CN118363017A - Airborne sounding LiDAR setting angle deviation checking method and system - Google Patents
Airborne sounding LiDAR setting angle deviation checking method and system Download PDFInfo
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- G01S7/00—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00
- G01S7/48—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S17/00
- G01S7/497—Means for monitoring or calibrating
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- G—PHYSICS
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- G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
- G01C13/00—Surveying specially adapted to open water, e.g. sea, lake, river or canal
- G01C13/008—Surveying specially adapted to open water, e.g. sea, lake, river or canal measuring depth of open water
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- G01C15/00—Surveying instruments or accessories not provided for in groups G01C1/00 - G01C13/00
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- 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
- G01C21/1652—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 with ranging devices, e.g. LIDAR or RADAR
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- G—PHYSICS
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- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- G01S17/00—Systems using the reflection or reradiation of electromagnetic waves other than radio waves, e.g. lidar systems
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Abstract
The invention belongs to the technical field of ocean mapping, and discloses a method and a system for detecting and correcting airborne sounding LiDAR (light detection and ranging) setting angle deviation. The method constructs an airborne sounding LiDAR point position reduction model taking optical zero error correction into consideration, and lays a foundation for airborne sounding LiDAR setting angle deviation correction; constructing a pitch angle self-checking model of a single-navigation-zone uncontrolled plane, and performing airborne sounding LiDAR pitch angle self-checking; and constructing a bidirectional navigation belt uncontrolled vector minimized roll angle self-checking model, and performing airborne sounding LiDAR roll angle self-checking. The method solves the problem of insufficient accuracy of the airborne sounding LiDAR measurement point cloud, can provide technical support for the fine processing of the airborne LiDAR sounding data, can also provide high-accuracy data for the underwater topography measurement of areas such as coastal zones, and promotes the research and application development of the fields such as ocean science, ocean mapping and the like.
Description
Technical Field
The invention belongs to the technical field of ocean mapping, and particularly relates to a method and a system for detecting and correcting airborne sounding LiDAR (light detection and ranging) setting angle deviation.
Background
The airborne LiDAR sounding (Airborne LiDAR Bathymetry, ALB) is an emerging underwater topography measurement technology integrating a global navigation satellite system, an inertial navigation system and laser ranging, has the characteristics of high measurement precision, high efficiency, strong maneuverability, amphibious and the like, and can effectively fill the water depth measurement gap of a shallow water area of a coastal zone. However, when the airborne LiDAR sounding system is integrally installed, the positioning accuracy of the laser foot point can be seriously affected by the placement angle deviation generated between the laser scanner and the inertial navigation system and the lever arm error between the phase center of the global navigation satellite system and the inertial navigation system. The lever arm error can be accurately obtained by high-precision observation and the like, but the placement angle deviation cannot be accurately obtained by direct observation. Therefore, an effective method must be employed to correct the placement angle error. The airborne sounding LiDAR positioning angle deviation checking device can solve the problem that the accuracy of airborne sounding LiDAR measurement point cloud is insufficient, can provide technical support for the fine processing of airborne sounding LiDAR data, can also provide high-accuracy data for underwater topography measurement in areas such as coastal zones, and promotes research and application development in the fields such as ocean science and ocean mapping.
The existing method mainly comprises the following steps: the step geometry method is simple and convenient to operate, but is easy to generate manual interpretation errors; the method utilizes the inter-band line characteristics to carry out the calibration of the angular deviation, is simple to operate, is easy to extract and has unstable calibration result; the method can better reduce the deviation of the setting angle, but the method is difficult to determine at the same name point and has higher requirement on the point density; the reference plane feature constraint method is easy to extract features and high in efficiency, but requires known high-precision calibration field data.
Through the above analysis, the problems and defects existing in the prior art are as follows: in the prior art, a site checking control point is not easy to acquire, and the positioning angle is difficult to correct due to the difficulty in determining sparse homonymous features of the measuring point cloud, so that the accuracy of the airborne sounding LiDAR measuring point cloud is low.
Disclosure of Invention
In order to overcome the problems in the related art, the disclosed embodiment of the invention provides an airborne sounding LiDAR (light detection and ranging) setting angle deviation checking method and system, and particularly relates to an airborne sounding LiDAR setting angle deviation checking method oriented to sparse point cloud field-free control.
The technical scheme is as follows: an airborne sounding LiDAR setting angle deviation checking method comprises the following steps:
S1: constructing an airborne sounding LiDAR point position reduction model considering optical zero error correction, and using the model for detecting and correcting the positioning angle deviation of the airborne sounding LiDAR;
S2: constructing a pitch angle self-checking model of a single-navigation-zone uncontrolled plane, and performing airborne sounding LiDAR pitch angle self-checking;
s3: and constructing a bidirectional navigation belt uncontrolled vector minimized roll angle self-checking model, and performing airborne sounding LiDAR roll angle self-checking.
