A method for determining the optimal position of a synchronous differential base station for aerial remote sensing flight

Abstract

The application discloses a method for determining optimal positions of synchronous differential base stations for aerial remote sensing flight, and belongs to the technical field of aerial remote sensing. The method comprises the following steps: performing spatial analysis on vector data of a working area, quantitatively calculating distance average distance and maximum distance parameters, calculating average distances of each position from the working area within a given maximum base station distance threshold range by using python, outputting results, performing spatial analysis on the evaluation distance results and road data, extracting a range with a certain threshold distance from the road, and combining surface land cover classification data and road vector data according to base station erection requirements of different scales, surface cover, water area and forest area which are not suitable for base station erection, open source DEM data, and the optimal base station erection position or the nearest position of the base station erection is circled, so as to guarantee the differential processing precision of aerial remote sensing POS data.

Description

TECHNICAL FIELD

[0001] The application belongs to the field of aerial remote sensing technology, and relates to a method for determining optimal positions of aerial remote sensing flight synchronous differential base stations. BACKGROUND

[0002] Aerial remote sensing is a means for acquiring information of the ground surface by non-contact manner with sensors carried on an airplane. Aerial remote sensing has the characteristics of high resolution and high accuracy compared with satellite remote sensing, and is an important part of remote sensing application. The basic principle of aerial remote sensing is to determine the position and shape of the object by measuring the image point according to the object-image space geometric relationship. Therefore, the establishment of the object-image space geometric relationship is the core problem of aerial remote sensing. The imaging principle of both frame cameras and linear array push-broom cameras is determined and known, so the main problem of establishing the object-image space geometric relationship is the determination of the spatial position and attitude of the sensor, which is generally referred to as sensor orientation. In recent years, DGPS positioning technology and DGPS / IMU combined navigation positioning technology have become the mainstream technology of aerial remote sensing.

[0003] DGPS is to observe GPS satellite signals synchronously and continuously through one or more GPS receivers set on the ground base station and the GPS receiver installed on the mobile carrier, and to obtain the spatial position parameters of the mobile carrier through GPS carrier phase measurement differential positioning technology. The DGPS positioning accuracy depends on many factors, which are not only affected by the receiving conditions, signal loss, atmospheric refraction, multipath, satellite number, base station distribution distance and other factors, but also related to the DCPS processing technology, such as the system accuracy can reach meter level by using pseudo-range differential positioning, and the accuracy can reach centimeter level by using carrier phase differential processing technology. In general, with the increase of the distance between the moving target and the reference station, the influence of ephemeris error and atmospheric propagation error will increase significantly. According to experience, the decline rate of GPS positioning accuracy is about 1 centimeter per kilometer. Therefore, the selection of the optimal base station position has an important influence on the accuracy of aerial remote sensing data. SUMMARY

[0004] The application provides a method for determining optimal positions of aerial remote sensing flight synchronous differential base stations,

[0005] A method for determining the optimal position of an airborne remote sensing flight synchronous differential base station erection, comprising the following steps: quantitatively calculating the distance from the work area average distance and maximum distance parameters by spatial analysis of the vector data of the work area, calculating the average distance from the work area for each position within a given maximum base station distance threshold range using python, and outputting the results, conducting spatial analysis on the evaluation distance results and road data, extracting the range within a certain threshold distance from the road (traffic accessibility), and according to the requirements of base station erection at different scales, combining land cover classification data and road vector data, and combining land cover, removing areas unsuitable for base station erection such as water and forest, and combining open source DEM data to delineate the optimal base station erection position or the nearest position for base station erection, thereby ensuring the accuracy of airborne remote sensing data.

[0006] The advantages of the present application are:

[0007] 1. Distance constraint according to specification requirements

[0008] The present application constrains the distance between the base station and the work area by quantitative calculation to ensure that it meets the specification requirements. This method effectively optimizes the base station position, thereby reducing errors and improving the accuracy of airborne remote sensing data, ensuring that the distance between the base station and the mobile receiver is controlled within the optimal range. This significantly improves the accuracy of the data, providing a reliable data foundation for subsequent analysis and application.

