CN105866791B - The method that the vehicle-mounted LiDAR point cloud data precision of net raising is controlled using target - Google Patents
The method that the vehicle-mounted LiDAR point cloud data precision of net raising is controlled using target Download PDFInfo
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- 238000012423 maintenance Methods 0.000 claims description 7
- 238000004364 calculation method Methods 0.000 claims description 4
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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
- G01S17/00—Systems using the reflection or reradiation of electromagnetic waves other than radio waves, e.g. lidar systems
- G01S17/88—Lidar systems specially adapted for specific applications
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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
- G01S7/00—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00
- G01S7/48—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S17/00
- G01S7/481—Constructional features, e.g. arrangements of optical elements
- G01S7/4817—Constructional features, e.g. arrangements of optical elements relating to scanning
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Abstract
The present invention relates to a kind of methods for net being controlled to improve vehicle-mounted LiDAR point cloud data precision using target.The required precision that the error for using vehicle-mounted LiDAR systems generate in rail track measurement process causes LiDAR point cloud data to be unsatisfactory for route survey needs to be constrained using the measurement error of target dominating pair of vertices in-vehicle LiDAR data, eliminates error and improves precision.The present invention determines the installation position and installation method at target control point first, and Basic Control Networks is relied on to complete the measurement and compensating computation of target control net；According to the size of the influence factor selection target box body of scanning dot density, it is ensured that extract the accuracy of target control point coordinates from point cloud data；Two sets of coordinate pair point cloud datas based on target control point carry out segmentation constraint adjustment, realize a raising for cloud precision.The present invention eliminates measurement error using the target point in target control net, solves the problems, such as that measurement error causes vehicle-mounted LiDAR point cloud loss of significance.
Description
Technical field
The invention belongs to railway construction technical field of mapping, and in particular to a kind of target for existing railway circuit repetition measurement
Establishment of control net method.
Background technology
With greatly improving for the general fast railway operation speed in China and frequency, the requirement to railway operation safety is also increasingly
Height, therefore also gradually increased with the demand of railway in operation maintenance that railway operation maintenance is measured as foundation.It is vehicle-mounted three-dimensional sharp
Optical radar（LiDAR）Scanning system has been concerned as a kind of advanced data acquisition means, data can it is more intuitive,
Quickly show and analyze rail track situation, to improve measurement efficiency play the role of it is critical, be railway operation safeguard survey
The advanced effective means of one kind of amount.
However vehicle-mounted LiDAR scanning systems are a complicated integrated systems, the data precision of scanning is by each in system
The joint effect of a component, error source are mainly the error and hardware integration error generated in measurement process, including：Positioning misses
Difference, laser ranging error, angle error, placement angle error, IMU drift errors and system integration error, data processing error etc..
These errors largely affect the precision of scan data, in order to obtain the point cloud data of higher precision, need using control
Target control point constraint measurement error in system net improves the precision of vehicle-mounted LiDAR point cloud data.
Since the point cloud data that LiDAR measuring methods obtain cannot establish accurate correspondence with known point, make
The correspondence of point cloud and known point is established with target control point.Target control point is defined as the intersection point of three target planes, from
Accurate target control point is extracted in point cloud, correspondence is established with the target control point actually measured, passes through target control point
Two sets of coordinates establish error equation carry out constraint adjustment improve point a cloud precision, come obtain meet operation maintenance measurement accuracy requirement
Point cloud data.
Invention content
The object of the present invention is to provide a kind of method for net being controlled to improve vehicle-mounted LiDAR point cloud data precision using target,
Available for the operating line repetition measurement for railway of growing up, high-precision data basis is provided for repetition survey of existing rail way.
