CN114199189B - Mining subsidence monitoring method combining unmanned plane and DINSAR technology - Google Patents
Mining subsidence monitoring method combining unmanned plane and DINSAR technology Download PDFInfo
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
- G01C5/00—Measuring height; Measuring distances transverse to line of sight; Levelling between separated points; Surveyors' levels
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- G01S13/00—Systems using the reflection or reradiation of radio waves, e.g. radar systems; Analogous systems using reflection or reradiation of waves whose nature or wavelength is irrelevant or unspecified
- G01S13/88—Radar or analogous systems specially adapted for specific applications
- G01S13/885—Radar or analogous systems specially adapted for specific applications for ground probing
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- G01S13/00—Systems using the reflection or reradiation of radio waves, e.g. radar systems; Analogous systems using reflection or reradiation of waves whose nature or wavelength is irrelevant or unspecified
- G01S13/88—Radar or analogous systems specially adapted for specific applications
- G01S13/89—Radar or analogous systems specially adapted for specific applications for mapping or imaging
- G01S13/90—Radar or analogous systems specially adapted for specific applications for mapping or imaging using synthetic aperture techniques, e.g. synthetic aperture radar [SAR] techniques
- G01S13/9004—SAR image acquisition techniques
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- G01S19/00—Satellite radio beacon positioning systems; Determining position, velocity or attitude using signals transmitted by such systems
- G01S19/38—Determining a navigation solution using signals transmitted by a satellite radio beacon positioning system
- G01S19/39—Determining a navigation solution using signals transmitted by a satellite radio beacon positioning system the satellite radio beacon positioning system transmitting time-stamped messages, e.g. GPS [Global Positioning System], GLONASS [Global Orbiting Navigation Satellite System] or GALILEO
- G01S19/42—Determining position
- G01S19/45—Determining position by combining measurements of signals from the satellite radio beacon positioning system with a supplementary measurement
- G01S19/46—Determining position by combining measurements of signals from the satellite radio beacon positioning system with a supplementary measurement the supplementary measurement being of a radio-wave signal type
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- Radar Systems Or Details Thereof (AREA)
Abstract
The invention relates to the technical field of mining subsidence monitoring, in particular to a mining subsidence monitoring method combining unmanned aerial vehicle and DINSAR technology. The method not only utilizes the high precision of unmanned plane data in the center of a subsidence area, but also maintains the superiority of a DINSAR differential result in edge monitoring, and overcomes the shortcomings of the DINSAR approach in the incoherence of large gradient deformation and the defects of unmanned plane technology in the aspect of edge micro deformation monitoring. And the advantages of the two data are complemented, so that the high-precision monitoring of the mining subsidence area is realized.
Description
Technical Field
The invention relates to the technical field of mining subsidence monitoring, in particular to a mining subsidence monitoring method combining unmanned aerial vehicle and DINSAR technology.
Background
The mining causes surface movement and deformation because the original stress balance state of surrounding rock mass is destroyed after the ore layer of the mining area is mined, and stress redistribution is required to reach a new balance. After the underground ore layer is mined in a large area, the upper rock layer is out of support, the original stress balance condition is destroyed, movement deformation is generated, and then the overlying rock layer is slumped, broken and bent, so that the earth surface is sunk and concavely deformed. The subsidence of the ground caused by the mining of the seam is referred to herein as mining subsidence.
Mining subsidence is affected by a plurality of factors, and complete surface deformation information needs to be monitored so as to provide scientific basis for safety mining and comprehensive environmental treatment of subsidence areas. The traditional mining subsidence monitoring method is leveling measurement and GPS measurement, but the traditional monitoring technologies such as leveling measurement and GPS measurement require a great deal of manpower and material resources, and continuous ground deformation information cannot be directly obtained. Unmanned aerial vehicle low altitude photogrammetry technology and synthetic aperture radar differential interferometry (differential interferometric synthetic aperture radar, DInSAR) technology are used as novel geodetic measurement means developed in recent years, and the defects of the traditional monitoring technology are overcome to a certain extent. Mining subsidence is a large-deformation geological disaster, and although the central subsidence value of a subsidence area can be obtained by monitoring mining subsidence by an unmanned plane, subsidence data cannot reach the traditional millimeter-level monitoring precision, high-precision monitoring of the edge of a mining area is difficult, and the edge expression capability is poor; the DInSAR technology is affected by various factors such as track error and atmospheric delay, when the deformation gradient of the ground surface is too large, interference image pair is lost, and effective interference fringes cannot be obtained, so that a main value of mining subsidence cannot be obtained, and the accuracy of a subsidence area with large and rapid subsidence amount is low.
