is as follows: perform azimuth-directed FFT on each corrected burst data to obtain the second burst data.

[0079] ③ For example Figure 3 As shown, the second burst data is the migration curve within the burst. Figure 3In the diagram, the vertical axis represents the azimuth frequency, and the horizontal axis represents the distance. After FDC correction, it can be seen that the closest slant distance (within the circle) is near the azimuth zero frequency, indicating that the FDC correction is correct.

[0080] Step 113: Based on the total delay correction for each azimuth frequency energy position corresponding to each target imaging point, obtain the delay correction phase corresponding to each target imaging point, and multiply the delay correction phase of each target imaging point by the corresponding second burst data to obtain multiple total delay correction data for each target imaging point. Wherein:

[0081] ① From all the second burst data, obtain a preset number of target burst data corresponding to each target imaging point, and obtain an azimuth frequency energy position corresponding to each target burst data. Specifically:

[0082] 1) For each target imaging point, search for its corresponding N according to the preset search method. sat The second burst data (denoted as the target burst data) is accumulated from the number of bursts.

[0083] 2) such as Figure 4 As shown, the preset search method specifically includes: First, for the i-th target imaging point T i Based on the target imaging point number and the second satellite coordinate number, the second burst data numbered k is roughly located. Then, a search is performed at m positions near k (e.g., m=8) to find the value of β. k The smallest second burst data number, β k Let N be the beam pointing vector at the target imaging point and the angle between the target imaging point and the burst azimuth vector. Take N values ​​to the left and right of the found index k as the center. sat / 2、N sat / 2-1 second burst data, denoted as the target burst data corresponding to the target imaging point.

[0084] 3) Based on the third preset formula, obtain the azimuth frequency energy position corresponding to each target burst data. The third preset formula is: j T_B =min_number[abs(f a -f dc_T_B +f dc_B )], f a It is the azimuth frequency axis, f dc_T_B f is the burst data of the B-th target corresponding to the T-th target imaging point. dc min_number refers to finding the f frequency composed of 64 frequencies. a The position number where the minimum value occurs on the axis, resulting in jT_B This refers to the azimuth frequency energy position of the burst data of the Bth target corresponding to the Tth target imaging point.

[0085] It should be noted that the calculation is performed in the above manner for each target imaging point, thus completing the Stacking generation. The Stacking generation result is an N-value generated for each target imaging point. sat Multiply by N r The matrix.

[0086] ② The step of obtaining the total delay correction for the frequency energy position of each azimuth corresponding to each target imaging point includes:

[0087] Based on the fourth preset formula, the total delay correction for the azimuth frequency energy position corresponding to each target imaging point is obtained; the fourth preset formula is: ΔR total_B_T =R S_T -R Doppler_B_T -R B_caiyang R B_T =|S B -T T |,R Doppler_B_T =-Kr sign ·f dc_T_B / 2·c·Tp / B, K=B / Tp. R B_T R is the slant range correction for the B-th azimuth frequency energy position corresponding to the T-th target imaging point. Doppler_B_T R is the Doppler correction value for the B-th azimuth frequency energy position corresponding to the T-th target imaging point. B_caiyang ΔR is the initial correction value for sampling the frequency energy position of the Bth azimuth. total_B_T For the total delay correction of the B-th azimuth frequency energy position corresponding to the T-th target imaging point, Kr sign For frequency modulation, c is the speed of light, Tp is the pulse width, and B is the bandwidth.

[0088] ③ The step of obtaining the delay correction phase corresponding to each target imaging point based on the total delay correction of each azimuth frequency energy position corresponding to each target imaging point includes:

[0089] Based on the fifth preset formula, and according to the total delay correction of the azimuth frequency energy position corresponding to each target imaging point, the delay correction phase of the azimuth frequency energy position corresponding to each target imaging point is obtained; the fifth preset formula is: M B_T (t a )=exp(j·2π·2K / c·ΔR total_B_T ·t r K = B / Tp is the range-directed modulation frequency, t r Starting with 0, 1 / f s The intervals are increasing, for a total of N.r A time vector composed of N data points, r This represents the number of sampling points along the distance.

