CN117606351A - Target selection system and method for target geometric precision factor minimum contribution value recursion - Google Patents
Target selection system and method for target geometric precision factor minimum contribution value recursion Download PDFInfo
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Abstract
The invention provides a target selection system and a target selection method for target geometric precision factor minimum contribution value recursion. According to the invention, the measurement data of the black square intersection point of each grid mark in the shape of a Chinese character 'tian' under the coordinate of a three-dimensional scanner and the three-dimensional coordinate of the high-precision total station coordinate system are substituted into a scanner system error self-checking model as homonymous points, a linear error equation is used for obtaining a coefficient matrix of an error equation set, and the geometric precision factors of all mark combinations and the contribution values of each mark to all mark geometric precision factors are calculated. And selecting the minimum contribution value, comparing the minimum contribution value with a threshold value, and rejecting targets with the contribution value smaller than the threshold value. Repeating the calculation, recursively estimating the minimum contribution value until the minimum contribution value is larger than the threshold value, and obtaining the final target selection scheme. Substituting the homonymous points of the selected targets into an error self-checking model, and resolving the systematic error to finish equipment checking. According to the invention, the geometric contribution values of each target to all targets are quantitatively analyzed, and targets are selected in a minimum contribution value recurrence mode, so that the rationality of target selection is improved.
Description
Technical Field
The invention belongs to the technical field of laser scanner calibration optimization design, and particularly relates to a target selection system and method for recursion of minimum contribution value of a target geometric precision factor.
Background
The ground three-dimensional scanner is an active measuring device and can quickly reproduce real scenes. The measuring principle is that the device emits laser, collects the information of time, intensity and the like of the emission signal and the reflected echo signal of the surface of the irradiation object, obtains the information of the distance, reflectivity and the like of the target, and then obtains the space information of the target by assisting with the scanning angle information in the vertical direction and the horizontal direction. Compared with the traditional surveying and mapping means, the technology has the advantages of high measuring speed, strong effectiveness, all-weather work, easy data transmission, processing and expression and convenient operation. With the continuous update of the three-dimensional laser scanning technology, more and more high-precision measurement fields begin to introduce the technology. In order to obtain high-quality laser point clouds, equipment calibration is necessary.
The existing method only improves the scanner calibration method in aspects of target patterns, materials, calibration models, parameter optimization methods and the like, but the influence mechanism of the geometric parameters of the targets on the scanner calibration performance is not clear enough; the single-storage conversion target type can not effectively improve the calibration precision and efficiency, and the influence of the qualitative or quantitative analysis target selection of a learner on the calibration of the system error is avoided. Therefore, the action mechanism of geometric characteristics such as target distance, number and distribution on the system error calibration accuracy is necessary to be studied, a scientific target selection method is formulated to improve the calibration efficiency, and the ground three-dimensional scanner is reasonably and efficiently calibrated.
Disclosure of Invention
Aiming at the problem of lack of quantitative analysis to formulate a scientific target selection scheme, the invention provides a target selection system and method for recursion of the minimum contribution value of the geometric precision factor of the target, and aims to design a scientific target combination or layout scheme by quantitatively analyzing the influence of each target on the overall combination target GDOP and model parameter calibration precision, so that target measurement is more targeted, optimal target combination or suboptimal target combination with small deviation can be selected rapidly, and the calibration efficiency is improved.