In step S1, an airborne sounding LiDAR point location calculation model is constructed that takes into account optical zero error correction, comprising:
Step 1.1: before the calibration of the positioning angle deviation, an airborne sounding LiDAR point position calculation model is established according to the mechanical structure of an airborne sounding LiDAR system, a reflected light ray direction vector is fused with aerial inclined distance information to obtain a laser foot point coordinate, and coordinate information is converted into a WGS-84 coordinate system by fusion of pose data;
Step 1.2: performing reflected ray direction vector Is calculated;
step 1.3: extracting homonymous angular points of a building as control points, and calculating distance differences of homonymous angular points Defining a distance difference objective function；
Step 1.4: calculating the rotation angle of the code wheel;
Step 1.5: the zero scale of the code disc corresponds to the optical zero, and the installation deviation of the optical zero is corrected.
In step 1.1, fusing pose data converts coordinate information into a WGS-84 coordinate system, and the expression is:
；
In the method, in the process of the invention, For WGS-84 coordinates fusing pose data,For the conversion of the local horizontal coordinate system to the WGS-84 coordinate system rotation matrix,For the transformation of the carrier coordinate system into a local horizontal coordinate system rotation matrix,The scanner coordinate system is converted to a carrier coordinate system rotation matrix,The placement angle error correction rotation matrix is used,The distance is measured for the laser to the target point,To drive the conversion of the motor coordinate system to the scanner coordinate system rotation matrix,Is the reflected ray direction vector.
In step 1.2, a reflected light direction vector is performedIs expressed as:
；
In the method, in the process of the invention, In order to reflect the direction vector of the light,For the included angle between the reflecting rotating mirror and the vertical plane of the rotating shaft of the driving motor,For the rotation angle of the code wheel,Is the included angle between the incidence direction of laser and the rotating shaft of the driving motor.
In step 1.3, the distance difference objective functionThe expression is:
；
In the method, in the process of the invention, For the distance difference objective function, for the distance difference index,For the number of the same-name point pairs,Is the firstFor the distance difference between the points of the same name,Is the distance difference threshold value of the same name point.
In step 1.4, the rotation angle of the code wheel is calculated, and the expression is:
；
In the method, in the process of the invention, For the rotation angle of the code wheel,For the code wheel reading,The resolution of the code disc;
In step 1.5: correcting the installation deviation of the optical zero position, wherein the expression is as follows:
；
In the method, in the process of the invention, In order to correct the post-code wheel reading,Is the initial value of the optical zero.
In step S2, a pitch angle self-checking model of a single-navigation-zone uncontrolled plane is constructed, and airborne depth detection LiDAR pitch angle self-checking is performed, including:
Step 2.1: for two layers of parallel point clouds layered by pitch angle error, performing plane fitting by using a RANSAC algorithm, randomly selecting 3 non-collinear points to construct a plane model, calculating a plane equation corresponding to the 3 points, and for each point in the point cloud Calculate its vertical distance to the planeTo determine the inner point and set the iteration numberAnd a distance thresholdDetermining two plane parametersAndAnd calculate the distance between two planes；
Step 2.2: will beAs an unknown number, linearizing to perform taylor expansion and reserving a primary term;
Step 2.3: calculating the distance error between two planes;
Step 2.4: when the least squares adjustment model constraint condition of the expression At the minimum, obtaining a normal equation;
step 2.5: and obtaining a pitch angle error parameter from a normal equation.
In step 2.1, the distance between the two planes is calculatedThe expression is:
；
In the method, in the process of the invention, In the event of a pitch angle error,Respectively fitting and determining two plane parameters based on the re-calculated point cloud after adding the pitch angle error,The coefficients of the plane equations x, y and z are respectively;
In step 2.2, the linearization process of the above formula (6) is performed with taylor expansion and the term is reserved once, and the expression is:
；
In the method, in the process of the invention, In order to correct the post-function value,Is a function value in the initial state,As a function ofFor pitch angle errorIs a partial derivative of (c).
In step 2.3, a distance error equation between two planes is calculated, expressed as:
；
In the method, in the process of the invention, Is the distance error between the two planes,For the matrix of unknown coefficient when the taylor formula is developed,Is the distance between the two planes,To be solved for pitch angle error；
In step 2.4, the normal equation is:
；
In the method, in the process of the invention, Is the transposed matrix of b and,Is a weight array;
In step 2.5, the pitch angle error parameter calculation formula is:
。
in step S3, constructing a roll angle self-checking model with a bidirectional navigation belt uncontrolled vector minimization, including:
Step 3.1: solving the normal vector of the two-way navigation area offset two planes caused by the roll angle error by using a formula (11) AndCalculating the module length, wherein the expression is:
；
step 3.2: calculating the sine value of the included angle of the normal vectors of the two planes through a formula (12), wherein the expression is as follows:
；
In the method, in the process of the invention, Is the included angle between two plane normal vectors;
step 3.3: calculating a roll angle error, wherein the expression is as follows:
；
In the method, in the process of the invention, Is roll angle error.
