CN109141431A - Air strips matching process, device, electronic equipment and readable storage medium storing program for executing - Google Patents
Air strips matching process, device, electronic equipment and readable storage medium storing program for executing Download PDFInfo
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- CN109141431A CN109141431A CN201811049171.8A CN201811049171A CN109141431A CN 109141431 A CN109141431 A CN 109141431A CN 201811049171 A CN201811049171 A CN 201811049171A CN 109141431 A CN109141431 A CN 109141431A
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
- G01C21/00—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00
- G01C21/20—Instruments for performing navigational calculations
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
- G01C21/00—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00
- G01C21/10—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 by using measurements of speed or acceleration
- G01C21/12—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 by using measurements of speed or acceleration executed aboard the object being navigated; Dead reckoning
- G01C21/16—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 by using measurements of speed or acceleration executed aboard the object being navigated; Dead reckoning by integrating acceleration or speed, i.e. inertial navigation
- G01C21/165—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 by using measurements of speed or acceleration executed aboard the object being navigated; Dead reckoning by integrating acceleration or speed, i.e. inertial navigation combined with non-inertial navigation instruments
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
- G01C25/00—Manufacturing, calibrating, cleaning, or repairing instruments or devices referred to in the other groups of this subclass
Abstract
The present invention provides a kind of air strips matching process, device, electronic equipment and readable storage medium storing program for executing, it is related to the technical field of lidar measurement, including obtaining and loading point cloud data and track documents corresponding with point cloud data, the point cloud data of every air strips is obtained from polygonal region course line by track documents；The overlapping region for identifying every air strips, the selected characteristic point from the overlapping region point cloud data of adjacent air strips, and Feature Points Matching is formed into reference point pair；By pre-set error model and least square method, correction angle and minimum space distance value is calculated；The spatial position of point cloud data is modified according to minimum space distance value and correction angle, so that the spatial position of adjacent air strips matches, the embodiment of the present invention can estimate air strips match parameter automatically, improve air strips matching efficiency, the lap of different air strips is connected, realizes the splicing of different air strips data.
Description
Technical field
The present invention relates to lidar measurement technical fields, set more particularly, to a kind of air strips matching process, device, electronics
Standby and readable storage medium storing program for executing.
Background technique
Airborne laser radar measuring system is integrated with global position system GPS, inertial navigation system INS, laser radar and sweeps
Multiple components such as instrument are retouched, will receive the influence of a variety of error sources (systematic error and random error) in application process, specifically
It is presented as, when inertial navigation system INS attitude determination, during lidar measurement system is installed, does not ensure that sharp
It is parallel to each other between optical scanning reference frame and the reference axis of inertial platform reference frame, at this point, can generation system placement
Error.So the coordinate and elevation of the same point that difference air strips measure when multi-stripe laser scan stripes band covers same scanning area
It each other can be variant.
Artificial measurement calibration needs relevant professional knowledge and the skilled operation to software, and calculating automatically greatly to subtract
The workload of light work person.In the apparent data of feature, automatic calculate is fully able to substitution manual calculation, reach it is identical even
Higher precision.
Summary of the invention
In view of this, the purpose of the present invention is to provide air strips matching process, device, electronic equipment and readable storage mediums
Matter, it is automatic to estimate air strips match parameter, air strips matching efficiency is improved, the lap of different air strips is connected, is realized not
With the splicing of air strips data.
In a first aspect, the embodiment of the invention provides a kind of air strips matching process, comprising:
Obtain and load point cloud data and track documents corresponding with the point cloud data, by the track documents from
The point cloud data of every air strips is obtained in polygonal region course line；
The overlapping region for identifying every air strips, the selected characteristic from the overlapping region point cloud data of adjacent air strips
Point, and the Feature Points Matching is formed into reference point pair；
By pre-set error model and least square method, correction angle and minimum space distance value is calculated,
In, it is chosen from each reference point centering, the minimum space distance value between the characteristic point；
The spatial position of the point cloud data is modified according to the minimum space distance value and correction angle, so that institute
The spatial position for stating adjacent air strips matches.