The technical scheme of the system of the invention is a target selecting system for recursion of the minimum contribution value of the geometric precision factor of the target, comprising:
a plurality of black-white alternate grid targets are randomly distributed on the peripheral wall surfaces and the roof of the indoor environment;
placing a processing terminal, a three-dimensional scanner and a high-precision total station on the indoor ground;
the processing terminal is respectively connected with the three-dimensional scanner and the high-precision total station in sequence;
an error self-checking model is built, measurement data of black grid intersection points of each grid square target in a three-dimensional scanner coordinate system and three-dimensional coordinates of each black grid square target in a high-precision total station coordinate system are used as input of the error self-checking model and linearized to obtain an error equation and an error coefficient matrix of each grid square target, an error equation set is formed through the error equation structures of a plurality of grid square targets, and geometric precision factors of the grid square targets are calculated by combining the error coefficient matrices of the grid square targets;
calculating the contribution value of each grid square target to the geometric precision factors of the m grid square targets;
selecting a grid target with a minimum contribution value in a shape of Chinese character 'tian';
if the grid square target with the smallest contribution value is larger than or equal to the threshold value of the contribution value, the target selection is finished, and the selected grid square target with the smallest contribution value is output; if the grid square target with the smallest contribution value is smaller than the contribution value threshold, removing the grid square target with the smallest contribution value as a grid square target combination to be optimized until the grid square target with the smallest contribution value is larger than or equal to the contribution value threshold, and outputting the selected grid square target;
substituting the measurement data of each grid square target center in the target combination of the scanner system error calibration under the coordinate system of the three-dimensional scanner and the three-dimensional coordinates of the high-precision total station coordinate system into an error self-calibration model, iteratively solving parameters of the error self-calibration model according to the least square principle, acquiring indoor environment three-dimensional point clouds by a processing terminal through the three-dimensional scanner, and correcting the acquired indoor environment three-dimensional point clouds by combining the system errors of the three-dimensional scanner to obtain corrected indoor environment three-dimensional point clouds.
The technical scheme of the method is a target selecting method for recursion of the minimum contribution value of the geometric precision factor of the target, and specifically comprises the following steps:
step 1: the processing terminal scans indoor environment point clouds by using a three-dimensional scanner, obtains measurement data of black square intersection points of each grid square target in a three-dimensional scanner coordinate system by using a corner extraction algorithm, adjusts the high-precision total station to sequentially aim at the black square intersection points of each grid square target, and acquires three-dimensional coordinates of the black square intersection points of each grid square target in the high-precision total station coordinate system by using the high-precision total station;
step 2: constructing an error self-checking model, taking measurement data of black square intersection points of each grid square target in a three-dimensional scanner coordinate system and three-dimensional coordinates of the black square intersection points of each grid square target in a high-precision total station coordinate system as input of the error self-checking model, linearizing the input error self-checking model to obtain an error equation and an error coefficient matrix of each grid square target, constructing an error equation set through the error equations of a plurality of grid square targets, and calculating geometric precision factors of a plurality of grid square targets by combining the error coefficient matrices of a plurality of grid square targets;
step 3: calculating the contribution value of each grid square target to the geometric precision factors of the m grid square targets;
step 4: selecting a grid square target with the smallest contribution value from the contribution values of the geometric precision factors of the grid square targets to the m grid square targets;
step 5: if the grid targets with the smallest contribution value are larger than or equal to the contribution value threshold value, selecting targets is finished, and the step 6 is skipped; if the grid square target with the smallest contribution value is smaller than the contribution value threshold, removing the grid square target with the smallest contribution value from the m grid square targets as a grid square target combination to be preferred, enabling m=m-1, repeating the steps 1-4 until the grid square target with the smallest contribution value is larger than or equal to the contribution value threshold, and jumping to the step 6;
step 6: taking the output selected grid targets of the grid patterns as target combinations for error checking of a scanner system, substituting measurement data of the centers of the grid targets of the grid patterns of each grid pattern in the target combinations for error checking of the scanner system under a three-dimensional scanner and three-dimensional coordinates of the grid targets of each grid pattern in a high-precision total station under the coordinate system into an error self-checking model in the step 2, iteratively calculating parameters of the error self-checking model according to a least square principle to obtain an error self-checking model after optimization solution, acquiring three-dimensional point clouds of an indoor environment by a processing terminal through the three-dimensional scanner, combining the solving parameters of the error self-checking model to obtain the system error of the three-dimensional scanner, and correcting the acquired three-dimensional point clouds of the indoor environment by combining the system error of the three-dimensional scanner to obtain the three-dimensional point clouds of the indoor environment after correction;
