CN110440762B - Gridding image control point layout method for multi-rotor unmanned aerial vehicle mountainous area aerial survey image - Google Patents
Gridding image control point layout method for multi-rotor unmanned aerial vehicle mountainous area aerial survey image Download PDFInfo
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
- G01C11/00—Photogrammetry or videogrammetry, e.g. stereogrammetry; Photographic surveying
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- G—PHYSICS
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- G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
- G01C11/00—Photogrammetry or videogrammetry, e.g. stereogrammetry; Photographic surveying
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Abstract
The invention discloses a gridding image control point layout method for a mountainous area aerial survey image of a multi-rotor unmanned aerial vehicle, belonging to the technical field of aerial surveying and mapping; it comprises the following steps: 1. determining a mapping range; 2. selecting the size of the grid according to the proportion of the formed graph and the complexity of the terrain; 3. preliminarily designing an image control point layout scheme; 4. preliminarily optimizing an image control point layout scheme; 5. finally optimizing an image control point layout scheme; 6. image control points are distributed on site; 7. sorting the coordinates of the image control points; by the gridding image control point distribution scheme, the problems of large curvature of a flight line and uneven distribution of photos caused by deviation of the flight line due to the fact that the quality of the unmanned aerial vehicle is easily influenced by wind power can be well solved; through this scheme, the pos data precision that many rotor unmanned aerial vehicle carried on navigation type single-frequency GPS chip and lead to is solved to the mathematical model of usable rear intersection low, and the problem that the reliability is poor improves the pos precision and the reliability of photo.
Description
Technical Field
The invention relates to the technical field of aerial surveying and mapping, in particular to a gridding image control point arrangement method for mountainous area aerial surveying and mapping of a multi-rotor unmanned aerial vehicle.
Background
When using unmanned aerial vehicle to carry out large scale photogrammetry mapping in mountain area aviation at present, there are following two problems: (1) the multi-rotor unmanned aerial vehicle is light in weight and easy to deviate from a flight path due to wind, so that the flight path has high curvature and uneven photo distribution; (2) because the multi-rotor unmanned aerial vehicle carries a navigation type single-frequency GPS chip, the pos data has low precision and poor reliability; aiming at the first problem, the main reason is that the light unmanned aerial vehicle has poor wind resistance, but if the weight of the unmanned aerial vehicle is directly increased, the original design purpose of a scheme for carrying out aerial survey by using the light unmanned aerial vehicle is deviated; for the second precision problem, the main reason is that it is difficult to directly meet the aerial survey requirement in the single-frequency GPS chip, but because the replacement cost of hardware quality is too high, other means need to be adopted for improvement under the condition of limited expenditure.
Disclosure of Invention
The technical problem to be solved by the invention is as follows: the method for arranging the gridding image control points of the multi-rotor unmanned aerial vehicle mountainous area aerial survey imaging is provided, so that the problems that photo shooting of the unmanned aerial vehicle is not uniformly distributed and the data precision is poor in the current aerial survey process are solved.
In order to solve the problems, the invention provides the following technical scheme:
a gridding image control point layout method for multi-rotor unmanned aerial vehicle mountainous area aerial surveying mapping comprises the following steps:
s1, determining a mapping range on the scale map according to the aerial survey task book, and performing coordinate conversion on coordinates in different coordinate systems within the mapping boundary line range;
s2, selecting the size of the grid laid on the map;
s3, according to the grid size determined in the step S2, uniformly drawing grids in the range of the mapping boundary line determined in the step S1 on the measurement map; and numbering the grids
S4, checking the terrain in each grid determined in the step S3, determining terrain feature points in the grid according to the terrain on the map, taking the terrain feature points as image control points, uniformly setting grid points in the grid without the terrain feature points as image control points, and recording the coordinates of all the image control points;
s5, importing all the coordinates of the image control points obtained in the step S4 into a Google map, and further optimizing the image control points according to the latest satellite map generated by the Google map;
s6, importing the coordinates of the image control points optimized in the step S5 into a GNSS handbook, laying field image control points, and measuring the center coordinates of the marks according to the image control points which are actually laid and collected by a GNSS instrument;
and S7, uniformly numbering the coordinate data of the centers of all the image control point measurement marks, introducing the numbered image control points into the CAD, comparing, checking and correcting the numbered grids obtained in the step S3, and finally obtaining image control point layout coordinates with reliable precision.
