Satellite-borne rain measurement radar positioning precision correction method based on sea-land signal distribution difference

Abstract

The application provides a kind of based on sea-land signal distribution difference's satellite-borne rain measuring radar positioning precision correction method and system, comprising: determining the latitude and longitude range of overlapping area;With the rain measuring radar detection data after screening to determine the starting and ending detection period;The detection signal difference value of the current detection wave position and the previous detection wave position, the detection signal difference value of the current detection wave position and the next detection wave position in the same period are calculated to determine the land surface pixel signal threshold, extract the land surface distribution pixel;Determine the sea-land distribution boundary position of detection signal and count the total number of land surface distribution pixels;In the direction of along track and across track, pixel offset is carried out, and pixel matching coverage is calculated;The number of pixel offset in the direction of along track and across track closest to 1 is obtained respectively, and the positioning precision correction is completed.The application can be used in the research field of satellite-borne rain measuring radar detection signal accurate positioning, and is an effective and important technical means to realize the positioning precision correction of rain measuring radar detection signal.

Description

Technical Field

[0001] This invention belongs to the field of precise positioning of satellite-borne rain measurement radar detection signals, specifically, it relates to a method for correcting the positioning accuracy of satellite-borne rain measurement radar based on the differences in signal distribution between land and sea. Background Technology

[0002] Precipitation events are often accompanied by severe weather systems such as typhoons, torrential rains, or strong convection, making them crucial weather events. A deeper understanding of the three-dimensional structure and climatic distribution characteristics of precipitation is a prerequisite for meteorological disaster prevention and mitigation. Spaceborne precipitation radar possesses significant advantages over ground-based meteorological observation stations and other methods, enabling the acquisition of precipitation information in diverse terrains, uninhabited areas, and ocean surfaces, achieving effective detection of instantaneous precipitation globally. The abundant precipitation data accumulated through satellite remote sensing provides immense convenience and data support for research on regional precipitation structure characteristics.

[0003] The accuracy of the preprocessing of the raw detection signals from spaceborne rain-measuring radar is fundamental to subsequent data analysis and applications. Rain-measuring radar is affected by factors such as transportation, satellite launch, and the on-orbit operating environment, which can cause changes in load characteristic parameters such as the original line-of-sight of the radar detection beam. This results in a shift in the positioning accuracy of the raw detection signal, necessitating positioning accuracy correction.

[0004] Currently, for the positioning accuracy correction of satellite remote sensing slices, related technologies generally compare the positional relationship between the original detection signal distribution and the known ground observation target signal distribution, and adjust the positioning accuracy by utilizing the target point position matching characteristics of the two types of data. However, this method requires simultaneously acquiring the positions of fixed ground observation targets observed by the same remote sensing satellite, necessitating manual selection and identification, which introduces subjective judgment errors and detection signal distribution position matching errors. Meanwhile, some technologies adjust positioning accuracy by modifying payload parameters on-orbit, but the characteristic parameters of the payload to be modified are difficult to obtain, and the correction processing chain is relatively long. For example, patent document CN108242047A discloses a CCD-based optical satellite remote sensing image data correction method. By establishing forward and inverse calculation models from image to ground latitude and longitude for both virtual and real CCDs, it completes image stitching, band registration, geometric distortion correction, and generates a high-precision RPC.

[0005] Spaceborne precipitation radar is a microwave active precipitation measurement radar. Its detection signals show significant differences over the ocean and land surfaces. Positioning accuracy can be corrected by utilizing the relative positional differences between the sea-land distribution boundaries of the detection signals and the high-precision coastline. This method can complete positioning accuracy correction using a single-track detection signal, reducing the amount of data required for target location matching and mitigating errors in manual identification and evaluation of location matching in traditional methods. Therefore, it is necessary to propose a positioning accuracy correction method and system for spaceborne precipitation radar based on the differences in sea-land signal distribution, improving the preprocessing accuracy of spaceborne precipitation radar detection signals and better serving the analysis and application of backend satellite remote sensing data. Summary of the Invention

[0006] To address the shortcomings of existing technologies, the purpose of this invention is to provide a method for correcting the positioning accuracy of spaceborne rain measurement radar based on the differences in signal distribution between land and sea.