preferably, the measurement data of the black square intersection point of each grid square target in step 1 is defined as follows:
i∈[1,m]
wherein m represents the number of square targets in the shape of Chinese character 'Tian', r i A distance measurement value in measurement data of a black square intersection point of an ith grid mark in a three-dimensional scanner coordinate system is represented,horizontal angle, θ, in measurement data representing black grid intersection point of ith grid target in three-dimensional scanner coordinate system i A height angle of a black square intersection point of the ith grid mark in the measurement data of the three-dimensional scanner coordinate system is represented;
the three-dimensional coordinates of the black square intersection point of each grid mark in the shape of the Chinese character 'tian' in the high-precision total station coordinate system are defined as follows:
(x i ,y i ,z i )
i∈[1,m]
wherein m represents the number of square targets in the shape of Chinese character 'tian', and x i X-axis coordinate, y of black grid intersection point representing ith grid mark in form of Chinese character 'tian' shape in high-precision total station coordinate system i Y-axis coordinate, z of black grid intersection point representing ith grid mark in form of Chinese character 'tian' shape in high-precision total station coordinate system i Z-axis coordinates of black grid intersection points of the ith grid mark in the high-precision total station coordinate system are represented;
preferably, the error self-checking model in step 2 is specifically defined as follows:
i∈[1,m]
wherein m represents the number of square targets in the shape of Chinese character 'Tian', r i Represent the firstThe measured values of the black square intersection points of the i square targets in the three-dimensional scanner coordinate system,horizontal angle, θ, in measurement data representing black grid intersection point of ith grid target in three-dimensional scanner coordinate system i Height angle, x, in measurement data representing black grid intersection point of ith grid mark in three-dimensional scanner coordinate system i X-axis coordinate, y of black grid intersection point representing ith grid mark in form of Chinese character 'tian' shape in high-precision total station coordinate system i Y-axis coordinate, z of black grid intersection point representing ith grid mark in form of Chinese character 'tian' shape in high-precision total station coordinate system i The Z-axis coordinate of the black square intersection point of the ith grid mark in the high-precision total station coordinate system is represented, the error self-checking model is 13 parameters in total, b is a ranging addition constant, K is a ranging multiplication constant, phi and omega, K respectively represents a first rotation parameter, a second rotation parameter and a third rotation parameter, and Deltax, deltay and Deltaz respectively represent a first translation parameter, a second translation parameter and a third translation parameter, K, b, alpha and w 1 ,w 2 ,β x ,β y Respectively representing a first internal parameter, a second internal parameter, a third internal parameter, a seventh internal parameter, R (Φ, Ω, K) representing a rotation matrix between the three-dimensional scanner coordinates and the total station coordinates, and>representing a scanner longitudinal axis rotation matrix,>and->Rotation matrix representing the rotation of the scanner's transverse axis coordinate system to the longitudinal axis coordinate system along the X-axis and Y-axis, respectively,/->Representing the laser vector reflected by the reflector;
and step 2, calculating geometric precision factors of the grid targets in the shape of the Chinese character 'Tian', wherein the geometric precision factors are specifically as follows:
wherein trace represents matrix trace calculation, A m An error equation coefficient matrix representing m grid targets,transposed matrix of error equation coefficient matrix representing m grid targets in shape of Chinese character 'tian', GDOP m Representing geometric precision factors of m grid targets in a Chinese character 'tian' shape;
preferably, in step 3, the contribution value of each grid square target to the geometric precision factor of m grid square targets is calculated, and the specific formula is as follows:
wherein,representing the contribution value of the ith square grid target to the geometric precision factors of m square grid targets, G m An inverse matrix obtained by multiplying error equation coefficient matrix representing m square grid targets with corresponding transpose matrix, A m Error equation coefficient matrix representing m grid targets in Chinese character 'tian' shape>Transposed matrix of error equation coefficient matrix representing m square grid targets, d i Error coefficient matrix for ith square target of each Chinese character 'tian'>The transposed matrix of the error coefficient matrix of each square mark in the shape of the Chinese character 'Tian', I being a unit matrix;
the invention has the advantages that:
according to the method, the influence of the target GDOP on the model parameter calibration precision is analyzed, and the condition of combining the target GDOP minimum value is obtained through quantitative analysis;
quantitatively evaluating the influence of the number, the distance and the distribution uniformity of targets on the accuracy of the GDOP and the model parameters;
the contribution value of each target to the combined target GDOP is quantitatively analyzed, and the targets with small contribution values are removed, so that target measurement is more targeted, and the target measurement efficiency is improved;
the target selecting method based on the recursion of the minimum target GDOP contribution value has the advantages that the target selecting result is close to the GDOP of the optimal target combination, and the target selecting calculation efficiency is greatly improved;
the method can be used for error checking of a ground three-dimensional scanner system, and can select targets by quantitatively analyzing geometric contribution values of each target to calibration target selection, so that the rationality of target selection is improved, and the checking efficiency is improved.