Preferably, the coordinate conversion performed in step S1 is obtained by conversion as follows:
x2＝x1+Δx
y2＝y1+Δy
in the formula, x1、y1Is the coordinate in the coordinate system before conversion, and Δ x, Δ y are the coordinates in the coordinate system inferiorCan be calculated according to the coordinates of the control points, x2、y2Are the coordinates of the transformed coordinate system.
Preferably, if a topographic map with a scale of 1:500 is selected, the size range of the grid selected in the step S2 is between 60 m and 120 m; if a 1:1000 scale topographic map is selected, the size range of the selected grid is 80-150 m; if a 1:2000 scale topographic map is selected, the size range of the selected grid is between 100 and 200 m; and the size of the grid specifically used is calculated by the following formula:
d＝dmin+(dmax-dmin)×λ
where d is the last used mesh size, dminIs the lower limit of the grid size, dmaxAnd lambda is a terrain complexity coefficient for the upper limit of the size of the grid.
Preferably, in step S4, the selection of the feature points in the mesh includes a mountain vertex, a mountain foot point, and a mountain shoulder slope point; meanwhile, the high points and the low points of the cliff and the steep bank with the local height change larger than 10m are defined as the terrain feature points.
Preferably, the optimization of the image control points in step S5 includes moving or deleting the image control points disposed on the buildings and ponds; image control points are added at the top and the foot of a large slope due to the construction of roads, houses and the like.
Preferably, in step S7, the accuracy analysis is performed on the numbered central coordinate data of the image control point measurement markers, and the image control points whose accuracy does not meet the requirement are removed.
The invention has the beneficial effects that:
the invention carries out scheme design before the image control point arrangement is implemented, and by selecting the optimal image control point arrangement scheme, the arranged image control points are uniformly distributed, have good terrain representativeness and meet the precision requirement. By the gridding image control point distribution scheme, the problems of large curvature of a flight line and uneven distribution of photos caused by deviation of the flight line due to the fact that the quality of the unmanned aerial vehicle is easily influenced by wind power can be well solved; through this scheme, the pos data precision that many rotor unmanned aerial vehicle carried on navigation type single-frequency GPS chip and lead to is solved to the mathematical model of usable rear intersection low, and the problem that the reliability is poor improves the pos precision and the reliability of photo.
Detailed Description
The invention will be further described with reference to specific examples:
example (b):
the embodiment provides a gridding image control point layout method for multi-rotor unmanned aerial vehicle mountainous area aerial surveying imaging, which comprises the following steps:
s1, determining a mapping range on the scale map according to the aerial survey task book, and performing coordinate conversion on coordinates in different coordinate systems within the mapping boundary line range; the mapping coordinate system required by the current aerial survey mission book is generally a CGCS2000 or Western Ann 80 coordinate system, while the ordinary scale map is generally a Beijing 54 coordinate system, so that the mapping coordinate system is required to be used after coordinate conversion;
s2, selecting the size of the grid laid on the map;
s3, according to the grid size determined in the step S2, uniformly drawing a grid within the range of the drawing boundary line determined in the step S1 on the measuring map; and numbering the grids;
s4, checking the terrain in each grid determined in the step S3, determining terrain feature points in the grid according to the terrain on the map, taking the terrain feature points as image control points, uniformly setting grid points in the grid without the terrain feature points as image control points, and recording the coordinates of all the image control points; when the topographic feature points are determined, the topographic feature points are generally arranged near the middle lines of three overlapped and side-to-side overlapped courses, and can be arranged in a course overlapping range when the topographic feature points are difficult to determine; meanwhile, image control points are additionally arranged around a large-area featureless area; meanwhile, a certain density is required to be ensured, so that the distance between each point and the corresponding point cannot be too large; under the condition that the temperature and the air pressure are proper, image control point layout work is carried out by adopting RTK, a ground control point symbol which is accurate and convenient to identify is generally manufactured, and grid type ground image control point layout is carried out;