[0007] A method for correcting the positioning accuracy of a spaceborne rain-measuring radar based on the difference in signal distribution between land and sea, provided by the present invention, includes:

[0008] Step S1: Determine the range of the overlapping area based on the relative position of the coastline and the current rain-measuring radar detection area;

[0009] Step S2: Filter the rain-measuring radar detection data using the overlapping area range;

[0010] Step S3: Using the rain-measuring radar detection data, determine the starting detection period and the ending detection period;

[0011] Step S4: For the rain-measuring radar detection data between the start detection period and the end detection period, calculate the difference in detection signal between the current detection wave position and the previous and next detection wave positions within the same detection period;

[0012] Step S5: Determine the land surface pixel signal threshold based on the detected signal difference, and extract the land surface distributed pixels;

[0013] Step S6: Based on the extracted land surface distribution pixels, determine the location of the land-sea distribution boundary of the detection signal and count the total number of land surface distribution pixels;

[0014] Step S7: Perform cell offset in the along-track and cross-track directions, and calculate the cell matching coverage based on the total number of pixels distributed on the land surface;

[0015] Step S8: Based on the distribution of pixel matching coverage curves along the track and across the track, obtain the number of pixel offsets along the track and across the track where the pixel matching coverage is closest to 1.

[0016] Step S9: Complete the positioning accuracy correction based on the number of pixels offset along the track and across the track.

[0017] Preferably, the differences between the current probe wave position and the previous probe wave position and the next probe wave position are denoted as DF1 and DF2, respectively.

[0018] In step S5, if the DF1 of a pixel in the area near the land-sea boundary is positive and exceeds the first set value, and the DF2 of a pixel is negative or does not exceed the second set value, then the distribution of the detected pixels is considered to extend from the ocean to the land surface; otherwise, the distribution of the detected pixels is considered to extend from the land surface to the ocean surface. The signal values ​​of pixels that satisfy the distribution characteristics of DF1 and DF2 in all periods are counted, and the minimum value is set as the extraction threshold to obtain the land surface distribution pixels.

[0019] Preferably, in step S6, it is determined periodically whether the detected pixel is a land surface pixel. Based on the distribution order of the detected pixel positions, whether it extends from the ocean to the land surface or from the land surface to the ocean surface, the position of the rain-measuring radar detection signal at the sea-land distribution boundary is determined periodically, and the number of land surface pixels is counted to obtain the total number of land surface distributed pixels.

[0020] Preferably, in step S7, the pixel matching coverage rate is calculated using the following formula:

[0021]

[0022] Cov_rate represents the cell matching coverage rate;

[0023] Num i This represents the total number of land surface pixels within the coastline range during the i-th correction process;

[0024] Num total This represents the total number of pixels distributed across the land surface within the overlapping area.

[0025] A positioning accuracy correction system for a spaceborne rain-measuring radar based on the difference in signal distribution between land and sea, provided by the present invention, includes:

[0026] Module M1: Determines the range of the overlapping area based on the relative position of the coastline and the current rain-measuring radar detection area;

[0027] Module M2: Filters rain-measuring radar detection data using the overlapping area range;

[0028] Module M3: Uses the rain-measuring radar detection data to determine the starting detection period and the ending detection period;

[0029] Module M4: For the rain-measuring radar detection data between the start and end detection cycles, calculate the difference in detection signal between the current detection wave position and the previous and next detection wave positions within the same detection cycle;

[0030] Module M5: Based on the difference in the detected signals, determine the threshold of the land surface pixel signal and extract the distributed pixels on the land surface;

[0031] Module M6: Based on the extracted land surface distribution pixels, determine the location of the land-sea distribution boundary of the detection signal and count the total number of land surface distribution pixels;

[0032] Module M7: Performs cell offset in the along-track and cross-track directions, and calculates cell matching coverage based on the total number of pixels distributed on the land surface;

[0033] Module M8: Based on the distribution of pixel matching coverage curves along the track and across the track, obtain the number of pixel offsets along the track and across the track where the pixel matching coverage is closest to 1.

[0034] Module M9: Corrects positioning accuracy based on the number of pixels offset along and across the track.

[0035] Preferably, the differences between the current probe wave position and the previous probe wave position and the next probe wave position are denoted as DF1 and DF2, respectively.

[0036] In module M5, if the DF1 of a pixel in the area near the land-sea boundary is positive and exceeds a first set value, and the DF2 of a pixel is negative or does not exceed a second set value, then the distribution of the detected pixels is considered to extend from the ocean to the land surface; otherwise, the distribution of the detected pixels is considered to extend from the land surface to the ocean surface. The signal values ​​of pixels that satisfy the DF1 and DF2 distribution characteristics in all periods are counted, and the minimum value is set as the extraction threshold to obtain the land surface distribution pixels.