Drawings
Fig. 1: the method of the embodiment of the invention is a flow chart;
fig. 2: the embodiment of the invention relates to a grid target graph in a Chinese character 'tian' shape;
fig. 3: GDOP difference algorithm contrast graphs of different numbers of targets in the embodiment of the invention;
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
In particular, the method according to the technical solution of the present invention may be implemented by those skilled in the art using computer software technology to implement an automatic operation flow, and a system apparatus for implementing the method, such as a computer readable storage medium storing a corresponding computer program according to the technical solution of the present invention, and a computer device including the operation of the corresponding computer program, should also fall within the protection scope of the present invention.
The following description is made with reference to fig. 1-3 for a target selection system and method based on minimum contribution of a target geometry accuracy factor.
Specific embodiments of the system of the present invention are as follows:
a plurality of black-white alternate grid targets are randomly distributed on the peripheral wall surfaces and the roof of the indoor environment;
placing a processing terminal, a three-dimensional scanner and a high-precision total station on the indoor ground;
the processing terminal is respectively connected with the three-dimensional scanner and the high-precision total station in sequence;
the model of the processing terminal is a computer terminal;
the model of the three-dimensional scanner is HGS-300;
the model of the high-precision total station is Leka TS60;
specific embodiments of the method of the invention are as follows:
FIG. 1 is a flow chart of a method according to an embodiment of the present invention;
step 1: the processing terminal scans indoor environment point clouds by using a three-dimensional scanner, obtains measurement data of black square intersection points of each grid square target in a three-dimensional scanner coordinate system by using a corner extraction algorithm, adjusts the high-precision total station to sequentially aim at the black square intersection points of each grid square target, and acquires three-dimensional coordinates of the black square intersection points of each grid square target in the high-precision total station coordinate system by using the high-precision total station;
the grid targets are shown in figure 2;
the measurement data of the black square intersection point of each grid mark in the shape of Chinese character 'tian' in step 1 is defined as follows:
i∈[1,m]
wherein m=40 represents the number of square targets in the shape of a Chinese character 'tian', r i A distance measurement value in measurement data of a black square intersection point of an ith grid mark in a three-dimensional scanner coordinate system is represented,horizontal angle, θ, in measurement data representing black grid intersection point of ith grid target in three-dimensional scanner coordinate system i A height angle of a black square intersection point of the ith grid mark in the measurement data of the three-dimensional scanner coordinate system is represented;
the three-dimensional coordinates of the black square intersection point of each grid mark in the shape of the Chinese character 'tian' in the high-precision total station coordinate system are defined as follows:
(x i ,y i ,z i )
i∈[1,m]
wherein m represents the number of square targets in the shape of Chinese character 'tian', and x i X-axis coordinate, y of black grid intersection point representing ith grid mark in form of Chinese character 'tian' shape in high-precision total station coordinate system i Y-axis coordinate, z of black grid intersection point representing ith grid mark in form of Chinese character 'tian' shape in high-precision total station coordinate system i Z-axis coordinates of black grid intersection points of the ith grid mark in the high-precision total station coordinate system are represented;
step 2: constructing an error self-checking model, taking measurement data of black square intersection points of each grid square target in a three-dimensional scanner coordinate system and three-dimensional coordinates of the black square intersection points of each grid square target in a high-precision total station coordinate system as input of the error self-checking model, linearizing the input error self-checking model to obtain an error equation and an error coefficient matrix of each grid square target, constructing an error equation set through the error equations of a plurality of grid square targets, and calculating geometric precision factors of a plurality of grid square targets by combining the error coefficient matrices of a plurality of grid square targets;
and 2, the error self-checking model is specifically defined as follows:
i∈[1,m]