With reference to first aspect, the embodiment of the invention provides the first possible embodiments of first aspect, wherein institute
The overlapping region for identifying every air strips is stated, the selected characteristic point from the overlapping region point cloud data of adjacent air strips, and
The Feature Points Matching is formed into reference point to including:
Grid processing is carried out to the point cloud data of every air strips, judges whether be stored with described cloud number in grid
According to identifying whether the grid is overlapping region；
Point cloud data in the overlapping region of adjacent air strips is subjected to matrix calculating, the first numerical value is obtained, according to institute
State the first numerical value selected characteristic point from the point cloud data；
Neighborhood is chosen to each characteristic point, obtains the plane normal direction of each characteristic point and each neighborhood
Amount, chooses that the planar process vector direction is identical and shortest two characteristic points of space length of the characteristic point, as
One reference point pair.
With reference to first aspect, the embodiment of the invention provides second of possible embodiments of first aspect, wherein one
A point cloud data is a three-dimensional coordinate, and the point cloud data in the overlapping region by adjacent air strips carries out matrix
It calculates, obtains the first numerical value, selected characteristic point includes: from the point cloud data according to first numerical value
Covariance matrix is calculated by the point cloud data in the overlapping region, wherein each point cloud data conduct
A row matrix in the covariance matrix；
Each row matrix of the covariance matrix is calculated, is calculated corresponding with each row matrix
One numerical value；
The smallest first numerical value is searched from each first numerical value, it will be opposite with the smallest first numerical value
The row matrix answered is deleted from the covariance matrix, until the number of the remaining row matrix reaches default
Number, using the corresponding point cloud data of the remaining row matrix as characteristic point.
With reference to first aspect, the embodiment of the invention provides the third possible embodiments of first aspect, wherein institute
It states through pre-set error model and least square method, correction angle is calculated and minimum space distance value includes:
By pre-set error model, the space length value between each reference point centering feature point is obtained；
Minimum space distance value and the angle of roll is calculated by least square method, three pitch angle, course angle angles are repaired
Positive value.
With reference to first aspect, the embodiment of the invention provides the 4th kind of possible embodiments of first aspect, wherein institute
It states acquisition and loads point cloud data and track documents corresponding with the point cloud data, by the track documents from polygon
The point cloud data that every air strips are obtained in the course line of region includes:
Point cloud data and track documents corresponding with the point cloud data are obtained and loaded, polygonal region boat is obtained
Line, the track documents include GPS time；
The point cloud data is cut according to the GPS time of air strips start-stop, is obtained from the polygonal region course line
The point cloud data of every air strips.
With reference to first aspect, the embodiment of the invention provides the 5th kind of possible embodiments of first aspect, wherein institute
It states acquisition and loads point cloud data and track documents corresponding with the point cloud data, obtaining polygonal region course line includes:
Initial data is pre-processed, point cloud data and track documents corresponding with the point cloud data are obtained；
The point cloud data and the track documents are loaded, polygonal region course line is obtained.
With reference to first aspect, the embodiment of the invention provides the 6th kind of possible embodiments of first aspect, wherein institute
Stating correction angle includes angle of roll correction value, pitch angle correction value and course angle correction value.
Second aspect, the embodiment of the present invention also provide a kind of air strips coalignment, are applied to electronic equipment, described device packet
It includes:
Module is obtained, point cloud data and track documents corresponding with the point cloud data are obtained and load, by described
Track documents obtain the point cloud data of every air strips from polygonal region course line；
Matching module identifies the overlapping region of every air strips, the overlapping region point cloud data from adjacent air strips
Middle selected characteristic point, and the Feature Points Matching is formed into reference point pair；
Correction angle and minimum space is calculated by pre-set error model and least square method in computing module
Distance value, wherein chosen from each reference point centering, the minimum space distance value between the characteristic point；
Correction module repairs the spatial position of the point cloud data according to the minimum space distance value and correction angle
Just, so that the spatial position of the adjacent air strips matches.