[0037] Preferably, in module M6, it is determined periodically whether the detected pixel is a land surface pixel. Based on the distribution order of the detected pixel positions, whether it extends from the ocean to the land surface or from the land surface to the ocean surface, the position of the rain-measuring radar detection signal at the sea-land distribution boundary is determined periodically, and the number of land surface pixels is counted to obtain the total number of land surface distributed pixels.

[0038] Preferably, in module M7, the pixel matching coverage rate is calculated using the following formula:

[0039]

[0040] Cov_rate represents the cell matching coverage rate;

[0041] Num i This represents the total number of land surface pixels within the coastline range during the i-th correction process;

[0042] Num total This represents the total number of pixels distributed across the land surface within the overlapping area.

[0043] According to the present invention, a computer-readable storage medium storing a computer program is provided, wherein when the computer program is executed by a processor, the steps of the method for correcting the positioning accuracy of a spaceborne rain measuring radar based on the difference in signal distribution between land and sea are implemented.

[0044] An electronic device according to the present invention includes a memory, a processor, and a computer program stored in the memory and executable on the processor. When the computer program is executed by the processor, it implements the steps of the positioning accuracy correction method for spaceborne rain measurement radar based on the difference in sea and land signal distribution.

[0045] Compared with the prior art, the present invention has the following beneficial effects:

[0046] 1. This invention does not require comparing the position of the current probe slice with the probe slice of the fixed ground observation target or modifying the load characteristic parameters on the orbit for correction. It does not require a large amount of data matching accuracy evaluation, and overcomes the technical problems that manual statistics and identification will increase matching errors, and that the parameters are not easy to obtain and the processing correction link is long. It fills the gap in the prior art.

[0047] 2. This invention can be applied to the research field of precise positioning of satellite-borne rain-measuring radar detection signals, and is an effective and important technical means to achieve positioning accuracy correction of rain-measuring radar detection signals.

[0048] 3. This invention corrects positioning accuracy by comparing the significant differences between rainfall radar detection signals over the ocean and land surfaces, and utilizing the relative positional differences between the sea-land distribution boundaries of the detection signals and the high-precision coastline. This method can complete positioning accuracy correction using single-track detection signals, reducing the large amount of data required for target position matching in traditional methods, and minimizing errors in manual statistical identification and evaluation of position matching. It also shortens the positioning accuracy correction link for on-orbit payload parameter injection to a certain extent, improving the timeliness and accuracy of preprocessing the raw rainfall radar detection signals. Attached Figure Description

[0049] Other features, objects, and advantages of the present invention will become more apparent from the following detailed description of non-limiting embodiments with reference to the accompanying drawings:

[0050] Figure 1 This is a schematic diagram of the working method of the present invention.

[0051] Figure 2 This is the original signal distribution diagram of the rain-measuring radar in the overlapping area of ​​this invention.

[0052] Figure 3 This is a map showing the distribution of the coastline of Hainan Province, China, within the overlapping area, as described in this invention.

[0053] Figure 4This is a map showing the distribution of the original detection signal of the rain-measuring radar and the coastline in Hainan Province, China, as described in this invention.

[0054] Figure 5 This is a gradient distribution diagram of the same-period signal variation of the rain-measuring radar in Hainan Province, China, within the overlapping area, as described in this invention.

[0055] Figure 6 This is a schematic diagram of the land surface pixel extraction of Hainan Province, China, in this invention.

[0056] Figure 7 This is a map showing the distribution of rain-measuring radar detection signals along the land-sea boundary in Hainan Province, China, as described in this invention.

[0057] Figure 8 This is a map showing the distribution of land surface pixels of the rain-measuring radar detection signal in Hainan Province, China, within the coastline area, as described in this invention.

[0058] Figure 9 This is a distribution curve of the number of pixels offset along the track and across the track in this invention, along with the coverage of the matching pixels.

[0059] Figure 10 This is a map showing the distribution of rain-measuring radar detection signals and coastline in Hainan Province, China, after positioning accuracy correction, as described in this invention. Detailed Implementation

[0060] The present invention will now be described in detail with reference to specific embodiments. These embodiments will help those skilled in the art to further understand the present invention, but do not limit the invention in any way. It should be noted that those skilled in the art can make several changes and improvements without departing from the concept of the present invention. These all fall within the protection scope of the present invention.