wherein m represents the number of square targets in the shape of Chinese character 'Tian', r i A distance measurement value in measurement data of a black square intersection point of an ith grid mark in a three-dimensional scanner coordinate system is represented,horizontal angle, θ, in measurement data representing black grid intersection point of ith grid target in three-dimensional scanner coordinate system i Height angle, x, in measurement data representing black grid intersection point of ith grid mark in three-dimensional scanner coordinate system i Black square intersection point representing ith square mark in shape of Chinese character' tianX-axis coordinate and y-axis coordinate in total station coordinate system i Y-axis coordinate, z of black grid intersection point representing ith grid mark in form of Chinese character 'tian' shape in high-precision total station coordinate system i The Z-axis coordinate of the black square intersection point of the ith grid mark in the high-precision total station coordinate system is represented, the error self-checking model is 13 parameters in total, b is a ranging addition constant, K is a ranging multiplication constant, phi and omega, K respectively represents a first rotation parameter, a second rotation parameter and a third rotation parameter, and Deltax, deltay and Deltaz respectively represent a first translation parameter, a second translation parameter and a third translation parameter, K, b, alpha and w 1 ,w 2 ,β x ,β y Respectively representing a first internal parameter, a second internal parameter, a third internal parameter, a seventh internal parameter, R (Φ, Ω, K) representing a rotation matrix between the three-dimensional scanner coordinates and the total station coordinates, and>representing a scanner longitudinal axis rotation matrix,>and->Rotation matrix representing the rotation of the scanner's transverse axis coordinate system to the longitudinal axis coordinate system along the X-axis and Y-axis, respectively,/->Representing the laser vector reflected by the reflector;
and step 2, calculating geometric precision factors of the grid targets in the shape of the Chinese character 'Tian', wherein the geometric precision factors are specifically as follows:
wherein trace represents matrix trace calculation, A m An error equation coefficient matrix representing m grid targets,transposed matrix of error equation coefficient matrix representing m grid targets in shape of Chinese character 'tian', GDOP m Representing geometric precision factors of m grid targets in a Chinese character 'tian' shape;
step 3: calculating the contribution value of each grid square target to the geometric precision factors of the m grid square targets;
and 3, calculating the contribution value of each grid square target to the geometric precision factors of the m grid square targets, wherein the specific formula is as follows:
wherein,representing the contribution value of the ith square grid target to the geometric precision factors of m square grid targets, G m An inverse matrix obtained by multiplying error equation coefficient matrix representing m square grid targets with corresponding transpose matrix, A m Error equation coefficient matrix representing m grid targets in Chinese character 'tian' shape>Transposed matrix of error equation coefficient matrix representing m square grid targets, d i Error coefficient matrix for ith square target of each Chinese character 'tian'>The transposed matrix of the error coefficient matrix of each square mark in the shape of the Chinese character 'Tian', I being a unit matrix;
step 4: selecting a grid square target with the smallest contribution value from the contribution values of the geometric precision factors of the grid square targets to the m grid square targets;
step 5: if the grid targets with the smallest contribution value are larger than or equal to the contribution value threshold value, selecting targets is finished, and the step 6 is skipped; if the grid square target with the smallest contribution value is smaller than the contribution value threshold, removing the grid square target with the smallest contribution value from the m grid square targets as a grid square target combination to be preferred, enabling m=m-1, repeating the steps 1-4 until the grid square target with the smallest contribution value is larger than or equal to the contribution value threshold, and jumping to the step 6;
step 6: and 2, taking the output selected grid targets as target combinations for error checking of a scanner system, substituting measurement data of the centers of the grid targets of each grid in the target combinations for error checking of the scanner system under a three-dimensional scanner and three-dimensional coordinates of the centers of the grid targets of each grid in the high-precision total station under the coordinate system into an error self-checking model in the step 2, iteratively calculating parameters of the error self-checking model according to a least square principle to obtain an error self-checking model after optimization solution, acquiring three-dimensional point clouds of an indoor environment by a processing terminal through the three-dimensional scanner, combining the solving parameters of the error self-checking model to obtain the system error of the three-dimensional scanner, correcting the acquired three-dimensional point clouds of the indoor environment by combining the system error of the three-dimensional scanner to obtain three-dimensional point clouds of the indoor environment after correction, and improving the quality of the three-dimensional point clouds.