s5, importing all the coordinates of the image control points obtained in the step S4 into a Google map, and further optimizing the image control points according to the latest satellite map generated by the Google map; considering that the production application of the proportional scale map has certain hysteresis, the positions, the number and the density of the image control points are optimized through the latest satellite map, and the accuracy of an aerial survey task is further improved;
s6, importing the coordinates of the image control points optimized in the step S5 into a GNSS handbook, laying field image control points, and measuring the center coordinates of the marks according to the image control points which are actually laid and collected by a GNSS instrument; when image control points are laid in field operation, mainly in a point lofting mode, laying image control point measurement marks after lofting to corresponding positions according to the indication of a GNSS instrument, and collecting the central coordinates of the actually laid image control point measurement marks;
and S7, uniformly numbering the coordinate data of the centers of all the image control point measurement marks, introducing the numbered image control points into the CAD, comparing, checking and correcting the numbered grids obtained in the step S3, and finally obtaining image control point layout coordinates with reliable precision.
Preferably, the coordinate conversion performed in step S1 is obtained by conversion as follows:
x2＝x1+Δx
y2＝y1+Δy
in the formula, x1、y1Is the coordinate of the coordinate system before conversion, and the coordinate system is poor, can be calculated according to the coordinate of the control point, x2、y2Are the coordinates of the transformed coordinate system.
Preferably, if a topographic map with a scale of 1:500 is selected, the size range of the grid selected in the step S2 is between 60 m and 120 m; if a 1:1000 scale topographic map is selected, the size range of the selected grid is 80-150 m; if a topographic map with a 1:2000 scale is selected, the size range of the selected grids is between 100 and 200 m; and the size of the grid specifically used is calculated by the following formula:
d＝dmin+(dmax-dmin)×λ
where d is the last used mesh size, dminIs the lower limit of the grid size, dmaxThe upper limit of the size of the grid, lambda is the terrain complexityAnd (4) degree coefficient. Considering the actual landform characteristics, if the terrain is smooth and the change is not large, taking the upper limit of the grid range value; if the terrain is complex and changes violently, the lower limit of the grid range value is taken into consideration and proper encryption is taken into consideration.
Preferably, in step S4, the selection of the feature points in the mesh includes a mountain vertex, a mountain foot point, and a mountain shoulder slope point; meanwhile, the high points and the low points of the cliff and the steep bank with the local height change larger than 10m are defined as the terrain feature points. The reason for providing the topographic feature points at the high and low points of the position where the height difference changes greatly is to control the height difference and to improve the representativeness of the distribution of the topographic feature points.
Preferably, the optimization of the image control points in step S5 includes moving or deleting the image control points disposed on the buildings and ponds; image control points are added at the top and the bottom of the slope at a larger side slope caused by building roads, houses and the like. Because human activities have a great influence on the natural environment, in a series of activities, the measurement marks which are inconvenient to be used as image control points on buildings and ponds need to be deleted, and the image control points need to be supplemented to ensure the measurement accuracy under the condition of artificially generated slopes.
Preferably, in step S7, the accuracy analysis is performed on the numbered central coordinate data of the image control point measurement markers, and the image control points whose accuracy does not meet the requirement are removed.