[0061] This invention determines the latitude and longitude range of the overlapping area based on the relative position of the high-precision coastline and the current rain-measuring radar detection area; filters the rain-measuring radar detection data and coastline data using the overlapping area range; determines the start and end detection cycles using the filtered rain-measuring radar detection data; calculates the difference in detection signals between the current detection wave position and the previous and next detection wave positions within the same cycle; determines the land surface pixel signal threshold based on the detection signal difference and extracts the land surface distributed pixels; determines the boundary position of the land-sea distribution of the detection signal and counts the total number of land surface distributed pixels; performs pixel offset in the along-track and cross-track directions, counts the number of land surface distributed pixels, and calculates the pixel matching coverage rate; based on the pixel matching coverage rate curve distribution in the along-track and cross-track directions, obtains the number of along-track and cross-track pixel offsets with the pixel matching coverage rate closest to 1; and completes the positioning accuracy correction based on the number of along-track and cross-track pixel offsets.

[0062] According to the present invention, a method for correcting the positioning accuracy of a spaceborne rain-measuring radar based on the difference in signal distribution between land and sea is provided, such as... Figure 1 As shown, it includes the following steps:

[0063] Step S1: Determine the latitude and longitude range of the overlapping area based on the relative position of the high-precision coastline and the current rain-measuring radar detection area. The rain-measuring radar detection data is single-track data, that is, within the single-track range of the rain-measuring radar detection, select the area that overlaps with the coastline and give the latitude and longitude range of the overlapping area (minimum longitude, maximum longitude, minimum latitude, and maximum latitude).

[0064] Step S2: Filter the rain-measuring radar detection data and coastline data using the overlapping area range. Select the background noise power data from the rain-measuring radar detection data, and filter the monorail bottom detection data and coastline data located within the overlapping area based on the latitude and longitude range of the overlapping area.

[0065] Step S3: Determine the start and end detection cycles using the filtered rain-measuring radar detection data. Using the filtered radar detection data, compare the position of each detected pixel with the latitude and longitude range of the overlapping area in each cycle to obtain the cycle (cycle number) of the rain-measuring radar entering and leaving the overlapping area, which is defined as the start and end detection cycles.

[0066] Step S4: Calculate the difference in detection signal between the current detection wave position and the previous and next detection wave positions within the same cycle. Using the rain-measuring radar detection data between the start and end cycles, within the same cycle, for each detection wave position, calculate the difference in detection signal between the current detection wave position and the previous and next detection wave positions, denoted as DF1 and DF2 respectively.

[0067] Step S5: Determine the land surface pixel signal threshold based on the difference in detected signals and extract the land surface distributed pixels. Using the detected signal differences DF1 and DF2, if the DF1 of pixels near the land-sea boundary is positive and relatively large, and the DF2 of the pixels is negative or a small positive value, then it indicates that the detected pixel distribution extends from the ocean to the land surface, and vice versa. Therefore, if the detected pixel location is distributed from the ocean to the land surface, and the detected signal value shows an increasing trend in each period, the signal values ​​of pixels that meet the distribution characteristics of DF1 and DF2 in all periods are statistically analyzed, and the minimum value is set as the extraction threshold. For the rain-measuring radar detection signal in the overlapping area, the land surface distributed pixels are extracted using the extraction threshold.

[0068] Step S6: Determine the location of the land-sea distribution boundary of the detection signal and count the total number of land surface pixels. Using the land surface pixels in the overlapping area, determine whether a detection pixel is a land surface pixel on a cycle-by-cycle basis. Combined with the distribution order of the detection pixels (extending from the ocean to the land surface or from the land surface to the ocean surface), determine the location of the rain-measuring radar detection signal at the land-sea distribution boundary on a cycle-by-cycle basis, and count the number of land surface pixels to obtain the total number of land surface pixels.

[0069] Step S7: Perform pixel offsets in the along-orbit and cross-orbit directions, count the number of land surface distributed pixels, and calculate the pixel matching coverage rate. The positioning accuracy correction process is decomposed into positioning accuracy correction processes in the satellite's along-orbit and cross-orbit detection directions, i.e., pixel offsets are performed in the along-orbit and cross-orbit directions. During each offset process, the total number of land surface distributed pixels within the coastline area is calculated. Combining the total number of land surface distributed pixels in the overlapping area with the calculated pixel matching coverage rate, the calculation formula is as follows:

[0070]

[0071] Where Cov_rate represents the cell matching coverage rate, Num i Num represents the total number of land surface pixels distributed within the coastline area during the i-th correction process. total This represents the total number of pixels distributed across the land surface within the overlapping area.

[0072] Step S8: Based on the pixel matching coverage curve distribution along the track and across the track, obtain the number of pixel offsets along the track and across the track in which the pixel matching coverage is closest to 1. Using the pixel matching coverage corresponding to the multiple pixel offset processes, form pixel matching coverage curves along the track and across the track. In each curve distribution, the number of offset pixels corresponding to the pixel matching coverage closest to 1 can be found, that is, the offset of the total number of land surface pixels within the coastline range closest to the total number of land surface pixels within the overlapping area. Then, obtain the optimal number of pixel offsets along the track and across the track.