The invention can be used for error checking of a ground three-dimensional scanner system, and can select targets by quantitatively analyzing geometric contribution values of each target to calibration target selection, so that the rationality of target selection is improved, and the checking efficiency is improved;
the choice of targets based on the minimum contribution of GDOP may increase measurement efficiency, but also has limitations. The m targets are algorithmically selected to obtain r targets, and the selection result is suboptimal because of the limitation of the previous m-r+1 selection. Most preferably the target method should traverse GDOPs for all r target combinations in m targets, with the target combination of the smallest GDOP being optimal. FIG. 1, a different number of targets selected from 38 targets versus the difference in GDOP between the algorithm herein and the optimal result. Obviously, the target selection results are almost identical.
However, the difference in the calculation efficiency between the two is large. If selected from m targetsSelecting 6 optimal targets, and calculating an optimal resultMinor GDOP, whereas m-6 minor GDOPs and m+m-1+, +7 major +.>The amount of computation is necessarily less than the number of equally calculated GDOPs. The calculated amounts of the two methods are compared with each other according to the number of targets shown in Table 5. The computational effort of the algorithm herein is much smaller than the traversal method in terms of the computational effort of one GDOP.
Table 1 comparison of the calculated amounts of the two algorithms
In summary, a quantitative evaluation approach can be provided for individual targets based on target GDOP theory; reasonable target combination can be obtained according to the target GDOP contribution value recurrence method, and the checking efficiency is improved while the checking precision of equipment is ensured. The research has important reference value for the research of scanner periodic calibration and target layout.
It should be understood that parts of the specification not specifically set forth herein are all prior art.
It should be understood that the foregoing description of the preferred embodiments is not intended to limit the scope of the invention, but rather to limit the scope of the claims, and that those skilled in the art can make substitutions or modifications without departing from the scope of the invention as set forth in the appended claims.
Claims (6)
1. A target selection system for target geometric precision factor minimum contribution recurrence, comprising:
a plurality of black-white alternate grid targets are randomly distributed on the peripheral wall surfaces and the roof of the indoor environment;
placing a processing terminal, a three-dimensional scanner and a high-precision total station on the indoor ground;
the processing terminal is respectively connected with the three-dimensional scanner and the high-precision total station in sequence;
taking the measurement data of the black grid intersection point of each grid square target in a three-dimensional scanner coordinate system and the three-dimensional coordinate of each grid square target in a high-precision total station coordinate system as the input of an error self-checking model and linearizing to obtain an error equation and an error coefficient matrix of each grid square target, further forming an error equation set, and calculating geometric precision factors of a plurality of grid square targets by combining the error coefficient matrices of a plurality of grid square targets;
calculating the contribution value of each grid square target to the geometric precision factors of the m grid square targets;
selecting a grid target with a minimum contribution value in a shape of Chinese character 'tian';
if the grid square target with the smallest contribution value is larger than or equal to the threshold value of the contribution value, the target selection is finished, and the selected grid square target with the smallest contribution value is output; if the grid square target with the smallest contribution value is smaller than the contribution value threshold, removing the grid square target with the smallest contribution value as a grid square target combination to be optimized until the grid square target with the smallest contribution value is larger than or equal to the contribution value threshold, and outputting the selected grid square target;
substituting the measurement data of each grid square target center in the target combination of the scanner system error calibration under the coordinate system of the three-dimensional scanner and the three-dimensional coordinates of the high-precision total station coordinate system into an error self-calibration model, iteratively solving parameters of the error self-calibration model according to the least square principle, acquiring indoor environment three-dimensional point clouds by a processing terminal through the three-dimensional scanner, and correcting the acquired indoor environment three-dimensional point clouds by combining the system errors of the three-dimensional scanner to obtain corrected indoor environment three-dimensional point clouds.
