CN110334174B - POS data deviation rectifying method and system - Google Patents
POS data deviation rectifying method and system Download PDFInfo
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Abstract
The invention relates to a method and a system for correcting POS (position and orientation system) data, wherein the method comprises the following steps: step 1, POS data acquired at each time of a test road section are respectively subjected to POS resolving and then fused with point cloud data; step 2, when the POS data are judged to need deviation correction according to the fused point cloud data, POS data of a test road section are extracted, and a quality grade is obtained after POS calculation is carried out; and 3, establishing a deviation correction factor model according to the quality grade of each POS data, and correcting the deviation of each POS data according to the deviation correction reference of the deviation correction factor model. The quality grade corresponding to the POS data can be generated in the POS data resolving process, the weight of the POS data acquired at the time is determined according to the quality grade, and then the POS data is corrected, the problem data is not required to be corrected by acquiring a control point on the spot, the operation efficiency can be greatly improved, and the purposes of reducing the cost and increasing the efficiency are achieved.
Description
Technical Field
The invention relates to the field of data deviation correction, in particular to a POS data deviation correction method and system.
Background
In high-precision map data acquisition, a mobile measuring vehicle-mounted sensor (laser scanner, camera) and a means for carrying out measurement by a POS (point of sale) are widely adopted, wherein the POS system mainly functions to provide high-precision positioning and attitude determination information, for example, coordinate information is given to the point cloud data after the point cloud data is fused, and the precision of the map data is directly influenced by the quality of the POS data.
However, the actually collected POS data may be affected by various conditions, and after the POS data is fused with the point cloud data and then given to the point cloud data coordinate information, the point cloud data collected at the same position in different batches may have a large difference in accuracy, thereby causing a quality problem in the data. Aiming at the problem that the coordinate precision of point cloud data at the same position acquired for multiple times is large in difference, which acquired coordinate is accurate cannot be determined in the most difficult time, and the solution of the prior art is to acquire a control point on the spot and correct the data by taking the control point as a reference. However, acquiring control points in the field can add significant effort, resulting in inefficiencies.
Disclosure of Invention
The invention provides a POS data deviation rectifying method and system aiming at the technical problems in the prior art.
The technical scheme for solving the technical problems is as follows: a method of deskewing POS data, the method comprising:
and 3, establishing a deviation correction factor model according to the quality grade of each POS data, and correcting the POS data according to the deviation correction reference of the deviation correction factor model.
A POS data deskewing system, the system comprising: the POS data resolving and fusing module, the POS data precision judging module and the POS data deviation rectifying module are arranged in the POS terminal;
the POS data resolving and fusing module is used for respectively performing POS resolving on POS data acquired at each time of the test road section and fusing the POS data with point cloud data;
the POS data precision judging module is used for extracting the quality grade obtained after POS calculation is carried out on the POS data of the test road section when the POS data is judged to need deviation correction according to the point cloud data after fusion;
and the POS data deviation rectifying module is used for establishing a deviation rectifying factor model according to the quality grade of each POS data and rectifying the deviation of each POS data according to the deviation rectifying reference of the deviation rectifying factor model.
A non-transitory computer readable storage medium, on which a computer program is stored, the computer program, when executed by a processor, implementing the steps of the POS data rectification method described above.
The invention has the beneficial effects that: the quality grade corresponding to the POS data can be generated in the POS data resolving process, the weight of the POS data acquired at the time is determined according to the quality grade, and then the POS data is corrected, a method for correcting the problem data by acquiring control points on the spot is not needed, an acquisition team is not needed to acquire control points on the spot, the operation efficiency can be greatly improved, and the purposes of reducing the cost and increasing the efficiency are achieved.
On the basis of the technical scheme, the invention can be further improved as follows:
further, in the step 2, the method for determining whether the POS data needs to be corrected according to each of the fused point cloud data includes:
and judging whether the difference value of the coordinates of any same point in the fused point cloud data exceeds a set threshold value, if so, judging that the POS data acquired by the test road section needs to be corrected, and if not, judging that the POS data acquired by the test road section does not need to be corrected.
And the set threshold is set according to the length of the test road section and the precision of the acquisition equipment.
And when the POS data acquired by the test road section do not need to be corrected, finishing the correction process of the POS data of the test road section.