The technical solution adopted in the present invention is：
1st, the method that the vehicle-mounted LiDAR point cloud data precision of net raising is controlled using target, it is characterised in that：
It is realized by following steps：
Step 1：Determine the installation position at target control point and the installation method of target apparatus：
The uniformly distributed target control point in downline road both sides, and in POS calculation accuracies difference or GPS signal area easy to be lost
Target control point is added at the characteristic point of domain and rail track；Target box body is connect by connecting bolt and target measurement built-in fitting
And be fixed, target anchor point is provided on box body, target anchor point is always towards the direction of train driving when disposing box body；
Step 2：The size dimension of target apparatus is selected according to field working conditions：
Target apparatus is included there are three scanning plane, i.e. target top surface, face driving face and face of vertically driving a vehicle, three face intersection points are
Target anchor point.According to the influence factor of scanning dot density, the spacing of scanning element in target face is calculated；To ensure target anchor point
Extraction accuracy, different size of target is selected according to working environment, it is ensured that obtain at least three in three scanning target faces and sweep
Retouch line number evidence；
Step 3：Complete the measurement and compensating computation at target control point：
The testing and adjustment for completing target control net resolve, and provide and meet the control net achievement that subsequent data analysis uses；
Step 4：Segmentation constraint adjustment is carried out to point cloud data, improves the overall precision of point cloud：
Point coordinates is controlled using the accurate target of field operation actual measurement, segmentation constraint adjustment is carried out to original point cloud data, is led to
It crosses compensating computation and obtains the point cloud data of higher precision.
In step 1, target apparatus is target box body, is rigid polyhedron of the tool there are four face, drives a vehicle including the vertical back of the body
Vertical face driving face and face of vertically driving a vehicle below the target top surface and target top surface that face, back of the body driving face one are sloped downwardly；
Target top surface, face driving face and vertical driving face intersect at a point, which is target anchor point；
When carrying out vehicle-mounted LiDAR line scannings, target box body connect and goes forward side by side by connecting bolt and target measurement built-in fitting
Row is fixed, and target anchor point is always towards the direction of train driving；Vertical driving face is perpendicular to This train is bound for XXX, face driving face
With This train is bound for XXX be in 30 ° of angles；When This train is bound for XXX it is opposite when, target apparatus is rotated to opposite direction, vertical to drive a vehicle
Face knead dough driving face swaps, and former face driving face, which is rotated to vertically This train is bound for XXX, becomes new vertical driving face, and original is hung down
Straight traffic face rotate to This train is bound for XXX in 30 ° of angles direction, drive a vehicle face as new face.
In step 2, the influence factor for scanning dot density includes scanner measurement rate, scan frequency, train driving speed
Degree, distance of the target away from scanner, target are less than 30-70km/h with a distance from rail less than 5 meters, train running speed.
In step 4, the segmentation constraint adjustment for putting cloud is realized by following steps：
Obtain the three-dimensional coordinate information of two sets of target anchor points of scanning survey data and field operation measured data, target positioning
Point design is to obtain the vertex that three target faces of scanning element intersect；Each target scanning plane is considered smooth in three dimensions
Two dimensional surface, according to three dimensions plane equation, the point cloud data on three scanning planes is fitted respectively, is obtained three
The intersection point of fit Plane, the three-dimensional coordinate of the point are the coordinate of target anchor point；
It is carried using the actual measurement target positioning point coordinates obtained after measurement in step 3 and compensating computation and from point cloud data
The target positioning point coordinates of taking-up is segmented point cloud data by scan data precision as the characteristic point between two sets of coordinates,
Ensure to be overlapped more than one pair of target data between two adjacent sectionals, segmentation constraint is carried out using target dominating pair of vertices point cloud data
Adjustment obtains the point cloud data for meeting the requirement of rail track operation maintenance measurement accuracy, realizes the raising of point cloud data precision.
The present invention has the following advantages：
The present invention is directed to long and narrow band-like rail track, it is proposed that according to point of Along Railway landform, tunnel and high cutting
The method that cloth situation establishes target control net, ensure that the progress of a cloud precision controlling；
Novelty of the invention proposes the method that vehicle-mounted Point Cloud Data from Three Dimension Laser Scanning precision is improved using target, solution
It has determined and using vehicle-mounted LiDAR technologies in rail track operation maintenance measurement process ensure the critical issue of measurement accuracy, very
The defects of vehicle-mounted LiDAR equipment causes a cloud loss of significance is overcome in big degree, the purpose for improving point cloud precision is realized, makes
The measuring method can be used for railway operation and safeguard in measurement.
Description of the drawings
Fig. 1 is the layout diagram of target control net；
Fig. 2 is the installation method of measurement target drone during line scanning.