[0090] ④ Multiply the multiple delay correction phases of any target imaging point with the second burst data corresponding to that target imaging point to obtain multiple total delay correction data for that target imaging point, until multiple total delay correction data for each target imaging point are obtained.

[0091] Preferably, the step of determining multiple range-direction compressed data for each target imaging point based on multiple total delay correction data for each target imaging point includes:

[0092] Perform a range-direction fast Fourier transform on each total delay correction data of any target imaging point to obtain multiple range-direction compressed data of the target imaging point, until multiple range-direction compressed data of each target imaging point are obtained.

[0093] Preferably, the step of obtaining the target mask map for each target imaging point based on multiple total delay correction data for each target imaging point includes:

[0094] Each total delay correction corresponding to any target imaging point is calculated with the minimum total delay correction corresponding to that target imaging point to generate a first mask image for that target imaging point. Then, based on the location of each missing second burst data point corresponding to that target imaging point, a second mask image for that target imaging point is generated. Finally, the first and second mask images for that target imaging point are multiplied to obtain the target mask image for that target imaging point. This process is repeated until the target mask image for each target imaging point is obtained. Wherein:

[0095] ① The steps of calculating each total delay correction corresponding to any target imaging point and the minimum total delay correction corresponding to that target imaging point to generate the first mask image of that target imaging point include:

[0096] Based on the sixth preset formula, each total delay correction corresponding to any target imaging point is calculated with its minimum total delay correction to generate the first MASK image corresponding to that target imaging point; the sixth preset formula is: ΔR total_T For a set of ΔR total_B_T The set of TN sat / 2≤B<T+N sat / 2(Total N) sat (values), Indicates to Taking the positive value downwards, the calculated Range_geo_bin TThis represents the number of zeros from back to front at each B (target burst data), i.e., based on Range_geo_bin. T Generate N sat ×N r The mask, namely the geometric correction mask image (the first mask image), is as follows: Figure 5 As shown in (a).

[0097] ② In the process of generating the second MASK map of the target imaging point based on the missing locations of each missing second burst data corresponding to the target imaging point:

[0098] 1) The second mask chart is the data interval mask, that is, for N sat ×N r The Mask is assigned a value.

[0099] 2) such as Figure 5 As shown in (b), for all the second burst data corresponding to the target imaging point, the range direction at the lost second burst data is set to zero, and the range direction at the unlost second burst data is set to 1.

[0100] ③ For example Figure 5 As shown in (c), the first MASK image and the second MASK image of the target imaging point are multiplied together to obtain the target MASK image of the target imaging point.

[0101] ④ For each target imaging point, the corresponding target mask image is obtained using the steps ①-③ above.

[0102] Preferably, the step of obtaining the target waveform map of each target imaging point based on the target MASK map of each target imaging point and multiple range-compressed data includes:

[0103] Based on the target mask map of any target imaging point and the matrix corresponding to multiple range-compressed data, a first waveform map containing multiple waveforms corresponding to that target imaging point is obtained. The multiple waveforms in the first waveform map of the target imaging point are then subjected to modulus and squaring processing. All processed waveforms are then incoherently accumulated to obtain the target waveform map of that target imaging point. This process continues until the target waveform map of each target imaging point is obtained. Wherein:

[0104] The target waveform diagram of the target imaging point contains the multi-view waveform of the target imaging point.

[0105] Preferably, step 130 includes:

[0106] Based on the second auxiliary data and the target waveform diagram of each target imaging point, the target data of the synthetic aperture radar altimeter in the imaging processing is generated. Wherein:

[0107] The second auxiliary data and the target waveform of each target imaging point are packaged together to form L1B data.