2. A target selection method for target geometric precision factor minimum contribution value recursion applied to the target selection system for target geometric precision factor minimum contribution value recursion of claim 1, characterized by: the method comprises the following steps:
step 1: the processing terminal scans indoor environment point clouds by using a three-dimensional scanner, obtains measurement data of black square intersection points of each grid square target in a three-dimensional scanner coordinate system by using a corner extraction algorithm, adjusts the high-precision total station to sequentially aim at the black square intersection points of each grid square target, and acquires three-dimensional coordinates of the black square intersection points of each grid square target in the high-precision total station coordinate system by using the high-precision total station;
step 2: constructing an error self-checking model, taking measurement data of black square intersection points of each grid square target in a three-dimensional scanner coordinate system and three-dimensional coordinates of the black square intersection points of each grid square target in a high-precision total station coordinate system as input of the error self-checking model, linearizing the input error self-checking model to obtain an error equation and an error coefficient matrix of each grid square target, constructing an error equation set through the error equations of a plurality of grid square targets, and calculating geometric precision factors of a plurality of grid square targets by combining the error coefficient matrices of a plurality of grid square targets;
step 3: calculating the contribution value of each grid square target to the geometric precision factors of the m grid square targets;
step 4: selecting a grid square target with the smallest contribution value from the contribution values of the geometric precision factors of the grid square targets to the m grid square targets;
step 5: if the grid targets with the smallest contribution value are larger than or equal to the contribution value threshold value, selecting targets is finished, and the step 6 is skipped; if the grid square target with the smallest contribution value is smaller than the contribution value threshold, removing the grid square target with the smallest contribution value from the m grid square targets as a grid square target combination to be preferred, enabling m=m-1, repeating the steps 1-4 until the grid square target with the smallest contribution value is larger than or equal to the contribution value threshold, and jumping to the step 6;
step 6: and (3) taking the output selected grid targets as target combinations for scanner system error calibration, substituting the measurement data of each grid target center in the target combinations for scanner system error calibration under a three-dimensional scanner and the three-dimensional coordinates of each grid target center under a high-precision total station coordinate system into the error self-calibration model in the step (2), iteratively calculating parameters of the error self-calibration model according to a least square principle to obtain an error self-calibration model after optimization solution, acquiring three-dimensional point clouds of an indoor environment by a processing terminal through the three-dimensional scanner, combining the solving parameters of the error self-calibration model to obtain the system error of the three-dimensional scanner, and correcting the acquired three-dimensional point clouds of the indoor environment by combining the system error of the three-dimensional scanner to obtain the three-dimensional point clouds of the corrected indoor environment.