The third aspect, the embodiment of the present invention also provide a kind of electronic equipment, and the electronic equipment includes:
Storage medium；
Processor；And
Air strips coalignment, described device are stored in the storage medium, and soft including being executed by the processor
Part functional module, described device include:
Module is obtained, point cloud data and track documents corresponding with the point cloud data are obtained and load, by described
Track documents obtain the point cloud data of every air strips from polygonal region course line；
Matching module identifies the overlapping region of every air strips, the overlapping region point cloud data from adjacent air strips
Middle selected characteristic point, and the Feature Points Matching is formed into reference point pair；
Correction angle and minimum space is calculated by pre-set error model and least square method in computing module
Distance value, wherein chosen from each reference point centering, the minimum space distance value between the characteristic point；
Correction module repairs the spatial position of the point cloud data according to the minimum space distance value and correction angle
Just, so that the spatial position of the adjacent air strips matches.
The third aspect, the embodiment of the present invention also provide a kind of readable storage medium storing program for executing, are stored in the readable storage medium storing program for executing
Computer program, the computer program, which is performed, realizes air strips matching process as described above.
The embodiment of the invention provides a kind of air strips matching process, device, electronic equipment and readable storage medium storing program for executing, including area
The point cloud data for separating single air strips, the selected characteristic point from the point cloud data of the overlapping region of adjacent air strips, then by characteristic point
It carries out matching and forms reference point pair, correction angle and reference point centering feature point are calculated by error model and least square method
Between minimum space distance value, and the spatial position of point cloud data is modified according to minimum space distance value and correction angle,
So that the spatial position of adjacent air strips matches, the point cloud data in Different Plane is set to fit together, the embodiment of the present invention
Air strips match parameter can be estimated automatically, air strips matching efficiency is improved, the lap of different air strips is connected, and realized not
With the splicing of air strips data.
Other features and advantages of the present invention will illustrate in the following description, also, partly become from specification
It obtains it is clear that understand through the implementation of the invention.The objectives and other advantages of the invention are in specification, claims
And specifically noted structure is achieved and obtained in attached drawing.
To enable the above objects, features and advantages of the present invention to be clearer and more comprehensible, preferred embodiment is cited below particularly, and cooperate
Appended attached drawing, is described in detail below.
Detailed description of the invention
It, below will be to specific in order to illustrate more clearly of the specific embodiment of the invention or technical solution in the prior art
Embodiment or attached drawing needed to be used in the description of the prior art be briefly described, it should be apparent that, it is described below
Attached drawing is some embodiments of the present invention, for those of ordinary skill in the art, before not making the creative labor
It puts, is also possible to obtain other drawings based on these drawings.
Fig. 1 is matching process flow chart in air strips provided in an embodiment of the present invention；
Fig. 2 is that the box of the electronic equipment provided in an embodiment of the present invention for realizing above-mentioned air strips matching process is illustrated
Figure.
Icon: 100- electronic equipment；110- storage medium；120- processor；The air strips 200- coalignment；210- obtains mould
Block；220- matching module；230- computing module；240- correction module.
Specific embodiment
In order to make the object, technical scheme and advantages of the embodiment of the invention clearer, below in conjunction with attached drawing to the present invention
Technical solution be clearly and completely described, it is clear that described embodiments are some of the embodiments of the present invention, rather than
Whole embodiments.Based on the embodiments of the present invention, those of ordinary skill in the art are not making creative work premise
Under every other embodiment obtained, shall fall within the protection scope of the present invention.
Currently, when inertial navigation system INS attitude determination, it, can not during lidar measurement system is installed
Guarantee to be parallel to each other between laser scanning reference frame and the reference axis of inertial platform reference frame, at this point, can generate and be
System installation error.So the coordinate for the same point that difference air strips measure when multi-stripe laser scan stripes band covers same scanning area
It each other can be variant with elevation.Artificial measurement calibration needs relevant professional knowledge and the skilled operation to software, and counts automatically
Calculate the workload that can greatly mitigate operator.In the apparent data of feature, automatic calculate is fully able to substitution manual calculation,
Reach identical even higher precision.
Based on this, a kind of air strips matching process, device, electronic equipment and readable storage medium provided in an embodiment of the present invention
Matter can estimate air strips match parameter automatically, improve air strips matching efficiency, the lap of different air strips is connected, real
The splicing of existing different air strips data.
For convenient for understanding the present embodiment, first to a kind of air strips matching process disclosed in the embodiment of the present invention into
Row is discussed in detail；
Fig. 1 is matching process flow chart in air strips provided in an embodiment of the present invention.