[0009] 2. Globally optimal base station site selection

[0010] Considering the inverse relationship between distance and the accuracy of airborne remote sensing POS or GPS differential processing, the present application performs rasterization processing on the work area and calculates the average distance from the base station position, enabling the base station selection to obtain globally optimal results. This method ensures the positioning accuracy within the entire work area range, optimizes the reliability of data collection, and reduces the need for repeated observations, improving work efficiency.

[0011] 3. Comprehensive consideration of environmental factors

[0012] The present application considers factors such as roads, land cover, and terrain during base station site selection, providing important results for field operations. This comprehensive analysis method not only improves the scientificity and accuracy of base station site selection, but also ensures the practical operability of the site selection scheme, adapting to the needs of different environmental conditions. By removing unsuitable areas such as forests and water areas, the position selection of the base station is further optimized.

[0013] 4. Automatic operation reduces the use threshold

[0014] By using Python for automatic operation of distance specification area, the application reduces the use threshold. On this basis, even without professional data, it can guarantee that the base station erection meets the specification requirements. This automated method improves the simplicity and efficiency of operation, making the technology more widely and conveniently applied, especially for non-professionals, reducing the difficulty of learning and using.

[0015] 5、Improve data consistency

[0016] By optimizing base station site selection, the application can reduce the accumulation of positioning errors in the work area, improve data consistency and reliability. The improvement of data consistency is of great significance for subsequent analysis and application, such as geographic information system (GIS), environmental monitoring, resource management, etc., which can provide more accurate and consistent data support.

[0017] 6、Enhance the flexibility of technology application

[0018] The application adopts flexible calculation and analysis methods, making the base station site selection adaptable to different work area shapes and environmental conditions. This flexibility makes the technology more widely applicable, meeting the needs of various complex terrains and environments, thus improving the application value and applicability of the technology.

[0019] 7、Improve response speed

[0020] Through automatic and scientific site selection method, the application can quickly respond to the needs of different work areas, significantly shortening the time of base station site selection. This rapid response capability is of great significance in emergency response, disaster monitoring and other scenarios that require rapid deployment, providing timely and reliable data support.

[0021] 8、Reduce environmental impact

[0022] Environmental factors are considered in the site selection process to avoid base station erection in ecologically sensitive areas, protected areas, and other areas, reducing the impact on the environment. This environmentally friendly site selection method not only meets the concept of sustainable development, but also improves the social acceptance and recognition of the project. BRIEF DESCRIPTION OF DRAWINGS

[0023] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, a brief introduction to the drawings needed in the embodiment or prior art description will be given below. Obviously, the drawings in the following description are only some embodiments of the present application, and those skilled in the art can obtain other drawings according to these drawings without creative labor. As shown in the drawings:

[0024] Figure 1 The technical flowchart of the present application.

[0025] Figure 2 A working area case diagram of the present application.

[0026] Figure 3 An initialization range of the present application.

[0027] Figure 4 A working area gridding result of the present application.

[0028] Figure 5 A test area average distance calculation result of the present application.

[0029] Figure 6 A test area maximum distance calculation result of the present application.

[0030] Figure 7 A final result of the present application conforming to the base station allowed distance.

[0031] Figure 8 A better accessibility base station area (no water area, vegetation, and thus the final result) of the present application. DETAILED DESCRIPTION

[0032] The technical solutions in the embodiments of the present application will be described clearly and completely below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, rather than all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative labor fall within the scope of protection of the present application.

[0033] Embodiment 1: as shown in Figure 1 , Figure 2 , Figure 3 , Figure 4 , Figure 5 , Figure 6 , Figure 7 and Figure 8 An aerial remote sensing differential base station erection site selection method, in aerial remote sensing operation, the shape of the working area can be irregular, the ground environment and traffic conditions of the working area have great differences according to different regions, therefore, by performing spatial analysis on the vector data of the working area, the average distance and maximum distance parameters from the working area are quantitatively calculated, then according to the requirements of base station erection of different scales, combined with the land cover classification data and road vector data on the ground, the nearest position of the erected base station can be finally circled, so as to guarantee the aerial remote sensing data precision. The aerial remote sensing flight is provided with the accurate distance calculation of the base station erection in the survey area, and the optimal base station site selection is realized in combination with relevant data.