Claims (6)
1. The utility model provides a many rotor unmanned aerial vehicle mountain area aerial survey gridding like accuse point laying method of picture, its characterized in that: the method comprises the following steps:
s1, determining a mapping range on the scale map according to the aerial survey task book, and performing coordinate conversion on coordinates in different coordinate systems within the mapping boundary line range;
s2, selecting the size of the grid laid on the map;
s3, according to the grid size determined in the step S2, uniformly drawing grids in the range of the mapping boundary line determined in the step S1 on the measurement map; and numbering the grids;
s4, checking the terrain in each grid determined in the step S3, determining terrain feature points in the grid according to the terrain on the map, taking the terrain feature points as image control points, uniformly setting grid points in the grid without the terrain feature points as image control points, and recording the coordinates of all the image control points; the terrain feature points are arranged near the middle lines of the course three-piece overlapping and sideward overlapping, and the terrain feature points can be positioned in the course overlapping range; meanwhile, image control points are added around the large-area featureless area, and image control point layout work is carried out by adopting RTK;
s5, importing all the coordinates of the image control points obtained in the step S4 into a Google map, and further optimizing the image control points according to the latest satellite map generated by the Google map;
s6, importing the coordinates of the image control points optimized in the step S5 into a GNSS handbook, laying field image control points, and measuring the center coordinates of the marks according to the image control points which are actually laid and collected by a GNSS instrument;
and S7, uniformly numbering the coordinate data of the centers of all the image control point measurement marks, introducing the numbered image control points into the CAD, comparing, checking and correcting the numbered grids obtained in the step S3, and finally obtaining image control point layout coordinates with reliable precision.
2. The method for laying gridded image control points of the mountainous area aerial surveying image of the multi-rotor unmanned aerial vehicle according to claim 1, wherein the method comprises the following steps: the coordinate conversion performed in step S1 is obtained by conversion by the following equation:
x2＝x1+Δx
y2＝y1+Δy
in the formula, x1、y1Is the coordinate of coordinate system before conversion, and Δ x and Δ y are poor coordinate system and can be calculated according to the coordinate of control point, x2、y2Are the coordinates of the transformed coordinate system.
3. The method for laying gridded image control points of the mountainous area aerial surveying image of the multi-rotor unmanned aerial vehicle according to claim 1, wherein the method comprises the following steps: if a topographic map with a scale of 1:500 is selected, the size range of the grid selected in the step S2 is between 60 and 120 m; if a 1:1000 scale topographic map is selected, the size range of the selected grid is 80-150 m; if a 1:2000 scale topographic map is selected, the size range of the selected grid is between 100 and 200 m; and the size of the grid specifically used is calculated by the following formula:
d＝dmin+(dmax-dmin)×λ
where d is the last used mesh size, dminIs the lower limit of the grid size, dmaxAnd lambda is a terrain complexity coefficient for the upper limit of the size of the grid.
4. The gridded image control point layout method for the mountainous area aerial survey image of the multi-rotor unmanned aerial vehicle according to claim 1, characterized in that: in step S4, selecting a terrain feature point in the mesh, including a mountain vertex, a mountain foot point, and a mountain shoulder slope point; meanwhile, the high points and the low points of the cliff and the steep bank with the local height change larger than 10m are defined as the terrain feature points.
5. The method for laying gridded image control points of the mountainous area aerial surveying image of the multi-rotor unmanned aerial vehicle according to claim 1, wherein the method comprises the following steps: the optimization of the image control points in step S5 includes moving or deleting the image control points disposed on the buildings and ponds; image control points are added at the top and the foot of the slope due to the construction of roads and houses.
6. The method for laying gridded image control points of the mountainous area aerial surveying image of the multi-rotor unmanned aerial vehicle according to claim 1, wherein the method comprises the following steps: in step S7, precision analysis is performed on the numbered central coordinate data of the image control point measurement markers, and image control points whose precision does not meet the requirement are removed.
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| CN111678503A (en) * | 2020-06-15 | 2020-09-18 | 西安航空职业技术学院 | Unmanned aerial vehicle aerial survey control point arrangement and identification method and system |
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| CN112556725B (en) * | 2020-12-10 | 2023-03-21 | 湖北省地震局(中国地震局地震研究所) | Detection method for relative accuracy of portable unmanned aerial vehicle non-control point survey chart |
| CN117451011B (en) * | 2023-12-22 | 2024-03-08 | 南京信息工程大学 | Photogrammetry image control point quality evaluation method based on Monte Carlo test |
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