Because the limitations of the existing monitoring technology can not accurately obtain the subsidence deformation information of the whole earth surface in the monitoring process, a method for monitoring the subsidence deformation is needed to be provided so as to obtain a more complete high-precision monitoring result.
Disclosure of Invention
The invention aims to provide a mining subsidence monitoring method combining unmanned aerial vehicle and DINSAR technology, so as to solve the problems in the prior art.
In order to achieve the above purpose, the technical scheme adopted by the invention is as follows:
a mining subsidence monitoring method combining unmanned aerial vehicle and DInSAR techniques, the method comprising:
the method comprises the steps of monitoring an edge area of mining subsidence through a DINSAR, determining a coherence threshold of the DINSAR monitoring according to SAR satellite parameters, and taking a monitoring point which is smaller than the coherence threshold and closest to a mining subsidence center as a boundary of the DINSAR monitoring area;
the method comprises the steps of monitoring a mining subsidence central area through an unmanned aerial vehicle, determining a monitoring threshold value of unmanned aerial vehicle monitoring according to an unmanned aerial vehicle monitoring value and a corresponding actually measured level value, and taking a monitoring point which is larger than the monitoring threshold value and farthest away from the mining subsidence center as a boundary of the unmanned aerial vehicle monitoring area;
and acquiring high-precision surface deformation information of mining subsidence according to the coordinates of each monitoring point and the corresponding monitoring value of the DINSAR monitoring area and the unmanned aerial vehicle monitoring area.
Preferably, the coherence threshold of the DInSAR monitoring is determined according to the SAR satellite parameters, specifically:
obtaining a theoretical maximum deformation gradient d which can be detected by the DINSAR according to the radar wavelength and the pixel size of the SAR satellite max The saidThe lambda is the radar wavelength, and the mu is the pixel size;
maximum deformation gradient D detectable according to preset DINSAR max And said d max Determining a coherence coefficient, said D max ＝d max +0.002 (γ -1), the γ being the coherence coefficient;
and taking the obtained coherence coefficient as a coherence threshold for screening the DINSAR monitoring value.
Preferably, the monitoring threshold value of the unmanned aerial vehicle monitoring is determined according to the unmanned aerial vehicle monitoring value and the corresponding actually measured level value, specifically:
according to the formulaAcquiring a monitoring threshold T;
wherein the U is i Unmanned aerial vehicle monitoring value W for ith monitoring point i The measured level value of the ith monitoring point is obtained, and n is the number of monitoring points.
Preferably, if an unmonitored point exists between the DInSAR monitoring area and the unmanned aerial vehicle monitoring area, determining a monitored value of the unmonitored point by adopting an inverse distance weighting method, specifically:
according to the distance between the non-monitored point and the monitored points around the non-monitored point, the method passes through the formulaCalculating a monitoring value of an unmonitored point;
wherein i is an unmonitored point, j is a monitored point around the unmonitored point, W i And W is j Respectively representing the monitoring values of the corresponding points, d j Is the distance between the non-monitored point and the monitored points around it.
The beneficial effects of the invention are as follows:
the invention provides a mining subsidence monitoring method combining unmanned aerial vehicle and DINSAR technology, which fuses unmanned aerial vehicle monitoring results of mining subsidence areas with DINSAR differential subsidence results. The method not only utilizes the high precision of unmanned plane data in the center of a subsidence area, but also maintains the superiority of a DINSAR differential result in edge monitoring, and overcomes the shortcomings of the D-InSAR approach in the decoherence of large gradient deformation and the defects of unmanned plane technology in the aspect of edge micro deformation monitoring. And the advantages of the two data are complemented, so that the high-precision monitoring of the mining subsidence area is realized.
Drawings
FIG. 1 is a schematic view of various monitoring areas of a production subsidence area in accordance with an embodiment of the present invention;
in the figure, 1-mining area mining subsidence affects edges, 2-DInSAR monitors regional boundaries, and 3-unmanned aerial vehicle monitors regional boundaries.