[0034] This invention uses Python to calculate and output the average distance from each location to the working area within a given maximum base station distance threshold. Based on the evaluation distance results and road data, spatial analysis is carried out to extract the range (accessible by traffic) from the road at a certain threshold. Finally, combined with the ground cover, areas such as water bodies and forests that are unsuitable for setting up base stations are eliminated. Finally, combined with open source DEM data, the optimal base station location is determined.

[0035] A method for site selection and deployment of an aerial remote sensing differential base station includes the following steps:

[0036] Step 1: Calculate the initial area based on the vector position of the working area. An initial threshold needs to be provided. The threshold can refer to the distance to the farthest base station in the aerial remote sensing field specifications, or other custom distances. Using the center points of one or more faces in the working area, determine the range where the distance to any point less than the threshold, with the threshold as the radius and the center point as the origin. If the working area has multiple faces, select the intersection of the center points of all faces with the threshold as the radius as the initial range. The initial range is calculated using the center points of the faces, therefore the resulting range is a subset that satisfies the condition that the distance to any location in the working area is less than the threshold. If the result of step 1 is empty, the working area needs to be partitioned, and the calculation repeated until the condition is met.

[0037] Step 2: Select a suitable minimum cell to rasterize the initial range and the working range. Using the center of each raster as the calculation point, calculate the maximum and average distances between each raster in the initial range and all raster cells in the working range. Output the maximum distance and the average distance. Delete any values ​​greater than the threshold in the results.

[0038] Step 3: Depending on the requirements, if there is a need for traffic accessibility, perform spatial analysis on the road vector and average distance results to obtain a suitable area within a certain range of the road. If there is no requirement for road accessibility, this step can be skipped.

[0039] Step 4: Import LUCC (Land Use) data according to requirements and delete locations such as forests and water bodies that are not suitable for base station construction.

[0040] Step 5: Intersect the areas obtained in Steps 3 and 4 to determine the suitable area for base station installation. If the result is empty, the work area needs to be partitioned, and the calculation repeated until the conditions are met. Finally, an open area or a good location with good visibility should be selected based on the actual site conditions as the final location for base station installation.

[0041] Example 2: As Figure 1 , Figure 2 , Figure 3 , Figure 4 , Figure 5 , Figure 6 , Figure 7 andFigure 8 As shown in the figure, an aerial remote sensing differential base station erection site selection method, comprising the following steps:

[0042] Step 1.1, workspace file preparation

[0043] The format is shapefile, and the face file includes at least four files: *.shp, *.shx, *.dbf, and *.prj. There can be several regions in the workspace, such as Figure 2 As shown in the figure, the workspace has 5 face files.

[0044] Step 1.2, initial range and rasterization

[0045] The maximum distance allowed by the base station needs to be input, and the size of the rasterization calculation. Taking 50km maximum distance and 150m raster size as an example. First, calculate the intersection area within 50km range of the center point of the 5 face files, and rasterize the result with 150m length, as shown in Figure 3 As shown in the figure, the dark area is the initial area that meets the conditions. The smaller the selected raster length, the larger the calculation amount and the more detailed the result. The initial range is called raster A.

[0046] Step 1.3, workspace area rasterization

[0047] The vectors of the workspace are rasterized according to the input size, with 150m as the raster size, as shown in Figure 4 As shown in the figure, the workspace raster file is called raster B.

[0048] Step 1.4, calculate the average distance and maximum distance.

[0049] The average distance refers to the average value of the distance between a point in the initial range raster A and all points in raster B, and the maximum distance. Set a point in raster A as (u, v), and the point set of raster B as {(x1, y1), (x2, y2), (x3, y3), …, (xn, yn)}. n n

[0050] The average distance D_mean can be calculated by the following formula:

[0051]

[0052] i is 1, 2, 3, …, or n, n is a positive integer.

[0053] The maximum distance refers to the farthest distance between a point in raster A and all points in raster B.

[0054] Using the same symbols, the maximum distance D_max can be calculated by the following formula: ​​

[0055] The maximum function max returns the maximum value of all the calculated distances.

[0056] The average distance and the maximum distance obtained from the test data are shown in Figure 5 , Figure 6 .