[0073] Step S9: Correct the positioning accuracy based on the number of pixels offset along and across the track. Using the number of pixels offset along and across the track, correct the original positioning accuracy and improve the accuracy of the rain-measuring radar detection data preprocessing.

[0074] Furthermore, in conjunction with the appendix Figures 1 to 10 The specific description of the positioning accuracy correction method for spaceborne rain measuring radar based on the difference in signal distribution between land and sea of ​​the present invention is as follows:

[0075] The latitude and longitude range of the overlapping area is determined based on the relative position of the high-precision coastline and the current rain-measuring radar detection area. The rain-measuring radar detection data is single-track data, meaning that within the single-track range detected by the rain-measuring radar, areas overlapping with the coastline are selected, and the latitude and longitude range of the overlapping area (minimum longitude, maximum longitude, minimum latitude, and maximum latitude) is given.

[0076] Rainfall radar detection data and coastline data are filtered using the overlapping region. Rainfall radar detection data is selected based on its noise floor power. According to the latitude and longitude range of the overlapping region, single-track detection data and coastline data located within the overlapping region are then filtered. The original signal distribution of the rainfall radar within the overlapping region is shown below. Figure 2 As shown, the distribution of coastlines within the overlapping area is as follows: Figure 3 As shown.

[0077] The start and end detection cycles are determined using the filtered rainfall radar detection data. Using the filtered radar detection data, the positions of each detected pixel and the latitude and longitude range of the overlapping area are compared in each cycle to obtain the cycle (cycle number) of the rainfall radar entering and leaving the overlapping area, which is defined as the start and end detection cycles. The original rainfall radar detection signal and the coastline matching distribution are as follows: Figure 4 As shown.

[0078] Calculate the signal differences between the current probe position and the previous and subsequent probe positions within the same period. Using the rain-measuring radar detection data between the start and end periods, for each probe position within the same period, calculate the signal differences between the current probe position and the previous and subsequent probe positions, denoted as DF1 and DF2 respectively. The gradient distribution of the signal variation within the overlapping area of ​​the rain-measuring radar in the same period is shown below. Figure 5 As shown.

[0079] The land surface pixel signal threshold is determined based on the difference in the detected signals, and land surface distributed pixels are extracted. Using the detected signal differences DF1 and DF2, if the DF1 of pixels near the land-sea boundary is positive and relatively large, and the DF2 of the pixels is negative or a small positive value, then it indicates that the detected pixel distribution extends from the ocean to the land surface, and vice versa. Therefore, if the detected pixel location is distributed from the ocean to the land surface, and the detected signal value shows an increasing trend in each cycle, the signal values ​​of pixels satisfying the DF1 and DF2 distribution characteristics are statistically analyzed across all cycles, and the minimum value is set as the extraction threshold. For rain-measuring radar detection signals in overlapping areas, the land surface distributed pixels are extracted using the extraction threshold. A schematic diagram of land surface distributed pixel extraction is shown below. Figure 6 As shown.

[0080] The location of the land-sea boundary of the detection signal is determined, and the total number of land surface pixels is counted. Using the land surface pixels in the overlapping area, it is determined periodically whether a detection pixel is a land surface pixel. Combined with the distribution order of the detection pixels (extending from the ocean to the land surface or from the land surface to the ocean surface), the location of the rainfall radar detection signal at the land-sea boundary is determined periodically. The land-sea boundary distribution of the rainfall radar detection signal is as follows: Figure 7 As shown. The number of land surface pixels is counted periodically to obtain the total number of land surface distribution pixels. The distribution of land surface pixels in the rainfall radar detection signal within the coastline area is shown in the figure. Figure 8 As shown.

[0081] Pixel offsets are performed along the orbit and across the orbit, the number of land surface pixels is counted, and the pixel matching coverage rate is calculated. The positioning accuracy correction process is decomposed into positioning accuracy correction processes along the satellite's orbit and across the orbit, i.e., pixel offsets are performed in both directions. During each offset, the total number of land surface pixels within the coastline area is calculated. Combining the total number of land surface pixels in the overlapping area with the calculated pixel matching coverage rate, the calculation formula is as follows:

[0082]

[0083] Where Cov_rate represents the cell matching coverage rate, Num i Num represents the total number of land surface pixels distributed within the coastline area during the i-th correction process. total This represents the total number of pixels distributed across the land surface within the overlapping area.