Referring to Fig.1, air strips matching process the following steps are included:
Step S110 obtains and loads point cloud data and track documents corresponding with point cloud data, passes through track documents
The point cloud data of every air strips is obtained from polygonal region course line；
Step S120 identifies the overlapping region of every air strips, chooses from the overlapping region point cloud data of adjacent air strips special
Point is levied, and Feature Points Matching is formed into reference point pair；
Correction angle and minimum space is calculated by pre-set error model and least square method in step S130
Distance value, wherein chosen from each reference point centering, the minimum space distance value between characteristic point；
Step S140 is modified the spatial position of point cloud data according to minimum space distance value and correction angle, so that
The spatial position of adjacent air strips matches；
Specifically, the point cloud data for distinguishing single air strips is chosen from the point cloud data of the overlapping region of adjacent air strips
Characteristic point, then characteristic point is subjected to matching and forms reference point pair, correction angle is calculated by error model and least square method
Minimum space distance value between reference point centering feature point, and according to minimum space distance value and correction angle to point cloud data
Spatial position is modified, so that the spatial position of adjacent air strips matches, is fitted in the point cloud data in Different Plane
Together, the embodiment of the present invention can estimate air strips match parameter automatically, air strips matching efficiency be improved, by the overlapping portion of different air strips
Divide and connect, realizes the splicing of different air strips data；
Wherein, the embodiment of the present invention is applied to the apparent Point Cloud Data of feature, and effect is more significant, passes through automatic
With calculating, reaches and manually calculate identical even higher precision, improve waterway design efficiency, operating personnel is wanted in reduction
It asks；
Further, for the selected characteristic point from the overlapping region of adjacent air strips, step S120 is further comprising the steps of:
Step S210 carries out grid processing to the point cloud data of every air strips, judges whether stored a cloud in grid
Data, whether identification grid is overlapping region；
Here, for example, if having point cloud data in the grid that the 2nd row 3 of the air strips A arranges, the 2nd row 3 of the B air strips adjacent with A
Also there is point cloud data in the grid of column, then overlapping region includes the unit grids of the 2nd row 3 column；
Wherein, overlapping region is multiple unit grids for being stored with point cloud data；
Point cloud data in the overlapping region of adjacent air strips is carried out matrix calculating, obtains the first numerical value, root by step S220
According to the first numerical value from point cloud data selected characteristic point；
It should be noted that a point cloud data is a three-dimensional coordinate, including tri- axis of XYZ, step S220 also can be used to
Lower step is realized:
Step S310 calculates covariance matrix by the point cloud data in overlapping region, wherein each point cloud data is made
For a row matrix in covariance matrix；
Here, the point cloud data in overlapping region is multiple, and the number of point cloud data determines the line number of covariance matrix；
Specifically, point cloud data integrates as P={ p1,p2,p3,…,pn, respective normal direction is obtained according to each point cloud data
Amount, normal direction duration set are N={ n1,n2,n3,…,nn, and initialize one storage vector characteristics point ID number I=1,2,
3 ..., n }, ID number is corresponding with its normal vector with each point cloud data respectively, i.e. ID number 1, corresponding point cloud data P1, normal vector n1
With the first row matrix of covariance matrix；
At this point, calculating covariance matrix A according to all point cloud datas；
Step S320 calculates each row matrix of covariance matrix, is calculated corresponding with each row matrix
First numerical value；
Specifically, each row matrix of covariance matrix will be calculated according to following formula:
hii=aiQai T (1≤i≤n)
Wherein, Q=(ATA)-1, i is line number, aiFor the row matrix of the i-th row, h is the first numerical value, hiiIt is the first of the i-th row
Numerical value；
Step S330 searches the smallest first numerical value from each first numerical value, will be corresponding with the smallest first numerical value
Row matrix deleted from covariance matrix, until the number of remaining row matrix reaches predetermined number, by remaining row
The corresponding point cloud data of matrix is as characteristic point.