Another object of the present invention is to provide an airborne sounding LiDAR positioning angular deviation checking system, which implements the airborne sounding LiDAR positioning angular deviation checking method, the system comprising:
The point position reduction model construction module is used for constructing an airborne sounding LiDAR point position reduction model taking optical zero error correction into consideration and is used for detecting and correcting the positioning angle deviation of the airborne sounding LiDAR;
the pitch angle self-checking model construction module is used for constructing a pitch angle self-checking model of a single-navigation-zone non-control plane and carrying out airborne sounding LiDAR pitch angle self-checking;
the roll angle self-checking model construction module is used for constructing a roll angle self-checking model with the two-way navigation belt uncontrollable vector minimized and carrying out airborne sounding LiDAR roll angle self-checking.
By combining all the technical schemes, the invention has the following beneficial effects: according to the method and the system for detecting and correcting the positioning angle deviation of the airborne sounding LiDAR, the optical zero error correction model taking the difference between the detected and the famous actor point distance into consideration is constructed, so that the optical zero error correction of a code wheel device in the airborne sounding LiDAR system is carried out, and a foundation is laid for detecting and correcting the positioning angle; then, a positioning angle deviation calibration model based on plane feature constraint is constructed, and a random sampling consistency and a least square adjustment method are combined, and pitch angle deviation is calibrated by taking the minimum distance between two planes of a single-navigation-zone layering as the constraint; and correcting the roll angle deviation by taking the minimum included angle of the normal vectors of the two planes of the bidirectional navigation belt as the constraint. The airborne sounding LiDAR positioning angle deviation checking and correcting device solves the problem that the accuracy of airborne sounding LiDAR measurement point clouds is insufficient, can provide technical support for the fine processing of airborne sounding LiDAR sounding data, can also provide high-accuracy data for underwater topography measurement in areas such as coastal zones, and promotes research and application development in the fields such as ocean science and ocean mapping.
The invention can reduce the setting angle error caused by the fact that the coordinate systems of the laser scanning system and the inertial measurement unit system in the airborne laser radar cannot be aligned strictly or parallel due to the limitation of the manufacturing process, and improve the positioning precision of the laser foot points; the depth measurement precision standard of ocean engineering topography measurement standard is met, so that the on-water and underwater integrated high-precision airborne LiDAR sounding three-dimensional point cloud is obtained, a high-precision submarine topography model can be built, and powerful support is provided for ocean resource development, ocean environment protection and the like.
Compared with the method for calibrating the positioning angle deviation, which needs to calibrate the known control points of the field or high-precision three-dimensional data, the method has no specific requirement on the field and can finish the calibration of the positioning angle deviation without calibrating the known data of the field, and compared with a land laser radar, an ALB system has the advantages that the density of points is sparse due to low point frequency, and the method provides a positioning angle deviation calibration scheme aiming at sparse point clouds.
Drawings
The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the disclosure and together with the description, serve to explain the principles of the disclosure;
FIG. 1 is a flow chart of a method for calibrating the angular deviation of airborne sounding LiDAR positioning provided by an embodiment of the invention;
FIG. 2 is a schematic diagram of a calibration of angular misalignment of a device according to an embodiment of the present invention;
FIG. 3 is a block diagram of an airborne sounding LiDAR system in the present invention;
FIG. 4 is a road hierarchy diagram resulting from pitch angle errors in the present invention;
FIG. 5 is a graph of the offset due to roll angle error;
FIG. 6 is a cross-sectional view of road point clouds before and after pitch calibration;
FIG. 7 is a cross-sectional view of a road point cloud before and after roll angle calibration;
FIG. 8 is a cross-sectional view of a roof point cloud before and after heading angle calibration;
FIG. 9 is a map 20KU versus RTK and SBES points;
FIG. 10 is a chart of the map 20KU and RTK homonymous point elevation differences in the map 20KU and validation data homonymous point elevation difference distribution;
FIG. 11 is a chart showing the difference in elevation between map 20KU and SBES points of interest in the distribution of map 20KU and verification data points of interest.
Detailed Description
In order that the above objects, features and advantages of the invention will be readily understood, a more particular description of the invention will be rendered by reference to the appended drawings. In the following description, numerous specific details are set forth in order to provide a thorough understanding of the present invention. The invention may be embodied in many other forms than described herein and similarly modified by those skilled in the art without departing from the spirit or scope of the invention, which is therefore not limited to the specific embodiments disclosed below.
The innovation point of the invention is that: aiming at the problems that a control point is not easy to acquire in field calibration in areas such as coastal zones, homonymous features are difficult to determine due to sparse point clouds of depth measurement radars, and the like, an airborne depth measurement LiDAR setting angle deviation calibration method for sparse point clouds/field-control-free areas is provided. Firstly, an optical zero error correction model taking the same famous actor point distance difference into consideration is constructed, so that the optical zero error correction of a code wheel device in an ALB system is carried out, and a foundation is laid for the correction of the setting angle; then, by constructing a positioning angle deviation calibration model based on plane feature constraint and combining random sampling consistency (Random Sample Consensus, RANSAC) and a least square adjustment method, the minimum distance between two planes of a single-navigation-zone layering is taken as constraint, and pitch angle deviation is calibrated; and correcting the roll angle deviation by taking the minimum included angle of the normal vectors of the two planes of the bidirectional navigation belt as the constraint.