Fig. 3 is target apparatus front view.
Fig. 4 is target apparatus side view.
Fig. 5 is target apparatus vertical view.
In figure, 1- target box bodys, 2- back ofs the body driving face, 3- targets top surface, 4- faces driving face, 5- vertically drives a vehicle face, 6- targets
Anchor point.
Specific embodiment
The present invention will be described in detail With reference to embodiment.
The method of the present invention for net being controlled to improve vehicle-mounted LiDAR point cloud data precision using target, it is special to relate to
Target apparatus structure, target apparatus is target box body, is rigid polyhedron of the tool there are four face, drives a vehicle including the vertical back of the body
Vertical face driving face and face of vertically driving a vehicle below the target top surface and target top surface that face, back of the body driving face one are sloped downwardly；
Target anchor point is designed as the intersection point of target top surface, face driving face and vertical driving face.According to field working conditions during use, mark is determined
Size, installation position and the placement direction of target.
The above method is realized by following steps：
Step 1：Determine the installation position at target control point and the installation method of target apparatus：
Since railway is existing line, inertial navigation system can not can only alternately be turned on railway by acceleration and deceleration by left and right
Capable convergence is bent into, therefore the drift for starting inertial navigation measuring unit IMU after measuring can not be eliminated, with the growth of time of measuring, be used to
Lead drift gradually increase.Therefore to eliminate inertial navigation system error and GPS measurement errors, determine that the installation position at target control point should
It lays on downline road.
In addition, with the modernization and automation of railway operation, inbuilt electronics, electromagnetic equipment are more and more on railway,
These can interfere the normal work of IMU, once IMU operatings are not normal, POS calculation accuracies can be caused to substantially reduce；Meanwhile to obtain
Highdensity point cloud data on railway is taken, vehicle-mounted scanning device is generally 2.5-4.0m in the mounting height of last vehicle of train, such as
In high cutting, tunnel, the regions such as railway side massif is steep, easily blocked by surrounding higher building body, vehicle-mounted LiDAR systems occur and receive
Less than the situation of GPS signal.Therefore in POS calculation accuracies difference or GPS signal region easy to be lost, target control point should be laid.
Referring to Fig. 1, according to Along Railway tunnel, bridge, embankment, cutting and along the line on the basis of ground base station control net
High mountain cliff, vegetation to the circumstance of occlusion of satellite-signal, target control net is laid in downline both sides.
Target control point should be set to according to Along Railway features of terrain along roadbed, bridge, tunnel, high cutting and steep
Near high mountain.Generally in the strong location of unobscured, railway smooth-going, GPS signal, target can be laid diluter, general spacing
For 1km or so, it is laid in as possible at curvilinear characteristic point or at knick point.In alpine region, tunnel group etc. easily causes GPS signal losing lock
Area, according to length of tunnel, train speed calculate GPS signal losing lock time.When time of losing lock be less than 2 minutes when POS
Data precision loss is little, can add target in tunnel entrance, outlet.When GPS time of losing lock is more than 4 minutes, need to suitably increase
Add the layout density of target, particularly curve, hyperbola location, the trend of controlling curve is wanted in the laying of target, should be laid in as：
Point of tangent to spiral, point of spiral to curve, curve intermediate point, point of curve to spiral, point of spiral to tangent, the gradient are risen at the characteristic points such as close point.
Such as Fig. 2, target box body is by connecting bolt and target measures built-in fitting and connect and consolidated during line scanning
Fixed, target anchor point installation direction should change with the difference that This train is bound for XXX.Target anchor point should court in scanning process
To the direction of train driving, while the vertical driving face of target need to be perpendicular to This train is bound for XXX, face driving face and train driving
Direction is in 30 ° of angles.When This train is bound for XXX it is opposite when, target box body should be rotated to opposite direction, vertical face knead dough row of driving a vehicle
Vehicle face swaps, and former face driving face, which is rotated to vertically This train is bound for XXX, becomes new vertical driving face, former vertical face of driving a vehicle
Rotation to This train is bound for XXX in 30 ° of angles direction, drive a vehicle face as new face.