[0057] Step 1.5, output of the region meeting the specification

[0058] Because the grid A is centered on the middle point of each face file in the calculation of the initialization region, an overlapping region with a maximum distance as the radius is allowed. The range of the grid A is greater than and completely contains the distance range of the entire work area, so it is necessary to delete the results according to the threshold of the maximum operating distance, and the results are shown in Figure 7 .

[0059] Step 1.6, output of the optimal results of the comprehensive analysis

[0060] In actual work, technicians need to go to the designated area to erect the base station, so generally, the area close to the traffic road is considered, and the base station position needs to be suitable for the surface environment, and needs to be open and unobstructed in the surrounding area, so it is necessary to use land cover data to filter out the area suitable for the base station.

[0061] The final results meeting the base station allowable distance are spatially analyzed with the road, and if the road accessibility needs to be considered, a certain threshold buffer area of the road vector is selected and the overlapping part with the base station allowable distance grid is selected as the area with better accessibility, and 1km is selected as the threshold, and the results are shown in Figure 8 . In the results, the area with a distance of about small is used as the base station position, and the accuracy of the work area differential GPS is higher as a whole.

[0062] Finally, the lucc data is used for spatial analysis, and the areas such as water and vegetation are deleted, and the final results are obtained. In the test, the area is a gobi, and there is no water and vegetation, so the final results are Figure 8 . In actual base station erection, the area without business obstruction needs to be selected on site.

[0063] The above only describes the preferred embodiments of the present application and should not be used to limit the present application, and any modification, equivalent replacement and improvement made within the spirit and principle of the present application should be included in the protection scope of the present application.

Claims

1. A method for determining the optimal location for setting up a flight synchronization differential base station for airborne remote sensing, characterized in that, The process includes the following steps: spatial analysis of vector data in the work area to quantitatively calculate the average and maximum distance parameters from the work area; using Python to calculate the average distance from each location to the work area within a given maximum base station distance threshold and output the results; conducting spatial analysis based on the evaluation distance results and road data to extract the range of distance from roads at a certain threshold; based on the base station installation requirements at different scales, combining land cover classification data and road vector data, and combining land cover, eliminating areas unsuitable for base station installation such as water bodies and forests; and combining open-source DEM data to delineate the optimal base station installation location or the nearest location for base station installation, ensuring the accuracy of differential processing of aerial remote sensing POS data. It also includes the following steps: Step 1: Based on the vector position of the working area, calculate the initial area and assign an initial threshold. The threshold references the distance to the farthest base station in the aerial remote sensing field specifications or other custom distances. Using the center points of multiple faces within the working area, select the intersection of all face center points with the threshold as the radius as the initial range. Since the initial range is calculated based on the face center points, the resulting range is a subset satisfying that all locations within the working area are within the threshold range. If the result of step 1 is empty, the working area needs to be partitioned, and the calculation repeated until the condition is met. Step 2: Select a suitable minimum cell to rasterize the initial range and the working range. Using the center of each raster as the calculation point, calculate the maximum and average distances between each raster in the initial range and all raster cells in the working range. Output the maximum distance and the average distance. Delete any values ​​in the results where the maximum distance exceeds a threshold. Step 3: Based on requirements, if there is a need for traffic accessibility, perform spatial analysis on the road vector and average distance results to obtain a suitable area within a certain threshold distance from the road. If there is no requirement for road accessibility, skip this step. Step 4: Import LUCC (Land Use) data according to requirements, and delete forest and water areas that are unsuitable for base station construction. Step 5: Intersect the areas obtained in Step 3 and Step 4 to obtain a suitable range for base station installation. If the result is empty, the working area needs to be partitioned and recalculated until the conditions are met. Finally, the grid with the smallest average distance in the open area should be selected as the final location for base station installation based on the actual situation. The quantitative calculation of the average and maximum distance parameters from the work area also includes the following steps: Calculate the average distance and the maximum distance. Average distance refers to the average and maximum distance between points in the initial range grid A and all points in grid B. Let a point in grid A be ( ), the set of points of grid B and {( (), (), ), ..., ( )}, The mean distance D_mean is calculated by the following formula: The digits are 1, 2, 3... or n, where n is a positive integer. The maximum distance refers to the farthest distance between a point in grid A and all points in grid B. Using the same notation, the maximum distance D_max is calculated using the following formula: The maximum function `max` returns the maximum value among all calculated distances.

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