[0108] To better illustrate the technical solution of this embodiment, the following examples are used for explanation and verification, specifically:

[0109] The publicly released Sentinel-3A synthetic aperture radar altimeter satellite data measured at 15:00 on December 31, 2019, was used for verification. The algorithm used in this embodiment was compared with the Sentinel open-source Python processing algorithm to verify the processing effect of this embodiment. The main parameters of this embodiment (main parameters of Sentinel-3 closed-loop Ku-band SAR Altimeter) are shown in Table 1 below.

[0110] Table 1:

[0111]

[0112]

[0113] In this embodiment, the processing algorithm takes a Level 1A product nc file as input. The processing steps are as follows: Figure 1 As shown, to verify the effectiveness of the processing algorithm in this embodiment, 5000 bursts were actually processed, resulting in waveforms of 1380 target imaging points. The overall waveform is shown below. Figure 6 As shown in (a), the vertical axis represents the azimuth imaging points, and the horizontal axis represents the multi-view waveform for each target imaging point. It can be seen that the waveform is sawtooth-shaped, consistent with the Sentinel-3 Class 1B product. Processing the same data using the Sentinel open-source Python processing method released by Sentinel-3 yields the following results: Figure 6 As shown in (b), the two results are quite similar.

[0114] However, a careful comparison of the waveforms of certain target imaging points, such as the waveform of target imaging point 1020, reveals... Figure 7 As shown, Figure 7 (a) is the multi-view waveform of a certain imaging point obtained in this embodiment (horizontal axis is the range position, vertical axis is the amplitude). Figure 7(b) The multi-view waveform of the target imaging point obtained by processing with an open-source Python program shows that the accumulated quality at the peak (within the red circle) of the multi-view waveform obtained by the Python program is not ideal, and the peak is not sharp. The multi-view waveform of the target imaging point obtained by the processing method in this embodiment has sharp peaks (within the red circle), and the imaging quality is better. In terms of processing time, the open-source Python program takes 18 seconds to process 5000 first burst data points, while the method in this embodiment on the same computer takes 16 seconds to process 5000 first burst data points, which is almost the same.

[0115] Therefore, the technical solution of this embodiment improves the quality of multi-view waveforms without increasing the amount of computation, and can realize high-precision imaging processing of synthetic aperture radar altimeter, thereby obtaining high-quality L1B data in synthetic aperture radar altimeter imaging processing.

[0116] Figure 8 A schematic diagram of an embodiment of a synthetic aperture radar altimeter imaging processing system provided by the present invention is shown. Figure 8 As shown, the system 200 includes: a first processing module 210, a second processing module 220 and a third processing module 230.

[0117] The first processing module 210 is used to: obtain and determine multiple range compression data for each target imaging point based on the initial data of the synthetic aperture radar altimeter in the imaging process;

[0118] The second processing module 220 is used to: obtain a target MASK image for each target imaging point based on multiple total delay correction data for each target imaging point, and obtain a target waveform image for each target imaging point based on the target MASK image for each target imaging point and multiple range compression data;

[0119] The third processing module 230 is used to generate target data of the synthetic aperture radar altimeter in imaging processing based on the target waveform diagram of each target imaging point.

[0120] Preferably, the initial data includes: first auxiliary data and multiple first burst data; the first processing module 210 is specifically used for:

[0121] The first auxiliary data is subjected to linear interpolation to obtain the second auxiliary data, and multiple target imaging points are determined from the second auxiliary data;

[0122] Doppler center correction and Doppler sharpening are performed sequentially on each first burst data to obtain multiple second burst data. The azimuth frequency energy position of each target burst data corresponding to each target imaging point is determined from all the second burst data.

[0123] Based on the total delay correction of the frequency energy position corresponding to each target imaging point, the delay correction phase corresponding to each target imaging point is obtained. Then, the delay correction phase of each target imaging point is multiplied by the corresponding second burst data to obtain multiple total delay correction data for each target imaging point.