[0084] Based on the pixel matching coverage curve distribution along the track and across the track, the number of pixel offsets along the track and across the track with the pixel matching coverage closest to 1 is obtained. Using the pixel matching coverage corresponding to the multiple pixel offset processes, pixel matching coverage curves along the track and across the track are formed. In each curve distribution, the number of offset pixels corresponding to the pixel matching coverage closest to 1 can be found, that is, the offset of the total number of land surface pixels within the coastline range closest to the total number of land surface pixels within the overlapping area. Then, the optimal number of pixel offsets along the track and across the track is obtained. The distribution curves between the number of pixel offsets along the track and across the track and the matching pixel coverage are shown below. Figure 9 As shown.

[0085] Positioning accuracy correction is performed based on the number of pixel offsets along and across the track. Using these pixel offsets, the original positioning accuracy is corrected, thus improving the accuracy of the preprocessing of the rainfall radar detection data. The rainfall radar detection signal, after positioning accuracy correction, is matched with the coastline distribution as follows: Figure 10 As shown, after correcting the positioning accuracy of the rain-measuring radar detection signal, the matching accuracy between the land-sea distribution boundary of the detection signal and the high-precision coastline is significantly improved.

[0086] This invention also provides a positioning accuracy correction system for a spaceborne rain measurement radar based on the difference in signal distribution between land and sea. The positioning accuracy correction system for a spaceborne rain measurement radar based on the difference in signal distribution between land and sea can be implemented by executing the process steps of the positioning accuracy correction method for a spaceborne rain measurement radar based on the difference in signal distribution between land and sea. That is, those skilled in the art can understand the positioning accuracy correction method for a spaceborne rain measurement radar based on the difference in signal distribution between land and sea as a preferred embodiment of the positioning accuracy correction system for a spaceborne rain measurement radar based on the difference in signal distribution between land and sea.

[0087] A positioning accuracy correction system for a spaceborne rain-measuring radar based on the difference in signal distribution between land and sea, provided by the present invention, includes:

[0088] Module M1: Determines the latitude and longitude range of the overlapping area based on the relative position of the high-precision coastline and the current rain-measuring radar detection area. The rain-measuring radar detection data is single-track data, that is, within the single-track range of the rain-measuring radar detection, areas overlapping with the coastline are selected, and the latitude and longitude range of the overlapping area (minimum longitude, maximum longitude, minimum latitude, and maximum latitude) is given.

[0089] Module M2: Filters rain-measuring radar detection data and coastline data using the overlapping area range. The rain-measuring radar detection data selects the background noise power data, and based on the latitude and longitude range of the overlapping area, filters the monorail bottom detection data and coastline data located within the overlapping area.

[0090] Module M3: Determines the start and end detection cycles using the filtered rain-measuring radar detection data. Using the filtered radar detection data, the position of each detected pixel is compared with the latitude and longitude range of the overlapping area in each cycle to obtain the cycle (cycle number) of the rain-measuring radar entering and leaving the overlapping area, which is defined as the start and end detection cycles.

[0091] Module M4: Calculates the difference in detection signal between the current detection wave position and the previous and next detection wave positions within the same period. Using the rain-measuring radar detection data between the start and end periods, within the same period, for each detection wave position, calculates the difference in detection signal between the current detection wave position and the previous and next detection wave positions, denoted as DF1 and DF2 respectively.

[0092] Module M5: Determines the land surface pixel signal threshold based on the difference in detected signals and extracts the distributed pixels on the land surface. Using the detected signal differences DF1 and DF2, if a pixel near the land-sea boundary has a positive and relatively large DF1 value, and a negative or small positive DF2 value, it indicates that the detected pixel distribution extends from the ocean to the land surface, and vice versa. Therefore, if the detected pixel location is distributed from the ocean to the land surface, and the detected signal value shows an increasing trend in each cycle, the signal values ​​of pixels satisfying the DF1 and DF2 distribution characteristics are statistically analyzed across all cycles, and the minimum value is set as the extraction threshold. For rain-measuring radar detection signals in overlapping areas, the land surface distributed pixels are extracted using the extraction threshold.

[0093] Module M6: Determines the location of the land-sea distribution boundary of the detection signal and counts the total number of land surface pixels. Using the land surface pixels in the overlapping area, it determines whether a detection pixel is a land surface pixel on a cycle-by-cycle basis. Combining the distribution order of the detection pixels (extending from the ocean to the land surface or from the land surface to the ocean surface), it determines the location of the rain-measuring radar detection signal at the land-sea distribution boundary on a cycle-by-cycle basis and counts the number of land surface pixels to obtain the total number of land surface pixels.