Specifically, the smallest first numerical value is searched, by ID number corresponding to the smallest first numerical value from ID number set
It is deleted, and deletes the row matrix from covariance matrix A, then search the smallest first number again from n-1 the first numerical value
Value, then ID number corresponding to the smallest first numerical value at this time and row matrix is deleted, and so on recycled, delete every time
Except a corresponding point cloud data, until the number of ID number reaches predetermined number requirement, i.e., corresponding to these remaining ID numbers
Point cloud data is characterized a little；
Step S230 chooses neighborhood to each characteristic point, obtains the plane normal vector of each characteristic point and each neighborhood, selects
Making even, face normal vector direction is identical and shortest two characteristic points of space length of characteristic point, as a reference point pair.
Further, step S130 includes:
The space between each reference point centering feature point is calculated by pre-set error model in step S410
Distance value；
Minimum space distance value and the angle of roll, pitch angle, course angle three is calculated by least square method in step S420
The correction value at a angle.
Here, multiple space length values are calculated into minimum space distance value and correction angle by least square method；
Further, correction angle includes angle of roll correction value, pitch angle correction value and course angle correction value.
It should be noted that the prior art obtains calibration parameter using the artificial method for measuring calibration, respectively to the angle of roll,
Pitch angle, course angle carry out estimation error, relatively complicated；
Wherein, estimate the angle of roll (roll) error method are as follows: in two air strips data of shuttle flight perpendicular to
Heading amount surveys approximate atural object height difference △ h of the same name, and the horizontal distance r of approximate atural object and two air strips center lines of the same name,
The calculation formula for sidewindering angle error is as follows:
The method for estimating pitch angle (pitch) error are as follows: be parallel to flight side in two air strips data of shuttle flight
To the same atural object center of measurement along the range difference D of heading, in conjunction with average flight altitude H, the calculating of pitching angle error
Formula is as follows:
The method for estimating course angle (heading) error are as follows: measured with after into the two of flight air strips data in forward direction
The distance between S and two air strips of the distance between atural object laser footpoint average central D twice, the calculating of course angle error
Formula is as follows:
Further, step S110 includes:
Step S510 obtains and loads point cloud data and track documents corresponding with point cloud data, obtains polygon area
Domain course line, track documents include GPS time；
Step S520 cuts point cloud data according to the GPS time of air strips start-stop, obtains every from polygonal region course line
The point cloud data of air strips.
Further, step S510 also can be used following steps to realize, comprising:
Step S610 pre-processes the initial data that laser radar obtains, and obtains point cloud data and and point cloud data
Corresponding track documents；
Step S620 loads point cloud data and track documents, obtains polygonal region course line.
Further, as shown in Fig. 2, being the electronics provided in an embodiment of the present invention for realizing the air strips matching process
The schematic diagram of equipment 100.In the present embodiment, the electronic equipment 100 be may be, but not limited to, PC (Personal
Computer, PC), laptop, monitoring device, server etc. have the computer equipment of air strips matching and processing capacity.
The electronic equipment 100 further includes air strips coalignment 200, storage medium 110 and processor 120.The present invention
In preferred embodiment, air strips coalignment 200 includes that at least one can be stored in the form of software or firmware (Firmware)
In the storage medium 110 or it is solidificated in soft in the operating system (Operating System, OS) of the electronic equipment 100
Part functional module.The processor 120 is for executing the executable software module stored in the storage medium 110, for example, institute
State software function module included by air strips coalignment 200 and computer program etc..In the present embodiment, the air strips matching dress
Setting 200 also can integrate in the operating system, a part as the operating system.Specifically, the air strips matching
Device 200 includes:
Module 210 is obtained, obtains and loads point cloud data and track documents corresponding with the point cloud data, pass through institute
State the point cloud data that track documents obtain every air strips from polygonal region course line；
Matching module 220 identifies the overlapping region of every air strips, the overlapping region point cloud number from adjacent air strips
Reference point pair is formed according to middle selected characteristic point, and by the Feature Points Matching；
Computing module 230 is calculated correction angle and minimum is empty by pre-set error model and least square method
Between distance value, wherein chosen from each reference point centering, the minimum space distance value between the characteristic point；
Correction module 240, according to the minimum space distance value and correction angle to the spatial position of the point cloud data into
Row amendment, so that the spatial position of the adjacent air strips matches.