In embodiment 1, as shown in fig. 1, the method for calibrating the airborne sounding LiDAR positioning angle deviation provided by the embodiment of the invention comprises the following steps:
S1: constructing an airborne sounding LiDAR point position reduction model considering optical zero error correction, and using the model for detecting and correcting the positioning angle deviation of the airborne sounding LiDAR;
S2: constructing a pitch angle self-checking model of a single-navigation-zone uncontrolled plane, and performing airborne sounding LiDAR pitch angle self-checking;
s3: and constructing a bidirectional navigation belt uncontrolled vector minimized roll angle self-checking model, and performing airborne sounding LiDAR roll angle self-checking.
In step S1 of the embodiment of the present invention, the airborne sounding LiDAR (Airborne LiDAR Bathymetry, ALB) system mainly includes a laser, a reflecting mirror, a driving motor, an encoder scale, and the like, as shown in fig. 3. In order to construct an ALB system point location calculation model, the center of a reflection rotating mirror is taken as a coordinate origin, the flight direction of an airplane is taken as a Y axis, the vertical direction of the Y axis is taken as an X axis, and a right hand coordinate system of a scanner is vertically and upwards established in a Z axis; on the basis, a Y-axis of a scanner coordinate system is taken as a rotating shaft, the scanner coordinate system is rotated anticlockwise by an angle alpha, a driving motor coordinate system is established, at the moment, a Z-axis is changed into a driving motor rotating shaft, and the Y-axis is still the flight direction of the aircraft. The characteristic of high resolution of the code wheel in the ALB system can cause larger influence on the point cloud precision due to small deviation, and further influences the correction of the placement angle deviation, so that the optical zero error of the code wheel is necessary to be corrected before the correction of the placement angle deviation, the scanning track of the ALB system is in an elliptical-like shape in an ideal state, and coordinate points in a coordinate system of a scanner are symmetrically distributed relative to a Y-axis.
In step S1 of the embodiment of the present invention, constructing an airborne sounding LiDAR point location calculation model that allows for optical zero error correction includes:
Step 1.1: before the calibration of the angular deviation, an airborne sounding LiDAR (Airborne LiDAR Bathymetry, ALB) point position calculation model is established according to the mechanical structure of the airborne sounding LiDAR system, the reflected light ray direction vector is fused with the aerial oblique distance information to obtain the laser foot point coordinates, and then the coordinate information is converted into a WGS-84 coordinate system by fusing pose data, as shown in a formula (1) provided by the innovation of the invention:
；
In the method, in the process of the invention, For WGS-84 coordinates fusing pose data,For the conversion of the local horizontal coordinate system to the WGS-84 coordinate system rotation matrix,For the transformation of the carrier coordinate system into a local horizontal coordinate system rotation matrix,The scanner coordinate system is converted to a carrier coordinate system rotation matrix,The placement angle error correction rotation matrix is used,The distance is measured for the laser to the target point,To drive the conversion of the motor coordinate system to the scanner coordinate system rotation matrix,Is the reflected ray direction vector.
Step 1.2: the calculation mode of the reflected light ray direction vector V 1 is shown in a formula (2) which is innovatively proposed by the invention:
；
In the method, in the process of the invention, In order to reflect the direction vector of the light,For the included angle between the reflecting rotating mirror and the vertical plane of the rotating shaft of the driving motor,For the rotation angle of the code wheel,Is the included angle between the incidence direction of laser and the rotating shaft of the driving motor.
Step 1.3: extracting homonymous angular points of a building as control points, and calculating distance differences of homonymous angular pointsDefining a distance difference objective function; Formula (3) as innovatively proposed by the present invention:
；
In the method, in the process of the invention, For the distance difference objective function, for the distance difference index,For the number of the same-name point pairs,Is the firstFor the distance difference between the points of the same name,Is the distance difference threshold value of the same name point.
Step 1.4: the rotation angle of the code disc is calculated through a formula (4) provided by the innovation of the invention:
；
In the method, in the process of the invention, For the rotation angle of the code wheel,For the code wheel reading,The resolution of the code disc;
Step 1.5: the zero scale of the code disc directly corresponds to the optical zero, but the optical zero is corrected by utilizing the formula (5) provided by the innovation of the invention due to the installation deviation:
；
In the method, in the process of the invention, In order to correct the post-code wheel reading,Is the initial value of the optical zero.