Step 2：The size dimension of target is selected according to field working conditions：
The target control point of laying is for carrying out a cloud accuracy constraint, therefore it is required that target control point is with very high
Extraction accuracy.Scanning element more at most positioning accuracy on three scanning planes of target is higher, and the extraction accuracy of target is also higher.
Scanning dot density on target is influenced by Multiple factors：Scanner measurement rate is higher, scan frequency is higher, sweeps
It is bigger to retouch density；Train running speed is lower, target is nearer away from scanner distance, and scanning density is bigger, then is obtained in target face
Point cloud quantity it is more.
Due to determine a target face in cloud, three scan line cloud datas are at least needed on the face, therefore survey
Amount needs, according to above-mentioned rule, to calculate the scanning element spacing on target before starting, so as to select various sizes of target box body, to protect
Demonstrate,prove the point quantity that target face obtains.
Step 3：Complete the measurement and compensating computation at target control point：
The testing and adjustment for completing target control net resolve, and provide and meet the control net achievement that subsequent data analysis uses；
Step 4：Segmentation constraint adjustment is carried out to point cloud data：
The purpose that accuracy constraint is carried out to cloud is exactly to control point coordinates using the accurate target of field operation actual measurement, to original
Point cloud carries out segmentation constraint adjustment, obtains the point cloud data of higher precision.Therefore, carrying out a cloud constraint needs to obtain scanning survey
The three-dimensional coordinate information of two sets of target anchor points of data and field operation measured data, the target anchor point are designed as obtaining scanning element
The vertex that three target faces intersect.Each target face is considered as two dimensional surface smooth in three dimensions, according to three dimensions
Plane equation is respectively fitted the point cloud data on three faces, and the intersection point of three fit Planes is obtained, the three-dimensional of the point
Coordinate is the coordinate of target anchor point.
It is carried using the actual measurement target positioning point coordinates obtained after measurement in step 3 and compensating computation and from point cloud data
The target positioning point coordinates of taking-up, is segmented original point cloud data by scan data precision, ensures between two adjacent sectionals
More than one pair of target point is overlapped, segmentation constraint adjustment is carried out using the point-to-point cloud data of target, so as to fulfill point cloud data essence
The raising of degree achievees the purpose that meet the requirement of rail track operation maintenance measurement accuracy.
Present disclosure is not limited to cited by embodiment, and those of ordinary skill in the art are by reading description of the invention
And to any equivalent transformation that technical solution of the present invention is taken, it is that claim of the invention is covered.
Claims (4)
1. the method that vehicle-mounted LiDAR point cloud data precision is improved using target control net, it is characterised in that：
It is realized by following steps：
Step 1：Determine the installation position at target control point and the installation method of target apparatus：
The uniformly distributed target control point in downline road both sides, and in POS calculation accuracies difference or GPS signal region easy to be lost and
Target control point is added at the characteristic point of rail track；Target box body connect and goes forward side by side by connecting bolt and target measurement built-in fitting
Row is fixed, and target anchor point is provided on box body, and target anchor point is always towards the direction of train driving when disposing box body；
Step 2：The size dimension of target apparatus is selected according to field working conditions：
Target apparatus is included there are three scanning plane, i.e. target top surface, face driving face and face of vertically driving a vehicle, and three face intersection points are target
Anchor point；According to the influence factor of scanning dot density, the spacing of scanning element in target face is calculated；To ensure carrying for target anchor point
Precision is taken, different size of target is selected according to working environment, it is ensured that obtains at least three scan lines in three scanning target faces
Data；
Step 3：Complete the measurement and compensating computation at target control point：
The testing and adjustment for completing target control net resolve, and rotating detection process obtains actual measurement target positioning point coordinates, and adjustment resolving obtains
The target positioning point coordinates in point cloud data is obtained, provides and meets the control net achievement that subsequent data analysis uses；
Step 4：Segmentation constraint adjustment is carried out to point cloud data, improves the overall precision of point cloud：
Point coordinates is controlled using the accurate target of field operation actual measurement, segmentation constraint adjustment is carried out to original point cloud data, by flat
The point cloud data of higher precision is calculated in difference.