Detailed Description
The present invention will be described in further detail with reference to the accompanying drawings, in order to make the objects, technical solutions and advantages of the present invention more apparent. It should be understood that the detailed description is presented by way of example only and is not intended to limit the invention.
The invention provides a mining subsidence monitoring method combining unmanned plane and DINSAR technology, which comprises the following steps:
the method comprises the steps of monitoring an edge area of mining subsidence through a DINSAR, determining a coherence threshold of the DINSAR monitoring according to SAR satellite parameters, and taking a monitoring point which is smaller than the coherence threshold and closest to a mining subsidence center as a boundary of the DINSAR monitoring area;
the method comprises the steps of monitoring a mining subsidence central area through an unmanned aerial vehicle, determining a monitoring threshold value of unmanned aerial vehicle monitoring according to an unmanned aerial vehicle monitoring value and a corresponding actually measured level value, and taking a monitoring point which is larger than the monitoring threshold value and farthest away from the mining subsidence center as a boundary of the unmanned aerial vehicle monitoring area;
and acquiring high-precision surface deformation information of mining subsidence according to the coordinates of each monitoring point and the corresponding monitoring value of the DINSAR monitoring area and the unmanned aerial vehicle monitoring area.
At present, different SAR satellites mainly adopt L-band, C-band and X-band. For example, ALOS-1 and JERS-1 satellites employ an L band with a wavelength of 23.5cm; the RADASTA and the Sentinel satellite adopt C wave bands, and the wavelength is 5.6cm; the terraasar-X and COSMO satellites use the X-band, with a wavelength of 3cm. In the DINSAR technology, the deformation quantity of adjacent pixels, which can be acquired by interferometry in the adjacent revisit period, of the SAR satellite is lambda/4 at maximum. Therefore, the maximum deformation amount of the adjacent pixels which can be acquired in the L wave band is 5.87cm, the maximum deformation amount of the adjacent pixels which can be acquired in the C wave band is 1.4cm, and the maximum deformation amount of the adjacent pixels which can be acquired in the X wave band is 0.75cm. Furthermore, the greatest magnitude of sedimentation that can be monitored by the DInSAR technique during two imaging under ideal conditions is: w=r·λ/4 μ, where: w represents the line-of-sight settlement, r represents the primary influence radius of the mining area, and mu is the pixel size (ground resolution of the SAR sensor). The maximum vertical settlement of the InSAR monitoring is Δrmax=w/cos θ, where: Δrmax represents the maximum settlement amount in the vertical direction, and θ is the radar incident angle.
In practical applications, the sediment gradient and the sediment volume which can be monitored in each wave band of the SAR satellite are smaller than the theoretical values. For high-strength, large gradient deformations, the DInSAR technique is also difficult to qualify, so monitoring large sedimentation gradients with drone data is necessary. According to experience, the root mean square error of unmanned plane data and measured data is approximately 15cm-20cm, the sinking amount reaches meter level, and the unmanned plane is adopted to monitor mining area deformation, so that the accuracy requirement can be basically met, but the accuracy of the sinking edge area is relatively insufficient.
Therefore, the invention combines the unmanned plane and the DINSAR technology to monitor the subsidence deformation of the earth surface, and monitors the center of the mining subsidence area by utilizing the advantages of flexible maneuvering of the unmanned plane, small limit of the terrain and the like; the method can make up the defect of sparse measurement points in the traditional monitoring means by using the DINSAR technology, has the characteristics and advantages of real time and high precision, and can be used for carrying out deformation monitoring on the micro subsidence of the edge of the mining subsidence area. And fusing the deformation monitoring result of the unmanned aerial vehicle with the DINSAR result, and complementing the two data advantages to obtain a more accurate monitoring result. The distribution of the DINSAR monitoring area and the unmanned aerial vehicle monitoring area is shown in fig. 1, wherein 1 is the mining subsidence influence edge of a mining area, 2 is the DINSAR monitoring area boundary, and 3 is the unmanned aerial vehicle monitoring area boundary; it should be noted that the schematic diagram of the monitoring area is only one specific implementation schematic diagram provided by the present invention, and is only used to illustrate the present invention and not to limit the scope of the present invention.