[0124] Preferably, the first processing module 210 is further configured to:

[0125] Perform a range-direction fast Fourier transform on each total delay correction data of any target imaging point to obtain multiple range-direction compressed data of the target imaging point, until multiple range-direction compressed data of each target imaging point are obtained.

[0126] The technical solution of this embodiment improves the quality of multi-view waveforms without increasing the amount of computation, and can realize high-precision imaging processing of synthetic aperture radar altimeter, thereby obtaining high-quality L1B data in synthetic aperture radar altimeter imaging processing.

[0127] The parameters and steps for implementing the corresponding functions of each module in the above embodiment of the synthetic aperture radar altimeter imaging processing system 200 provided by the present invention can be referred to the parameters and steps in the embodiment of the synthetic aperture radar altimeter imaging processing method provided above, and will not be repeated here.

[0128] An embodiment of the present invention provides a storage medium, comprising: the storage medium storing instructions, which, when read by a computer, cause the computer to execute steps such as those of a synthetic aperture radar altimeter imaging processing method. For details, please refer to the parameters and steps in the embodiment of the synthetic aperture radar altimeter imaging processing method provided above, which will not be repeated here.

[0129] Computer storage media include, for example, USB flash drives and external hard drives.

[0130] Those skilled in the art will know that the present invention can be implemented as a method, system, and storage medium.

[0131] Therefore, the present invention can be implemented in the following forms: it can be entirely hardware, entirely software (including firmware, resident software, microcode, etc.), or a combination of hardware and software, generally referred to herein as a "circuit," "module," or "system." Furthermore, in some embodiments, the present invention can also be implemented as a computer program product contained in one or more computer-readable media, which contains computer-readable program code. Any combination of one or more computer-readable media can be used. The computer-readable medium can be a computer-readable signal medium or a computer-readable storage medium. The computer-readable storage medium can be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination thereof. More specific examples (a non-exhaustive list) of computer-readable storage media include: an electrical connection having one or more wires, a portable computer disk, a hard disk, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage device, magnetic storage device, or any suitable combination thereof. In this document, a computer-readable storage medium can be any tangible medium that contains or stores a program that can be used by or in conjunction with an instruction execution system, apparatus, or device. Although embodiments of the invention have been shown and described above, it is to be understood that these embodiments are exemplary and should not be construed as limiting the invention. Those skilled in the art can make changes, modifications, substitutions, and variations to the above embodiments within the scope of the invention.

Claims

1. A synthetic aperture radar altimeter imaging processing method, characterized in that, include: Based on the initial data from the synthetic aperture radar altimeter in the imaging process, multiple range compression data for each target imaging point are obtained and determined based on multiple total delay correction data for each target imaging point. Based on multiple total delay correction data for each target imaging point, a target mask map for each target imaging point is obtained. Based on the target mask map for each target imaging point and multiple range compression data, a target waveform map for each target imaging point is obtained. Based on the target waveform diagram of each target imaging point, the target data of the synthetic aperture radar altimeter in the imaging process is generated.

2. The synthetic aperture radar altimeter imaging processing method according to claim 1, characterized in that, The initial data includes: first auxiliary data and multiple first burst data; the step of obtaining multiple total delay correction data for each target imaging point based on the initial data from the synthetic aperture radar altimeter in imaging processing includes: The first auxiliary data is subjected to linear interpolation to obtain the second auxiliary data, and multiple target imaging points are determined from the second auxiliary data; Doppler center correction and Doppler sharpening are performed sequentially on each first burst data to obtain multiple second burst data. The azimuth frequency energy position of each target burst data corresponding to each target imaging point is determined from all the second burst data. Based on the total delay correction of the frequency energy position corresponding to each target imaging point, the delay correction phase corresponding to each target imaging point is obtained. Then, the delay correction phase of each target imaging point is multiplied by the corresponding second burst data to obtain multiple total delay correction data for each target imaging point.