[0094] Module M7: Performs pixel offsets in the along-orbit and cross-orbit directions, counts the number of land surface pixels, and calculates the pixel matching coverage rate. The positioning accuracy correction process is decomposed into positioning accuracy correction processes in the satellite's along-orbit and cross-orbit detection directions, i.e., pixel offsets are performed in the along-orbit and cross-orbit directions. During each offset, the total number of land surface pixels within the coastline area is calculated. Combining the total number of land surface pixels in the overlapping area with the calculated pixel matching coverage rate, the calculation formula is as follows:

[0095]

[0096] Where Cov_rate represents the cell matching coverage rate, Num i Num represents the total number of land surface pixels distributed within the coastline area during the i-th correction process. total This represents the total number of pixels distributed across the land surface within the overlapping area.

[0097] Module M8: Based on the pixel matching coverage curve distribution along the track and across the track, obtain the number of pixel offsets along the track and across the track in which the pixel matching coverage is closest to 1. Using the pixel matching coverage corresponding to the multiple pixel offset processes, pixel matching coverage curves along the track and across the track are formed. In each curve distribution, the number of offset pixels corresponding to the pixel matching coverage closest to 1 can be found, that is, the offset of the total number of land surface pixels within the coastline range closest to the total number of land surface pixels within the overlapping area. Then, the optimal number of pixel offsets along the track and across the track is obtained.

[0098] Module M9: Corrects positioning accuracy based on the number of pixel offsets along and across the track. Using the aforementioned number of pixel offsets along and across the track, the original positioning accuracy is corrected, thus improving the accuracy of the rain-measuring radar detection data preprocessing.

[0099] According to the present invention, a computer-readable storage medium storing a computer program is provided, wherein when the computer program is executed by a processor, the steps of the method for correcting the positioning accuracy of a spaceborne rain measuring radar based on the difference in signal distribution between land and sea are implemented.

[0100] Those skilled in the art will understand that, besides implementing the system and its various devices, modules, and units provided by this invention in the form of purely computer-readable program code, the same functions can be achieved entirely through logical programming of the method steps, making the system and its various devices, modules, and units of this invention function in the form of logic gates, switches, application-specific integrated circuits, programmable logic controllers, and embedded microcontrollers. Therefore, the system and its various devices, modules, and units provided by this invention can be considered as a hardware component, and the devices, modules, and units included therein for implementing various functions can also be considered as structures within the hardware component; alternatively, the devices, modules, and units for implementing various functions can be considered as both software modules implementing the method and structures within the hardware component.

[0101] Specific embodiments of the present invention have been described above. It should be understood that the present invention is not limited to the specific embodiments described above, and those skilled in the art can make various changes or modifications within the scope of the claims, which do not affect the essence of the present invention. Unless otherwise specified, the embodiments and features described in this application can be arbitrarily combined with each other.

Claims

1. A method for correcting the positioning accuracy of a spaceborne rain-measuring radar based on the difference in signal distribution between land and sea, characterized in that, include: Step S1: Determine the range of the overlapping area based on the relative position of the coastline and the current rain-measuring radar detection area; Step S2: Filter the rain-measuring radar detection data using the overlapping area range; Step S3: Using the rain-measuring radar detection data, determine the starting detection period and the ending detection period; Step S4: For the rain-measuring radar detection data between the start detection period and the end detection period, calculate the difference in detection signal between the current detection wave position and the previous and next detection wave positions within the same detection period; Step S5: Determine the land surface pixel signal threshold based on the detected signal difference, and extract the land surface distributed pixels; Step S6: Based on the extracted land surface distribution pixels, determine the location of the land-sea distribution boundary of the detection signal and count the total number of land surface distribution pixels; Step S7: Perform cell offset in the along-track and cross-track directions, and calculate the cell matching coverage based on the total number of pixels distributed on the land surface; Step S8: Based on the distribution of pixel matching coverage curves along the track and across the track, obtain the number of pixel offsets along the track and across the track where the pixel matching coverage is closest to 1. Step S9: Complete the positioning accuracy correction based on the number of pixels offset along the track and across the track.

2. The method for correcting the positioning accuracy of spaceborne rain-measuring radar based on the difference in signal distribution between land and sea, as described in claim 1, is characterized in that... The differences between the current probe wave position and the previous and next probe wave positions are denoted as DF1 and DF2, respectively. In step S5, if the DF1 of a pixel in the area near the land-sea boundary is positive and exceeds the first set value, and the DF2 of a pixel is negative or does not exceed the second set value, then the distribution of the detected pixels is considered to extend from the ocean to the land surface; otherwise, the distribution of the detected pixels is considered to extend from the land surface to the ocean surface. The signal values ​​of pixels that satisfy the distribution characteristics of DF1 and DF2 in all periods are counted, and the minimum value is set as the extraction threshold to obtain the land surface distribution pixels.