The step 3 of establishing the deviation correction factor model according to the quality grade of each POS data comprises the following steps:
and determining a weight corresponding to each POS data according to the quality grade of each POS data, determining the position moving distance of each POS data according to the weight, and determining the deviation rectifying reference of the deviation rectifying factor model.
Determining a deviation correction reference of the deviation correction factor model comprises the following steps:
when one of the quality grades of the POS data is 1, taking the POS data with the quality grade of 1 as the deviation correcting reference;
when more than one of the quality grades of each POS data is 1 or no 1, the weight of n POS data is 1/n, and each POS data is moved and combined according to the corresponding weight and then is used as the deviation correction reference of the POS data.
When n of the quality grades of the POS data are 1 and n is more than or equal to 2, the weight of the n POS data is 1/n;
and when the quality grade of each POS data does not have 1, the weight of the quality grade of each POS data is the ratio of the quality grade to the sum of the quality grades of each POS data.
In the step 1, POS data are collected twice on the test road section;
the process of correcting the POS data according to the correction reference of the correction factor model in the step 3 comprises the following steps:
when one of the quality grades of the two POS data is 1 and the quality grade of the other POS data is any one of 2-6, determining one POS data with the quality grade of 1 as a deviation correction reference, and moving the other POS data to the deviation correction reference;
when the quality grades of the two POS data are both 1, taking the central positions of the two POS data as deviation correcting references;
and when the quality grades of the two POS data are not 1, moving and combining the POS data according to the weight values of the POS data to be used as a deviation correcting reference of the POS data.
The beneficial effect of adopting the further scheme is that: and judging whether the POS data needs to be corrected or not according to whether the difference value of the coordinates of any same point in the fused point cloud data exceeds a threshold value or not, wherein the set threshold value of the difference value can be flexibly set according to the actual conditions such as the length of a test road section, the precision of acquisition equipment and the like, and the correction process of the POS data is finished when the POS data does not need to be corrected, so that the processing time is reduced.
Drawings
FIG. 1 is a flow chart of a POS data deviation rectifying method provided by the present invention;
FIG. 2 is a flowchart illustrating a POS data error correction method according to an embodiment of the present invention;
FIG. 3 is a block diagram of a POS data error correction system according to an embodiment of the present invention.
In the drawings, the components represented by the respective reference numerals are listed below:
1. the POS data resolving and fusing module, the POS data precision judging module and the POS data deviation rectifying module are respectively connected with the POS data resolving and fusing module, the POS data precision judging module and the POS data deviation rectifying module.
Detailed Description
The principles and features of this invention are described below in conjunction with the following drawings, which are set forth by way of illustration only and are not intended to limit the scope of the invention.
As shown in fig. 1, which is a flowchart of a POS data deviation rectifying method provided by the present invention, as shown in fig. 1, the method includes:
And 2, when the POS data are judged to need deviation correction according to the fused point cloud data, extracting the POS data of the test road section to obtain a quality grade after POS calculation.
And 3, establishing a deviation correction factor model according to the quality grade of each POS data, and correcting the deviation of each POS data according to the deviation correction reference of the deviation correction factor model.
The POS data calculation is to process and calculate the acquired sensor data and provide data with high precision, real-time display and direction record, the POS data calculation is performed through special software, a quality grade corresponding to the POS data is generated in the calculation process, the quality grade is represented by any natural number in numbers 1-6, and the smaller the numerical value is, the higher the credibility of the POS data is. According to the POS data deviation rectifying method provided by the invention, the quality grade corresponding to the POS data can be generated in the POS data resolving process, the weight of the POS data acquired at this time is determined according to the quality grade so as to rectify the POS data, the problem data is not required to be rectified by acquiring a control point on the spot, the operation efficiency can be greatly improved, and the purposes of reducing the cost and increasing the efficiency are achieved.
Example 1
The POS data is position data acquired by a GPS and inertial navigation data, the point cloud data does not have coordinate information, the process of giving the point cloud data coordinate information is to perform fusion processing on the POS data and the point cloud data, and the point cloud data containing the coordinate information is obtained after the POS data acquired for many times are respectively fused with the point cloud data.
And 2, when the POS data are judged to need deviation correction according to the fused point cloud data, extracting the POS data of the test road section to obtain a quality grade after POS calculation.