In this embodiment, a coherence threshold for DInSAR monitoring needs to be determined according to SAR satellite parameters, and a region with low coherence is removed to determine a DInSAR monitoring region. The coherence threshold is determined as follows:
D max ＝d max +0.002(γ-1)
wherein D is max Is the maximum deformation gradient detectable by the DINSAR; gamma is the coherence coefficient of the interferogram, ranging between 0 and 1; d, d max For the maximum deformation gradient detectable by theoretical DInSAR, i.e.(lambda is the radar wavelength and mu is the pixel size). D (D) max The method can be preset according to specific implementation scenes to obtain a proper coherence coefficient as a coherence threshold. For example for usingThe image of Sentinel-1A with 20m resolution in the C band can be calculated by the formula, and when the coherence coefficient gamma is smaller than 0.3, the maximum deformation gradient D which can be detected by the DINSAR is calculated max Almost 0. Therefore, to ensure the correctness of the phase unwrapping result, the correlation coefficient 0.3 is used as a screening threshold of the DInSAR monitored value. And extracting the coherence coefficient of each monitoring point, and setting the coherence threshold of the interference pair to be 0.3 in the data processing process so as to obtain a high-coherence interference pattern.
In this embodiment, the specific steps for determining the DInSAR monitoring area are as follows: and processing the two-scene SAR image, and carrying out two-track differential by combining an external DEM (Digital Elevation Model ) to obtain a differential interferogram. And (3) extracting a DInSAR monitoring value of each monitoring point on the working surface by using the function of extracting the value of the Spatial analysis tool to the point in the ArcGIS and processing the differential interference map. And screening the interference diagram obtained in the process of the DINSAR by using the set 0.3 coherence threshold value, opening the coherence diagram by using the ArcGIS to obtain the coherence coefficient of each monitoring point on the working surface, screening the interference diagram by using the set coherence threshold value, and taking the monitoring point which has the coherence less than 0.3 and is closest to the edge of the mining subsidence basin as the limit of the DINSAR monitoring, namely adopting the DINSAR monitoring at other monitoring points, which are close to one side of the edge of the mining subsidence basin, of the monitoring point.
In this embodiment, a monitoring threshold value of unmanned aerial vehicle monitoring needs to be determined according to an unmanned aerial vehicle monitoring value and a corresponding actually measured level value, so as to determine an unmanned aerial vehicle monitoring area. The determination formula of the monitoring threshold T is as follows:
wherein the U is i Unmanned aerial vehicle monitoring value W for ith monitoring point i The measured level value of the ith monitoring point is obtained, and n is the number of monitoring points.
The specific steps for determining the monitoring area of the unmanned aerial vehicle in the embodiment are as follows: and obtaining two-stage DEM data corresponding to the DINSAR interference time by using an unmanned aerial vehicle technology. The two-phase DEM is then subtracted to obtain the subsurface subsidence basin conditions resulting from the mining of the investigation region during the two-phase time period. The unmanned aerial vehicle monitoring values of all monitoring points are extracted, then the monitoring values obtained by the unmanned aerial vehicle are screened by utilizing the monitoring threshold T, the unmanned aerial vehicle monitoring value is selected to be larger than the monitoring threshold T, and the monitoring point farthest away from the center of the subsidence basin is the limit of unmanned aerial vehicle monitoring, namely, other monitoring points close to one side of the center of the subsidence basin at the monitoring point are monitored by adopting the unmanned aerial vehicle.
In this embodiment, data fusion is performed on a mining subsidence edge area obtained by high-precision monitoring of the DInSAR and a mining subsidence center area obtained by high-precision monitoring of the unmanned aerial vehicle, if an unmonitored point exists between the DInSAR monitoring area and the unmanned aerial vehicle monitoring area (i.e., a null value exists between the fused DInSAR monitoring area and the boundary of the unmanned aerial vehicle monitoring area), a reverse distance weighting method is adopted to determine a monitored value of the unmonitored point, which specifically includes the steps of:
according to the distance between the non-monitored point (xi, yi) and the monitored points (xj, yj) around the non-monitored point, the monitored value of the non-monitored point is calculated through the following formula:
wherein i is an unmonitored point, j is a monitored point around the unmonitored point, W i And W is j Respectively representing the monitoring values of the corresponding points, d j The distance between the non-monitored point (xi, yi) and the monitored point (xj, yj) around the non-monitored point (xi, yi) is the distance between the non-monitored point (xi, yi) and the monitored point (xj, yj) around the non-monitored point (xi, yi)
In this embodiment, if there is an overlap between the DInSAR monitoring area and the unmanned aerial vehicle monitoring area, since the monitoring error of the overlapping area is not large, the monitoring value of any monitoring area or the average value of the two monitoring values may be adopted.