In step S2 of the embodiment of the present invention, in the airborne LiDAR sounding system, the influence of the pitch angle on the scanning measurement is most remarkable, and the error causes layering of the ground object along the flight direction, which is particularly obvious in the measurement of the unidirectional navigation belt. Therefore, the pitch angle error is corrected first, and only the unidirectional tape is used for correction based on the characteristics thereof, so as to enhance the stability of the calibration process. Compared with the point characteristic and the line characteristic, the plane characteristic has geometric stability and is easy to detect and identify, in the ALB system, the pitch angle can cause layering phenomenon of a straight road to form two layers of parallel point clouds caused by pitch angle errors, and the two layers of parallel point clouds are shown in fig. 4. And respectively carrying out plane fitting on two layers of parallel point clouds caused by pitch angle errors based on the RANSAC algorithm, constructing a least square adjustment model with the distance between planes as constraint on the basis of the plane fitting, and iteratively solving the pitch angle errors.
The method for constructing the pitch angle self-checking model of the single-navigation-zone uncontrolled plane comprises the following steps of:
Step 2.1: performing plane fitting on two layers of parallel point clouds layered due to pitch angle errors by using a RANSAC algorithm, randomly selecting 3 non-collinear points to construct a plane model, calculating a plane equation corresponding to the 3 points, and for each point in the point clouds Calculating its vertical distance d from plane to determine internal point, setting iteration numberAnd a distance thresholdDetermining two plane parametersAndCalculating the distance between planes by using the formula (6) innovatively provided by the invention：
；
In the method, in the process of the invention,In the event of a pitch angle error,Respectively fitting and determining two plane parameters based on the re-calculated point cloud after adding the pitch angle error,The coefficients of the plane equations x, y and z are respectively;
Step 2.2: will be As an unknown number, performing taylor expansion on the linearization processing and reserving a primary term to obtain a formula (7) provided by the innovation of the invention:
；
In the method, in the process of the invention, In order to correct the post-function value,Is a function value in the initial state,As a function ofFor pitch angle errorIs a partial derivative of (c).
Step 2.3: theoretically, the distance between two planes is 0, but because the pitch angle is not actually 0, an error equation formula (8) provided by the innovation of the invention is obtained:
；
In the method, in the process of the invention, Is the distance error between the two planes,For the matrix of unknown coefficient when the taylor formula is developed,Is the distance between the two planes,To be solved for pitch angle error；
Step 2.4: when expressed asAt minimum, a normal equation is obtained, as shown in a formula (9) provided by the innovation of the invention:
；
In the method, in the process of the invention, Is the transposed matrix of b and,Is a weight array;
In step 2.5, the pitch angle error parameter calculation formula is:
。
In step S3 of the present embodiment, the roll angle may cause the scan plane to incline and cause the ground object to deviate on the vertical plane of the flight direction. Manual inspection typically visually estimates the distance between the clouds of straight road section points on the round-trip overlapping swaths, but is susceptible to subjective visual deviations. And iteratively solving the roll angle error by taking the minimum normal vector included angle between the two planes as a constraint. By extracting point clouds of the overlapping area of the straight road of the back-and-forth navigation belt, fitting the point cloud plane by using a RANSAC algorithm, solving the normal vector included angle between the two planes, and iterating the process until the roll angle reaches the optimal estimated value, wherein half of the included angle is the calculated roll angle as shown in figure 5. To improve the robustness of the calculation, a sine function is used to calculate the angle between the two planes.
The construction of the transverse roll angle self-checking model with the two-way navigation belt uncontrollable vector minimization comprises the following steps:
Step 3.1: solving the normal vector of the two-way navigation area offset two planes caused by the roll angle error by using a formula (11) AndCalculating the module length:
；
step 3.2: calculating the sine value of the normal vector included angle of the two planes through a formula (12):
；
In the method, in the process of the invention, Is the included angle between two plane normal vectors;
step 3.3: the roll angle error is calculated as shown in equation (13):
；
In the method, in the process of the invention, Is roll angle error.
The course angle correction is performed by using a conventional correction method for correcting a herringbone tip house with a ridge line perpendicular to the flight direction in the course.
According to the embodiment, the method can finish the calibration of the setting angle deviation without taking the known high-precision three-dimensional calibration field as a reference, and compared with the planar features used in the point feature and line feature method, the method is easier to detect, extract and identify, can solve the problems that the on-site calibration control point is difficult to acquire, the measurement point cloud sparse homonymous features are difficult to determine and the like, and cause difficult setting angle calibration, can provide technical support for the fine processing of airborne LiDAR sounding data, can also provide high-precision data for the underwater topography measurement of areas such as coastal zones and the like, and promotes the research and application development of the fields such as ocean science, ocean mapping and the like.
Embodiment 2 of the present invention provides an airborne sounding LiDAR positioning angle deviation calibration system, comprising:
The point position reduction model construction module is used for constructing an airborne sounding LiDAR point position reduction model taking optical zero error correction into consideration and is used for detecting and correcting the positioning angle deviation of the airborne sounding LiDAR;
the pitch angle self-checking model construction module is used for constructing a pitch angle self-checking model of a single-navigation-zone non-control plane and carrying out airborne sounding LiDAR pitch angle self-checking;
the roll angle self-checking model construction module is used for constructing a roll angle self-checking model with the two-way navigation belt uncontrollable vector minimized and carrying out airborne sounding LiDAR roll angle self-checking.