2. the method according to claim 1 for net being controlled to improve vehicle-mounted LiDAR point cloud data precision using target, feature
It is：
In step 1, target apparatus is target box body, is rigid polyhedron of the tool there are four face, including vertical back of the body driving face,
Vertical face driving face and face of vertically driving a vehicle below the target top surface and target top surface that back of the body driving face one is sloped downwardly；Target
Mark top surface, face driving face and vertical driving face intersect at a point, which is target anchor point；
When carrying out vehicle-mounted LiDAR line scannings, target box body measures built-in fitting by connecting bolt and target and connect and consolidated
Fixed, target anchor point is always towards the direction of train driving；Vertical driving face is perpendicular to This train is bound for XXX, face driving face and row
Vehicle travel direction is in 30 ° of angles；When This train is bound for XXX it is opposite when, target apparatus is rotated to opposite direction, it is vertical drive a vehicle face and
Face driving face swaps, and former face driving face, which is rotated to vertically This train is bound for XXX, becomes new vertical driving face, former vertical row
Vehicle face rotate to This train is bound for XXX in 30 ° of angles direction, drive a vehicle face as new face.
3. the method according to claim 1 for net being controlled to improve vehicle-mounted LiDAR point cloud data precision using target, feature
It is：
In step 2, the influence factor for scanning dot density includes scanner measurement rate, scan frequency, train running speed, target
The distance of gauge length scanner, target are less than 30-70km/h with a distance from rail less than 5 meters, train running speed.
4. the method according to claim 1 for net being controlled to improve vehicle-mounted LiDAR point cloud data precision using target, feature
It is：
In step 4, the segmentation constraint adjustment for putting cloud is realized by following steps：
The three-dimensional coordinate information of two sets of target anchor points of scanning survey data and field operation measured data is obtained, which sets
It is calculated as obtaining the vertex that three target faces of scanning element intersect；Each target scanning plane is considered as smooth two in three dimensions
Dimensional plane according to three dimensions plane equation, is respectively fitted the point cloud data on three scanning planes, and three fittings are obtained
The intersection point of plane, the three-dimensional coordinate of the point are the coordinate of target anchor point；
It the actual measurement target positioning point coordinates obtained using step 3 testing and is extracted from point cloud data after compensating computation
Target positions point coordinates as the characteristic point between two sets of coordinates, point cloud data is segmented by scan data precision, two is adjacent
Ensure to be overlapped more than one pair of target data between segmentation, segmentation constraint adjustment carried out using target dominating pair of vertices point cloud data,
The point cloud data for meeting the requirement of rail track operation maintenance measurement accuracy is obtained, realizes the raising of point cloud data precision.
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| CN107792115B (en) * | 2017-09-07 | 2019-01-04 | 中铁二院工程集团有限责任公司 | It is a kind of to automatically extract both wired rail crest level methods using three-dimensional laser point cloud |
| CN109613555B (en) * | 2018-11-09 | 2022-12-02 | 广西壮族自治区遥感信息测绘院 | Method for arranging sea-land integrated calibration yard for verifying double-frequency LiDAR (light detection and ranging) detector |
| CN111896938A (en) * | 2019-05-06 | 2020-11-06 | 山东鲁邦地理信息工程有限公司 | Vehicle-mounted laser radar scanning target laying and measuring method |
| CN111007530B (en) * | 2019-12-16 | 2022-08-12 | 武汉汉宁轨道交通技术有限公司 | Laser point cloud data processing method, device and system |
| TWI805007B (en) * | 2021-04-07 | 2023-06-11 | 湛積股份有限公司 | Trajectory reducing method and device |
| CN116859410B (en) * | 2023-06-08 | 2024-04-19 | 中铁第四勘察设计院集团有限公司 | Method for improving laser radar measurement accuracy of unmanned aerial vehicle on existing railway line |
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| AT514502B1 (en) * | 2013-07-10 | 2015-04-15 | Plasser & Theurer Export Von Bahnbaumaschinen Gmbh | Method for determining a track target position |
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| CN101913368A (en) * | 2010-08-11 | 2010-12-15 | 唐粮 | System and method for fast precise measurement and total factor data acquisition of high speed railway |
| CN103744086A (en) * | 2013-12-23 | 2014-04-23 | 北京建筑大学 | High-precision registration method for ground laser radar and close-range photography measurement data |
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