In this embodiment, after obtaining the complete subsidence value (i.e., the monitoring value) of each monitoring point, the coordinates of each monitoring point and the corresponding subsidence value may be used to draw a subsidence curve, so that the overall subsidence characteristics of the subsidence basin may be intuitively displayed.
By adopting the technical scheme disclosed by the invention, the following beneficial effects are obtained:
the invention provides a mining subsidence monitoring method combining unmanned aerial vehicle and DINSAR technology, which fuses unmanned aerial vehicle monitoring results of mining subsidence areas with DINSAR differential subsidence results. The method not only utilizes the high precision of unmanned plane data in the center of a subsidence area, but also maintains the superiority of a DINSAR differential result in edge monitoring, and overcomes the shortcomings of the D-InSAR approach in the decoherence of large gradient deformation and the defects of unmanned plane technology in the aspect of edge micro deformation monitoring. And the advantages of the two data are complemented, so that the high-precision monitoring of the mining subsidence area is realized.
The foregoing is merely a preferred embodiment of the present invention and it should be noted that modifications and adaptations to those skilled in the art may be made without departing from the principles of the present invention, which is also intended to be covered by the present invention.
Claims (2)
1. A mining subsidence monitoring method combining unmanned aerial vehicle and DInSAR technologies, the method comprising:
the method comprises the steps of monitoring an edge area of mining subsidence through a DINSAR, determining a coherence threshold of the DINSAR monitoring according to SAR satellite parameters, and taking a monitoring point which is smaller than the coherence threshold and closest to a mining subsidence center as a boundary of the DINSAR monitoring area;
determining a coherence threshold of the DINSAR monitoring according to SAR satellite parameters, wherein the coherence threshold comprises the following specific steps:
obtaining a theoretical maximum deformation gradient d which can be detected by the DINSAR according to the radar wavelength and the pixel size of the SAR satellite max The saidThe lambda is the radar wavelength, and the mu is the pixel size;
maximum deformation gradient D detectable according to preset DINSAR max And said d max Determining a coherence coefficient, said D max ＝d max +0.002 (γ -1), the γ being the coherence coefficient;
taking the obtained coherence coefficient as a coherence threshold for screening the DINSAR monitoring value;
the method comprises the steps of monitoring a mining subsidence central area through an unmanned aerial vehicle, determining a monitoring threshold value of unmanned aerial vehicle monitoring according to an unmanned aerial vehicle monitoring value and a corresponding actually measured level value, and taking a monitoring point which is larger than the monitoring threshold value and farthest away from the mining subsidence center as a boundary of the unmanned aerial vehicle monitoring area;
determining a monitoring threshold value of unmanned aerial vehicle monitoring according to the unmanned aerial vehicle monitoring value and the corresponding actually measured level value, specifically:
according to the formulaAcquiring a monitoring threshold T;
wherein the U is i Unmanned aerial vehicle monitoring value W for ith monitoring point i The measured level value of the ith monitoring point is obtained, and n is the number of monitoring points;
and acquiring high-precision surface deformation information of mining subsidence according to the coordinates of each monitoring point and the corresponding monitoring value of the DINSAR monitoring area and the unmanned aerial vehicle monitoring area.
2. The mining subsidence monitoring method combining the unmanned aerial vehicle and the DInSAR technology according to claim 1, wherein if an unmonitored point exists between the DInSAR monitoring area and the unmanned aerial vehicle monitoring area, determining a monitoring value of the unmonitored point by adopting an inverse distance weighting method, specifically:
according to the distance between the non-monitored point and the monitored points around the non-monitored point, the method passes through the formulaCalculating a monitoring value of an unmonitored point;
wherein i is an unmonitored point, j is a monitored point around the unmonitored point, W i And W is j Respectively representing the monitoring values of the corresponding points, d j Is the distance between the non-monitored point and the monitored points around it.
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