In the foregoing embodiments, the descriptions of the embodiments are emphasized, and in part, not described or illustrated in any particular embodiment, reference is made to the related descriptions of other embodiments.
In order to verify the performance of the method for detecting and correcting the positioning angle deviation of the airborne sounding LiDAR facing to sparse point cloud/field-free control, the method adopts airborne LiDAR sounding data on a certain university and a certain area along the coast to verify, ALB equipment used in experiments is a Mapper 20KU developed by a certain optical precision instrument research institute, the laser center wavelength is 532nm, the laser repetition frequency is 20kHz, the scanning angle is +/-20 degrees, the laser divergence angle is 1 mrad, the weight is 6kg, EG370N high-precision inertial navigation of NovAtel is integrated, and the flying carrier is a vertical take-off and landing fixed wing unmanned plane RY-V50.
And (3) demarcating a calibration field at a certain university in 9 months 2023, and collecting the calibration data of the angular deviation of the arrangement, wherein the experimental voyage is 120m, the flying speed is 22m/s, and the point cloud density is about 10 point clouds/m 2. In order to verify the accuracy of the system measurement after the angular deviation of the ALB system is checked and calibrated, the verification data are collected along the coast of a certain area, the voyage speed is the same as the voyage speed, the overlap of the voyage band is 30%, the transparency of the zither disc is 3.7m, the maximum detection depth is about 7.55m, meanwhile, a Real-time dynamic measurement (Real-TIME KINEMATIC, RTK) control point is collected as the accuracy verification data of the land external coincidence, and the data collected by the shipboard single beam sounding (Single Beam Echo Sounder, SBES) system are the accuracy verification data of the submarine external coincidence.
Qualitative analysis of the checking result: adopting the data of a checking field of a certain university, and constructing an optical zero error correction model of a Mapper 20KU according to the method, wherein the distance threshold D is set to be 0.002m, the initial value of the optical zero is 130901, and the checked value is 130100; and on the basis, constructing a setting angle deviation calibration model, wherein the calculated pitch angle deviation is 0.85 degrees, the roll angle deviation is 0.19 degrees, the course angle deviation is 0.78 degrees, and the characteristic area point clouds before and after three setting angle error calibration are shown in fig. 6-8. As can be seen from fig. 6, the straight road before pitch angle calibration is divided into two parallel point clouds caused by pitch angle errors, and the two parallel point clouds almost coincide into one layer after pitch angle calibration; as can be seen from fig. 7, the round trip road point cloud section forms an included angle before the roll angle calibration, and the round trip road point cloud section is restored to be straight and overlapped into a whole after the calibration; as can be seen from FIG. 8, the heading angle calibration is obviously shifted from the position of the apex of the inverted V-shaped room of the return belt, and the heading angle calibration can be well overlapped into a whole. In summary, the method can be used for better reducing the angular deviation of the airborne LiDAR system.
Quantitative analysis of the checking result:
(1) And (5) evaluating the internal coincidence precision.
In order to analyze the elevation deviation between adjacent bands, the stability of the same area detected by a Mapper 20KU is verified, the elevation error of the same name point of the overlapping area of 4 bands is selected and calculated, the coincidence precision is calculated, and the statistical result is shown in Table 1.
Table 1 match accuracy alignment within Mapper 20 ku:
As shown in the table 1, the error average value and root mean square error of the overlapping area of 4 bands used in the experiment are smaller than 5.0cm, the maximum value of most of the bands is 7.1cm, the minimum value is only 0.1cm, the high internal coincidence precision of the adjacent bands of the Mapper 20KU after the calibration is proved, and the measurement result has good stability.
(2) And (5) evaluating the external coincidence precision.
In order to verify the accuracy of the map 20KU, land location accuracy comparison analysis and seabed point accuracy comparison analysis are respectively carried out by taking data acquired by the land and underwater topography mapping means (RTKs and SBES) which are mature at present as reference data, and the distribution of the points in the area is shown in figure 9.
In order to quantitatively evaluate the elevation precision of the calibrated Mapper 20KU, based on the nearest neighbor principle, searching the corresponding homonym points of the ALB point cloud and the verification data (RTK, SBES) and comparing the elevation difference, and simultaneously calculating the average absolute error (Mean Absolute Error, MAE) and the root mean square error (Root Mean Square Error, RMSE). FIG. 10 is a differential layout of the elevation of the land with the same name as the ALB and the RTK, FIG. 11 is a differential layout of the elevation of the depth of the land with the same name as the ALB and the SBES, and the statistical results are shown in Table 2. The map 20KU sounding data was denoised and refraction corrected.