Specifically, the method for judging whether the POS data needs to be rectified according to the fused point cloud data comprises the following steps: and judging whether the difference value of the coordinates of any same point in the fused point cloud data exceeds a set threshold value, if so, judging that the POS data acquired by the test road section needs to be corrected, and if not, judging that the POS data acquired by the test road section does not need to be corrected.
In a specific testing process, POS data are generally collected twice, the two POS data are respectively fused with the point cloud data, after coordinate information is provided for the point cloud data, a difference value may exist between coordinates of the same point of the two fused point cloud data, a set threshold value of the difference value can be flexibly set according to practical conditions such as the length of a testing section and the precision of collecting equipment, namely when the difference value of coordinates of any same point in each fused point cloud data is small, the precision of the fused point cloud data is not a problem, when the difference value of coordinates of any same point in each fused point cloud data is large, the precision of the fused point cloud data is a problem, and the POS data on the testing section needs to be corrected.
And further, when the POS data acquired by the test road section is judged not to need to be corrected, finishing the correction process of the POS data of the test road section.
And 3, establishing a deviation correction factor model according to the quality grade of each POS data, and correcting the deviation of each POS data according to the deviation correction reference of the deviation correction factor model.
Specifically, the establishing of the deviation correction factor model according to the quality grade of each POS data includes: and determining a weight corresponding to each POS data according to the quality grade of each POS data, determining the position moving distance of each POS data according to the weight, and determining the deviation rectifying reference of the deviation rectifying factor model.
The rule for determining the deviation correcting reference is as follows: and when one of the quality grades of the POS data is 1, taking the POS data with the quality grade of 1 as a deviation correction reference.
When n of the quality grades of each POS data is 1 and n is more than or equal to 2, the weight of the n POS data with the quality grade of 1 is 1/n, and the n POS data with the quality grade of 1 are moved and combined according to the corresponding weight and then serve as the POS data as the deviation correction reference.
And when the quality grade of each POS data does not have 1, the weight of the quality grade of each POS data is the ratio of the quality grade to the sum of the quality grades of each POS data, and each POS data is moved and combined according to the corresponding weight and then is used as the deviation rectifying reference of the POS data.
In practical application, generally, two POS data are collected, taking the two POS data collection as an example:
when one of the quality grades of the two POS data is 1 and the quality grade of the other POS data is any one of 2-6, the coordinate of the POS data with the quality grade of 1 is considered to be a pair, the coordinate is considered as a deviation correction reference, and the other POS data is moved to the deviation correction reference.
When the quality grades of the two POS data are both 1, the quality of the two POS data is good, but the difference value of the coordinates after the point cloud data of the two POS data are fused exceeds a set threshold value, and the two POS data still have the precision problem, so that the two POS data are respectively moved by half of the distance difference of the two POS data, and the central positions of the two POS data are used as deviation correction reference.
When the quality grades of the two POS data are not 1, the POS data are moved according to the weight values of the two POS data, the POS data with the lower quality grade are accurate, the moving distance is shorter, and the two POS data are moved and combined to be used as the deviation-correcting reference of the POS data.
Specifically, the correcting the POS data according to the correction reference of the correction factor model includes: and correcting each POS data to the deviation correcting reference.
Example 2
And the POS data resolving and fusing module 1 is used for respectively performing POS resolving on the POS data acquired at each time of the test road section and then fusing the POS data with the point cloud data.
And the POS data precision judging module 2 is used for extracting the POS data of the test road section to obtain a quality grade after POS calculation when the POS data need to be corrected according to the fused point cloud data.
And the POS data deviation rectifying module 3 is used for establishing a deviation rectifying factor model according to the quality grade of each POS data and rectifying the deviation of each POS data according to the deviation rectifying reference of the deviation rectifying factor model.
Through the above description of the embodiments, those skilled in the art will clearly understand that each embodiment can be implemented by software plus a necessary general hardware platform, and certainly can also be implemented by hardware. With this understanding in mind, the above-described technical solutions may be embodied in the form of a software product, which can be stored in a computer-readable storage medium such as ROM/RAM, magnetic disk, optical disk, etc., and includes instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to execute the methods described in the embodiments or some parts of the embodiments.
The above description is only for the purpose of illustrating the preferred embodiments of the present invention and is not to be construed as limiting the invention, and any modifications, equivalents, improvements and the like that fall within the spirit and principle of the present invention are intended to be included therein.