3. The method for correcting the positioning accuracy of spaceborne rain-measuring radar based on the difference in signal distribution between land and sea, as described in claim 1, is characterized in that... In step S6, it is determined periodically whether the detected pixel is a land surface pixel. Based on the distribution order of the detected pixel positions, whether it extends from the ocean to the land surface or from the land surface to the ocean surface, the position of the rain-measuring radar detection signal at the sea-land distribution boundary is determined periodically, and the number of land surface pixels is counted to obtain the total number of land surface distributed pixels.

4. The method for correcting the positioning accuracy of spaceborne rain-measuring radar based on the difference in signal distribution between land and sea, as described in claim 1, is characterized in that... In step S7, the cell matching coverage rate is calculated using the following formula: Cov_rate represents the cell matching coverage rate; Num i This represents the total number of land surface pixels within the coastline range during the i-th correction process; Num total This represents the total number of pixels distributed across the land surface within the overlapping area.

5. A positioning accuracy correction system for a spaceborne rain-measuring radar based on the difference in signal distribution between land and sea, characterized in that, include: Module M1: Determines the range of the overlapping area based on the relative position of the coastline and the current rain-measuring radar detection area; Module M2: Filters rain-measuring radar detection data using the overlapping area range; Module M3: Uses the rain-measuring radar detection data to determine the starting detection period and the ending detection period; Module M4: For the rain-measuring radar detection data between the start and end detection cycles, calculate the difference in detection signal between the current detection wave position and the previous and next detection wave positions within the same detection cycle; Module M5: Based on the difference in the detected signals, determine the threshold of the land surface pixel signal and extract the distributed pixels on the land surface; Module M6: Based on the extracted land surface distribution pixels, determine the location of the land-sea distribution boundary of the detection signal and count the total number of land surface distribution pixels; Module M7: Performs cell offset in the along-track and cross-track directions, and calculates cell matching coverage based on the total number of pixels distributed on the land surface; Module M8: Based on the distribution of pixel matching coverage curves along the track and across the track, obtain the number of pixel offsets along the track and across the track where the pixel matching coverage is closest to 1. Module M9: Corrects positioning accuracy based on the number of pixels offset along and across the track.

6. The satellite-borne rain measurement radar positioning accuracy correction system based on the difference in signal distribution between land and sea according to claim 5, characterized in that, The differences between the current probe wave position and the previous and next probe wave positions are denoted as DF1 and DF2, respectively. In module M5, if the DF1 of a pixel in the area near the land-sea boundary is positive and exceeds a first set value, and the DF2 of a pixel is negative or does not exceed a second set value, then the distribution of the detected pixels is considered to extend from the ocean to the land surface; otherwise, the distribution of the detected pixels is considered to extend from the land surface to the ocean surface. The signal values ​​of pixels that satisfy the DF1 and DF2 distribution characteristics in all periods are counted, and the minimum value is set as the extraction threshold to obtain the land surface distribution pixels.

7. The satellite-borne rain measurement radar positioning accuracy correction system based on the difference in signal distribution between land and sea according to claim 5, characterized in that, In module M6, it is determined periodically whether the detected pixel is a land surface pixel. Based on the distribution order of the detected pixel positions, whether it extends from the ocean to the land surface or from the land surface to the ocean surface, the position of the rain-measuring radar detection signal at the sea-land distribution boundary is determined periodically, and the number of land surface pixels is counted to obtain the total number of land surface distributed pixels.

8. The satellite-borne rain measurement radar positioning accuracy correction system based on the difference in signal distribution between land and sea according to claim 5, characterized in that, In module M7, the pixel matching coverage rate is calculated using the following formula: Cov_rate represents the cell matching coverage rate; Num i This represents the total number of land surface pixels within the coastline range during the i-th correction process; Num total This represents the total number of pixels distributed across the land surface within the overlapping area.

9. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is executed by the processor, it implements the steps of the positioning accuracy correction method for spaceborne rain measurement radar based on the difference in signal distribution between land and sea, as described in any one of claims 1 to 4.

10. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the computer program is executed by the processor, it implements the steps of the positioning accuracy correction method for spaceborne rain measurement radar based on the difference in signal distribution between land and sea, as described in any one of claims 1 to 4.

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