Table 2 Mapper 20ku external compliance accuracy vs:
As shown in the table, the maximum value of the height difference between the point cloud acquired by the Mapper 20KU and the RTK homonymous point is 17.9 cm, the minimum value is 0.1cm, the MAE is 6.5cm, and the RMSE is 8.1cm; the maximum value of the height difference between the points with the same name as SBES is 27.6cm, the minimum value is 0.1cm, the MAE is 11.5cm, the RMSE is 13.4cm, and the depth measurement precision standard of ocean engineering measurement Specification is met: in the depth measurement, when the water depth is less than or equal to 20m, the error in the depth measurement is less than or equal to 0.2m. The method has the advantages that the arrangement angle deviation of the Mapper 20KU system is basically eliminated, the measurement accuracy is good, and the applicability of the method to the reduction of the optical zero error and the arrangement angle deviation of an ALB system is further improved.
While the invention has been described with respect to what is presently considered to be the most practical and preferred embodiments, it is to be understood that the invention is not limited to the disclosed embodiments, but on the contrary, is intended to cover various modifications, equivalents, and alternatives falling within the spirit and scope of the invention.
Claims (10)
1. An airborne sounding LiDAR setting angle deviation checking method is characterized by comprising the following steps:
S1: constructing an airborne sounding LiDAR point position reduction model considering optical zero error correction, and using the model for detecting and correcting the positioning angle deviation of the airborne sounding LiDAR;
S2: constructing a pitch angle self-checking model of a single-navigation-zone uncontrolled plane, and performing airborne sounding LiDAR pitch angle self-checking;
s3: and constructing a bidirectional navigation belt uncontrolled vector minimized roll angle self-checking model, and performing airborne sounding LiDAR roll angle self-checking.
2. The method for detecting and correcting the positioning angle deviation of the airborne sounding LiDAR according to claim 1, wherein in the step S1, an airborne sounding LiDAR point position calculation model which takes optical zero error correction into consideration is constructed, and the method comprises the following steps:
Step 1.1: before the calibration of the positioning angle deviation, an airborne sounding LiDAR point position calculation model is established according to the mechanical structure of an airborne sounding LiDAR system, a reflected light ray direction vector is fused with aerial inclined distance information to obtain a laser foot point coordinate, and coordinate information is converted into a WGS-84 coordinate system by fusion of pose data;
Step 1.2: performing reflected ray direction vector Is calculated;
step 1.3: extracting homonymous angular points of a building as control points, and calculating distance differences of homonymous angular points Defining a distance difference objective function；
Step 1.4: calculating the rotation angle of the code wheel;
Step 1.5: the zero scale of the code disc corresponds to the optical zero, and the installation deviation of the optical zero is corrected.
3. The method for checking the angular deviation of airborne sounding LiDAR according to claim 2, wherein in step 1.1, the fused pose data converts coordinate information into a WGS-84 coordinate system, and the expression is:
；
In the method, in the process of the invention, For WGS-84 coordinates fusing pose data,For the conversion of the local horizontal coordinate system to the WGS-84 coordinate system rotation matrix,For the transformation of the carrier coordinate system into a local horizontal coordinate system rotation matrix,The scanner coordinate system is converted to a carrier coordinate system rotation matrix,The placement angle error correction rotation matrix is used,The distance is measured for the laser to the target point,To drive the conversion of the motor coordinate system to the scanner coordinate system rotation matrix,Is the reflected ray direction vector.
4. The method for detecting and calibrating the angular deviation of airborne sounding LiDAR according to claim 2, wherein in step 1.2, the reflected light direction vector is performedIs expressed as:
；
In the method, in the process of the invention, In order to reflect the direction vector of the light,For the included angle between the reflecting rotating mirror and the vertical plane of the rotating shaft of the driving motor,For the rotation angle of the code wheel,Is the included angle between the incidence direction of laser and the rotating shaft of the driving motor.
5. The method for calibrating the angular deviation of airborne sounding LiDAR according to claim 2, wherein in step 1.3, the distance difference objective functionThe expression is:
；
In the method, in the process of the invention, For the distance difference objective function, for the distance difference index,For the number of the same-name point pairs,Is the firstFor the distance difference between the points of the same name,Is the distance difference threshold value of the same name point.
6. The method for checking the angular deviation of airborne sounding LiDAR according to claim 2, wherein in step 1.4, the rotation angle of the code wheel is calculated by the expression:
；
In the method, in the process of the invention, For the rotation angle of the code wheel,For the code wheel reading,The resolution of the code disc;
In step 1.5: correcting the installation deviation of the optical zero position, wherein the expression is as follows:
；
In the method, in the process of the invention, In order to correct the post-code wheel reading,Is the initial value of the optical zero.