3. The target selection method for target geometric precision factor minimum contribution recurrence according to claim 2, wherein:
the measurement data of the black square intersection point of each grid mark in the shape of Chinese character 'tian' in step 1 is defined as follows:
i∈[1,m]
wherein m represents the number of square targets in the shape of Chinese character 'Tian', r i A distance measurement value in measurement data of a black square intersection point of an ith grid mark in a three-dimensional scanner coordinate system is represented,horizontal angle, θ, in measurement data representing black grid intersection point of ith grid target in three-dimensional scanner coordinate system i A height angle of a black square intersection point of the ith grid mark in the measurement data of the three-dimensional scanner coordinate system is represented;
the three-dimensional coordinates of the black square intersection point of each grid mark in the shape of the Chinese character 'tian' in the high-precision total station coordinate system are defined as follows:
(x i ,y i ,z i )
i∈[1,m]
wherein m represents the number of square targets in the shape of Chinese character 'tian', and x i X-axis coordinate, y of black grid intersection point representing ith grid mark in form of Chinese character 'tian' shape in high-precision total station coordinate system i Y-axis coordinate, z of black grid intersection point representing ith grid mark in form of Chinese character 'tian' shape in high-precision total station coordinate system i And the Z-axis coordinate of the black square intersection point of the ith grid mark in the high-precision total station coordinate system is shown.
4. A target selection method for target geometric precision factor minimum contribution recurrence according to claim 3, wherein:
and 2, the error self-checking model is specifically defined as follows:
i∈[1,m]
wherein m represents the number of square targets in the shape of Chinese character' tian，r i A distance measurement value in measurement data of a black square intersection point of an ith grid mark in a three-dimensional scanner coordinate system is represented,horizontal angle, θ, in measurement data representing black grid intersection point of ith grid target in three-dimensional scanner coordinate system i Height angle, x, in measurement data representing black grid intersection point of ith grid mark in three-dimensional scanner coordinate system i X-axis coordinate, y of black grid intersection point representing ith grid mark in form of Chinese character 'tian' shape in high-precision total station coordinate system i Y-axis coordinate, z of black grid intersection point representing ith grid mark in form of Chinese character 'tian' shape in high-precision total station coordinate system i The Z-axis coordinate of the black square intersection point of the ith grid mark in the high-precision total station coordinate system is represented, the error self-checking model is 13 parameters in total, b is a ranging addition constant, K is a ranging multiplication constant, phi and omega, K respectively represents a first rotation parameter, a second rotation parameter and a third rotation parameter, and Deltax, deltay and Deltaz respectively represent a first translation parameter, a second translation parameter and a third translation parameter, K, b, alpha and w 1 ,w 2 ,β x ,β y Respectively representing a first internal parameter, a second internal parameter, a third internal parameter, a seventh internal parameter, R (Φ, Ω, K) representing a rotation matrix between the three-dimensional scanner coordinates and the total station coordinates, and>representing a scanner longitudinal axis rotation matrix,>and->Rotation matrix representing the rotation of the scanner's transverse axis coordinate system to the longitudinal axis coordinate system along the X-axis and Y-axis, respectively,/->Representing the moment of reflection of the laser vector by the reflectorAn array.
5. The target selection method for target geometric precision factor minimum contribution recurrence according to claim 4, wherein:
and step 2, calculating geometric precision factors of the grid targets in the shape of the Chinese character 'Tian', wherein the geometric precision factors are specifically as follows:
wherein trace represents matrix trace calculation, A m An error equation coefficient matrix representing m grid targets,transposed matrix of error equation coefficient matrix representing m grid targets in shape of Chinese character 'tian', GDOP m And the geometric precision factors of the m grid targets are represented.
6. The target selection method for target geometric precision factor minimum contribution recurrence according to claim 5, wherein:
and 3, calculating the contribution value of each grid square target to the geometric precision factors of the m grid square targets, wherein the specific formula is as follows:
wherein,representing the contribution value of the ith square grid target to the geometric precision factors of m square grid targets, G m Error equation coefficient matrix representing m square targets in Chinese character 'tian' shape and corresponding transposed momentMatrix multiplied inverse matrix, A m Error equation coefficient matrix representing m grid targets in Chinese character 'tian' shape>Transposed matrix of error equation coefficient matrix representing m square grid targets, d i Error coefficient matrix for ith square target of each Chinese character 'tian'>And the transpose matrix of the error coefficient matrix of each field-shaped square target is the ith matrix, and I is a unit matrix.
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