It is understood that the concrete operation method of each functional module in the present embodiment can refer to above method embodiment
The detailed description of middle corresponding steps, it is no longer repeated herein.
In conclusion the embodiment of the present invention provides a kind of air strips matching process, device, electronic equipment and readable storage medium
Matter distinguishes the point cloud data of single air strips, the selected characteristic point from the point cloud data of the overlapping region of adjacent air strips, then will be special
Sign point carries out matching and forms reference point pair, and correction angle is calculated by error model and least square method and reference point centering is special
Minimum space distance value between sign point, and the spatial position of point cloud data is repaired according to minimum space distance value and correction angle
Just, so that the spatial position of adjacent air strips matches, the point cloud data in Different Plane is made to fit together, the present invention is implemented
Example can estimate air strips match parameter automatically, improve air strips matching efficiency, the lap of different air strips is connected, and realize
The splicing of different air strips data.
In embodiment provided by the present invention, it should be understood that disclosed device and method, it can also be by other
Mode realize.Device and method embodiment described above is only schematical, for example, flow chart and frame in attached drawing
Figure shows the system frame in the cards of the system of multiple embodiments according to the present invention, method and computer program product
Structure, function and operation.In this regard, each box in flowchart or block diagram can represent a module, section or code
A part, a part of the module, section or code includes one or more for implementing the specified logical function
Executable instruction.It should also be noted that function marked in the box can also be with not in some implementations as replacement
It is same as the sequence marked in attached drawing generation.For example, two continuous boxes can actually be basically executed in parallel, they have
When can also execute in the opposite order, this depends on the function involved.It is also noted that in block diagram and or flow chart
Each box and the box in block diagram and or flow chart combination, can function or movement as defined in executing it is dedicated
Hardware based system realize, or can realize using a combination of dedicated hardware and computer instructions.
In addition, each functional module in each embodiment of the present invention can integrate one independent portion of formation together
Point, it is also possible to modules individualism, an independent part can also be integrated to form with two or more modules.
It should be noted that, in this document, term " including ", " including " or its any other variant are intended to non-row
Its property includes, so that the process, method, article or equipment for including a series of elements not only includes those elements, and
And further include the other elements being not explicitly listed, or further include for this process, method, article or equipment institute it is intrinsic
Element.In the absence of more restrictions, the element limited by sentence " including one ... ", it is not excluded that including institute
State in the process, method, article or equipment of element that there is also other identical elements.
It is obvious to a person skilled in the art that invention is not limited to the details of the above exemplary embodiments, Er Qie
In the case where without departing substantially from spirit or essential attributes of the invention, the present invention can be realized in other specific forms.Therefore, no matter
From the point of view of which point, the present embodiments are to be considered as illustrative and not restrictive, and the scope of the present invention is by appended power
Benefit requires rather than above description limits, it is intended that all by what is fallen within the meaning and scope of the equivalent elements of the claims
Variation is included within the present invention.Any reference signs in the claims should not be construed as limiting the involved claims.
Claims (10)
1. a kind of air strips matching process characterized by comprising
Point cloud data and track documents corresponding with the point cloud data are obtained and load, by the track documents from polygon
Shape region obtains the point cloud data of every air strips in course line；
The overlapping region for identifying every air strips, the selected characteristic point from the overlapping region point cloud data of adjacent air strips,
And the Feature Points Matching is formed into reference point pair；
By pre-set error model and least square method, correction angle and minimum space distance value is calculated, wherein from
Each reference point centering is chosen, the minimum space distance value between the characteristic point；
The spatial position of the point cloud data is modified according to the minimum space distance value and correction angle, so that the phase
The spatial position of adjacent air strips matches.
2. air strips matching process according to claim 1, which is characterized in that the overlay region of identification every air strips
Domain, the selected characteristic point from the overlapping region point cloud data of adjacent air strips, and the Feature Points Matching is formed into reference point
To including:
Grid processing is carried out to the point cloud data of every air strips, judges whether be stored with the point cloud data in grid,
Identify whether the grid is overlapping region；
Point cloud data in the overlapping region of adjacent air strips is subjected to matrix calculating, obtains the first numerical value, according to described the
One numerical value selected characteristic point from the point cloud data；
Neighborhood is chosen to each characteristic point, obtains the plane normal vector of each characteristic point and each neighborhood, selects
Take the planar process vector direction identical and shortest two characteristic points of the space length of the characteristic point, as a phase
Close point pair.