3. The synthetic aperture radar altimeter imaging processing method according to claim 1, characterized in that, The step of determining multiple range-compressed data for each target imaging point based on multiple total delay correction data for each target imaging point includes: Perform a range-direction fast Fourier transform on each total delay correction data of any target imaging point to obtain multiple range-direction compressed data of the target imaging point, until multiple range-direction compressed data of each target imaging point are obtained.

4. The synthetic aperture radar altimeter imaging processing method according to claim 2, characterized in that, The steps for obtaining the target mask map for each target imaging point based on multiple total delay correction data for each target imaging point include: Each total delay correction corresponding to any target imaging point is calculated with the minimum total delay correction corresponding to that target imaging point to generate a first MASK image of that target imaging point. Then, based on the loss location of each missing second burst data corresponding to that target imaging point, a second MASK image of that target imaging point is generated. Finally, the first MASK image and the second MASK image of that target imaging point are multiplied to obtain the target MASK image of that target imaging point. This process is repeated until the target MASK image of each target imaging point is obtained.

5. The synthetic aperture radar altimeter imaging processing method according to claim 1, characterized in that, The steps for obtaining the target waveform map for each target imaging point based on the target mask map and multiple range-compressed data for each target imaging point include: Based on the target MASK map of any target imaging point and the matrix corresponding to multiple range-direction compressed data, a first waveform map containing multiple waveforms corresponding to the target imaging point is obtained. The multiple waveforms in the first waveform map of the target imaging point are then subjected to modulus and squaring processing, and all processed waveforms are accumulated to obtain the target waveform map of the target imaging point, until the target waveform map of each target imaging point is obtained.

6. The synthetic aperture radar altimeter imaging processing method according to claim 2, characterized in that, The step of generating target data for the synthetic aperture radar altimeter in imaging processing based on the target waveform diagram of each target imaging point includes: Based on the second auxiliary data and the target waveform diagram of each target imaging point, the target data of the synthetic aperture radar altimeter in the imaging process is generated.

7. A synthetic aperture radar altimeter imaging processing system, characterized in that, include: The first processing module, the second processing module, and the third processing module; The first processing module is used to: obtain and determine multiple range compression data for each target imaging point based on the initial data of the synthetic aperture radar altimeter in the imaging process; The second processing module is used to: obtain a target MASK image for each target imaging point based on multiple total delay correction data for each target imaging point, and obtain a target waveform image for each target imaging point based on the target MASK image for each target imaging point and multiple range compression data; The third processing module is used to generate target data of the synthetic aperture radar altimeter in imaging processing based on the target waveform diagram of each target imaging point.

8. The synthetic aperture radar altimeter imaging processing system according to claim 7, characterized in that, The initial data includes: first auxiliary data and multiple first burst data; the first processing module is specifically used for: The first auxiliary data is subjected to linear interpolation to obtain the second auxiliary data, and multiple target imaging points are determined from the second auxiliary data; Doppler center correction and Doppler sharpening are performed sequentially on each first burst data to obtain multiple second burst data. The azimuth frequency energy position of each target burst data corresponding to each target imaging point is determined from all the second burst data. Based on the total delay correction of the frequency energy position corresponding to each target imaging point, the delay correction phase corresponding to each target imaging point is obtained. Then, the delay correction phase of each target imaging point is multiplied by the corresponding second burst data to obtain multiple total delay correction data for each target imaging point.

9. The synthetic aperture radar altimeter imaging processing system according to claim 7, characterized in that, The first processing module is further specifically used for: Perform a range-direction fast Fourier transform on each total delay correction data of any target imaging point to obtain multiple range-direction compressed data of the target imaging point, until multiple range-direction compressed data of each target imaging point are obtained.

10. A storage medium, characterized in that, The storage medium stores instructions that, when read by a computer, cause the computer to execute the synthetic aperture radar altimeter imaging processing method as described in any one of claims 1 to 6.

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