7. The airborne depth detection LiDAR placement angle deviation checking method of claim 1, wherein in step S2, a pitch angle self-checking model of a single-navigation-zone uncontrolled plane is constructed, and airborne depth detection LiDAR pitch angle self-checking is performed, comprising:
Step 2.1: for two layers of parallel point clouds layered by pitch angle error, performing plane fitting by using a RANSAC algorithm, randomly selecting 3 non-collinear points to construct a plane model, calculating a plane equation corresponding to the 3 points, and for each point in the point cloud Calculate its vertical distance to the planeTo determine the inner point and set the iteration numberAnd a distance thresholdDetermining two plane parametersAndAnd calculate the distance between two planes；
Step 2.2: will beAs an unknown number, linearizing to perform taylor expansion and reserving a primary term;
Step 2.3: calculating the distance error between two planes;
Step 2.4: when the least squares adjustment model constraint condition of the expression At the minimum, obtaining a normal equation;
step 2.5: and obtaining a pitch angle error parameter from a normal equation.
8. The method for calibrating angular deviation of airborne sounding LiDAR according to claim 7, wherein in step 2.1, the distance between two planes is calculatedThe expression is:
；
In the method, in the process of the invention, In the event of a pitch angle error,Respectively fitting and determining two plane parameters based on the re-calculated point cloud after adding the pitch angle error,The coefficients of the plane equations x, y and z are respectively;
In step 2.2, the linearization process of the above formula (6) is performed with taylor expansion and the term is reserved once, and the expression is:
；
In the method, in the process of the invention, In order to correct the post-function value,Is a function value in the initial state,As a function ofFor pitch angle errorIs a partial derivative of (2);
in step 2.3, a distance error equation between two planes is calculated, expressed as:
；
In the method, in the process of the invention, Is the distance error between the two planes,For the matrix of unknown coefficient when the taylor formula is developed,Is the distance between the two planes,To be solved for pitch angle error；
In step 2.4, the normal equation is:
；
In the method, in the process of the invention, Is the transposed matrix of b and,Is a weight array;
In step 2.5, the pitch angle error parameter calculation formula is:
。
9. The airborne sounding LiDAR placement angle deviation checking method of claim 1, wherein in step S3, constructing a roll angle self-checking model with bi-directional navigation belt uncontrolled vector minimization comprises:
Step 3.1: solving the normal vector of the two-way navigation area offset two planes caused by the roll angle error by using a formula (11) AndCalculating the module length, wherein the expression is:
；
step 3.2: calculating the sine value of the included angle of the normal vectors of the two planes through a formula (12), wherein the expression is as follows:
；
In the method, in the process of the invention, Is the included angle between two plane normal vectors;
step 3.3: calculating a roll angle error, wherein the expression is as follows:
；
In the method, in the process of the invention, Is roll angle error.
10. An airborne depth detection LiDAR placement angle deviation checking system, characterized in that the system implements the airborne depth detection LiDAR placement angle deviation checking method according to any of claims 1-9, the system comprising:
The point position reduction model construction module is used for constructing an airborne sounding LiDAR point position reduction model taking optical zero error correction into consideration and is used for detecting and correcting the positioning angle deviation of the airborne sounding LiDAR;
the pitch angle self-checking model construction module is used for constructing a pitch angle self-checking model of a single-navigation-zone non-control plane and carrying out airborne sounding LiDAR pitch angle self-checking;
the roll angle self-checking model construction module is used for constructing a roll angle self-checking model with the two-way navigation belt uncontrollable vector minimized and carrying out airborne sounding LiDAR roll angle self-checking.
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Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116299369A (en) * | 2023-05-23 | 2023-06-23 | 山东科技大学 | Positioning angle error correction method based on airborne laser sounding system |
| CN116973895A (en) * | 2023-09-22 | 2023-10-31 | 山东科技大学 | Real-time pose correction method for laser point cloud matching |
-
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Patent Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116299369A (en) * | 2023-05-23 | 2023-06-23 | 山东科技大学 | Positioning angle error correction method based on airborne laser sounding system |
| CN116973895A (en) * | 2023-09-22 | 2023-10-31 | 山东科技大学 | Real-time pose correction method for laser point cloud matching |
Non-Patent Citations (5)
| Title |
|---|
| 时振伟;阳凡林;刘翔;齐晓迪;: "用简述机载激光测深系统及其在海底底质分类中的应用", 中国水运(下半月), no. 10, 15 October 2013 (2013-10-15) * |
| 沈蔚;帅晨甫;惠笑;栾奎峰;张华臣;马建国;: "船载移动激光三维测量系统安置角偏差检校", 测绘通报, no. 02, 25 February 2020 (2020-02-25) * |
| 谢劭峰: "国产机载 LiDAR 系统安置角误差检校方案研究", 《测绘与空间地理信息》, 30 June 2016 (2016-06-30), pages 50 - 55 * |
| 谢劭峰;刘田龙;: "国产机载LiDAR系统安置角误差检校方案研究", 测绘与空间地理信息, no. 06, 25 June 2016 (2016-06-25) * |
| 马炳武;罗志清;李志杰;: "基于国产SW-LiDAR系统的安置角检校分析", 软件, no. 02, 15 February 2018 (2018-02-15) * |
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