3. air strips matching process according to claim 2, which is characterized in that a point cloud data is a three-dimensional seat
It marks, the point cloud data in the overlapping region by adjacent air strips carries out matrix calculating, the first numerical value is obtained, according to described
First numerical value selected characteristic point from the point cloud data includes:
Covariance matrix is calculated by the point cloud data in the overlapping region, wherein described in each point cloud data is used as
A row matrix in covariance matrix；
Each row matrix of the covariance matrix is calculated, is calculated and is counted with each row matrix corresponding first
Value；
The smallest first numerical value is searched from each first numerical value, it will be corresponding with the smallest first numerical value
The row matrix is deleted from the covariance matrix, until the number of the remaining row matrix reaches predetermined number,
Using the corresponding point cloud data of the remaining row matrix as characteristic point.
4. air strips matching process according to claim 1, which is characterized in that it is described by pre-set error model and
Least square method, is calculated correction angle and minimum space distance value includes:
By pre-set error model, the space length value between each reference point centering feature point is obtained；
By least square method be calculated minimum space distance value and the angle of roll, pitch angle, three angles of course angle correction value.
5. air strips matching process according to claim 1, which is characterized in that it is described acquisition and load point cloud data and with institute
The corresponding track documents of point cloud data are stated, obtain the point of every air strips from polygonal region course line by the track documents
Cloud data include:
Point cloud data and track documents corresponding with the point cloud data are obtained and loaded, polygonal region course line, institute are obtained
Stating track documents includes GPS time；
The point cloud data is cut according to the GPS time of air strips start-stop, obtains every from the polygonal region course line
The point cloud data of air strips.
6. air strips matching process according to claim 5, which is characterized in that it is described acquisition and load point cloud data and with institute
The corresponding track documents of point cloud data are stated, obtaining polygonal region course line includes:
Initial data is pre-processed, point cloud data and track documents corresponding with the point cloud data are obtained；
The point cloud data and the track documents are loaded, polygonal region course line is obtained.
7. air strips matching process according to claim 1, which is characterized in that the correction angle include angle of roll correction value,
Pitch angle correction value and course angle correction value.
8. a kind of air strips coalignment, which is characterized in that be applied to electronic equipment, described device includes:
Module is obtained, obtains and loads point cloud data and track documents corresponding with the point cloud data, pass through the track
File obtains the point cloud data of every air strips from polygonal region course line；
Matching module identifies the overlapping region of every air strips, selects from the overlapping region point cloud data of adjacent air strips
Characteristic point is taken, and the Feature Points Matching is formed into reference point pair；
Correction angle and minimum space distance is calculated by pre-set error model and least square method in computing module
Value, wherein chosen from each reference point centering, the minimum space distance value between the characteristic point；
Correction module is modified the spatial position of the point cloud data according to the minimum space distance value and correction angle,
So that the spatial position of the adjacent air strips matches.
9. a kind of electronic equipment, which is characterized in that the electronic equipment includes:
Storage medium；
Processor；And
Air strips coalignment, described device are stored in the storage medium, and the software function including being executed by the processor
Energy module, described device include:
Module is obtained, obtains and loads point cloud data and track documents corresponding with the point cloud data, pass through the track
File obtains the point cloud data of every air strips from polygonal region course line；
Matching module identifies the overlapping region of every air strips, selects from the overlapping region point cloud data of adjacent air strips
Characteristic point is taken, and the Feature Points Matching is formed into reference point pair；
Correction angle and minimum space distance is calculated by pre-set error model and least square method in computing module
Value, wherein chosen from each reference point centering, the minimum space distance value between the characteristic point；
Correction module is modified the spatial position of the point cloud data according to the minimum space distance value and correction angle,
So that the spatial position of the adjacent air strips matches.
10. a kind of readable storage medium storing program for executing, which is characterized in that be stored with computer program, the meter in the readable storage medium storing program for executing
Calculation machine program, which is performed, realizes air strips matching process described in any one of claim 1-7.
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