Claims (7)
1. A method for correcting a POS data error, the method comprising:
step 1, POS data acquired at each time of a test road section are respectively subjected to POS resolving and then fused with point cloud data;
step 2, when the POS data need to be rectified according to the fused point cloud data, extracting the POS data of the test road section to obtain a quality grade after POS resolving;
step 3, establishing a deviation correction factor model according to the quality grade of each POS data, and correcting the deviation of each POS data according to the deviation correction reference of the deviation correction factor model;
the step 3 of establishing the deviation correction factor model according to the quality grade of each POS data comprises the following steps:
determining a weight corresponding to each POS data according to the quality grade of each POS data, determining the position moving distance of each POS data according to the weight, and determining the deviation rectifying reference of the deviation rectifying factor model;
determining a deviation correction reference of the deviation correction factor model comprises the following steps:
when one of the quality grades of the POS data is 1, taking the POS data with the quality grade of 1 as the deviation correcting reference;
when n of the quality grades of the POS data are 1 and n is more than or equal to 2, the weight of the n POS data is 1/n;
when the quality grade of each POS data does not have 1, the weight of the quality grade of each POS data is the ratio of the quality grade to the sum of the quality grades of each POS data;
and moving and combining each POS data according to the corresponding weight value to be used as a deviation correcting reference of the POS data.
2. The method according to claim 1, wherein in the step 2, the method for determining whether the POS data needs to be corrected according to the fused point cloud data comprises:
and judging whether the difference value of the coordinates of any same point in the fused point cloud data exceeds a set threshold value, if so, judging that the POS data acquired by the test road section needs to be corrected, and if not, judging that the POS data acquired by the test road section does not need to be corrected.
3. The method of claim 2, wherein the set threshold is set based on a length of the test segment and an acquisition device accuracy.
4. The method of claim 2, wherein when it is determined that the POS data collected by the test road segment does not require rectification, the rectification process of the POS data of the test road segment is ended.
5. The method of claim 1, wherein in step 1, POS data is collected twice for the test segment;
the process of correcting the POS data according to the correction reference of the correction factor model in the step 3 comprises the following steps:
when one of the quality grades of the two POS data is 1 and the quality grade of the other POS data is any one of 2-6, determining one POS data with the quality grade of 1 as a deviation correction reference, and moving the other POS data to the deviation correction reference;
when the quality grades of the two POS data are both 1, taking the central positions of the two POS data as deviation correcting references;
and when the quality grades of the two POS data are not 1, moving and combining the POS data according to the weight values of the POS data to be used as a deviation correcting reference of the POS data.
6. A POS data deskewing system, comprising: the POS data resolving and fusing module, the POS data precision judging module and the POS data deviation rectifying module are arranged in the POS terminal;
the POS data resolving and fusing module is used for respectively performing POS resolving on POS data acquired at each time of the test road section and fusing the POS data with point cloud data;
the POS data precision judging module is used for extracting the quality grade obtained after POS calculation is carried out on the POS data of the test road section when the POS data is judged to need deviation correction according to the point cloud data after fusion;
the POS data deviation rectifying module is used for establishing a deviation rectifying factor model according to the quality grade of each POS data and rectifying the deviation of each POS data according to the deviation rectifying reference of the deviation rectifying factor model;
the step of establishing the deviation correction factor model according to the quality grade of each POS data comprises the following steps:
determining a weight corresponding to each POS data according to the quality grade of each POS data, determining the position moving distance of each POS data according to the weight, and determining the deviation rectifying reference of the deviation rectifying factor model;
determining a deviation correction reference of the deviation correction factor model comprises the following steps:
when one of the quality grades of the POS data is 1, taking the POS data with the quality grade of 1 as the deviation correcting reference;
when n of the quality grades of the POS data are 1 and n is more than or equal to 2, the weight of the n POS data is 1/n;
when the quality grade of each POS data does not have 1, the weight of the quality grade of each POS data is the ratio of the quality grade to the sum of the quality grades of each POS data;
and moving and combining each POS data according to the corresponding weight value to be used as a deviation correcting reference of the POS data.
7. A non-transitory computer readable storage medium, having a computer program stored thereon, wherein the computer program, when executed by a processor, implements the steps of the POS data deskewing method according to any one of claims 1 to 6.
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