Parameter calibration method and related device

Abstract

The invention provides a parameter calibration method and a related device, and the method comprises the steps: obtaining the original point cloud data, collected by a laser radar scanner, of a plurality of air strips, and the flight path data, collected by a combined navigation system, within the same time, and carrying out the calibration of the parameters through employing the data, and the internal and external parameters of a laser radar scanner system; the method comprises the following steps: obtaining the distance from a laser point to a plane through a series of processing, constructing an optimization target by using the distance from the laser point to the plane, solving the optimization target to obtain a first optimization value of an internal parameter and a second optimization value of an external parameter, and when the relationship between the optimization values obtained for two consecutive times meets a preset optimization relationship, determining that the laser point is a laser point. The internal parameter and the external parameter are calibrated by utilizing the optimal value obtained at the last time, automatic and high-precision synchronous calibration of the internal parameter and the external parameter can be realized, the method does not depend on a control point target or specific natural topographic features, the adaptability is wider, the efficiency is higher, the cost is lower, and complex surveying and mapping tasks such as unmanned area surveying and mapping, disaster emergency and the like can be met.

Description

Technical Field

[0001] This application relates to the field of data processing technology, and in particular to a parameter calibration method and related apparatus. Background Technology

[0002] As a crucial device for acquiring high-precision 3D spatial information, the accuracy of the point cloud data collected by a lidar scanner system directly determines the reliability of applications such as topographic mapping, power line inspection, and disaster monitoring. Parameter calibration of the lidar scanner system is essential for eliminating systematic errors, ensuring consistency between the point cloud data and the data in real space. Reduced parameter calibration accuracy can lead to point cloud data distortion and positioning drift, severely impacting the application of the point cloud data. Therefore, parameter calibration is the core bridge between "data acquisition" and "high-precision application" for a lidar scanner system.

[0003] The parameter calibration of a LiDAR scanner system includes intrinsic parameter calibration and extrinsic parameter calibration. Intrinsic parameter calibration is completed before the LiDAR scanner leaves the factory. Extrinsic parameter calibration includes two methods: one involves manually setting up ground control point targets, collecting point cloud data through the LiDAR scanner system, manually determining the correspondence between the point cloud data and the control point targets, and then solving for the extrinsic parameters; the other involves collecting point cloud data with natural terrain features (such as roads, building facades, etc.), establishing coplanar constraints of these features, and automatically calculating the extrinsic parameters. Currently, both intrinsic and extrinsic parameter calibration have the following problems:

[0004] First, the internal parameters are calibrated only before leaving the factory. However, with long-term use of the LiDAR scanner system, the accuracy of the internal parameters will continuously decrease, leading to a decline in the accuracy of the point cloud data collected by the LiDAR scanner system. Second, the calibration of external parameters relies on manually setting up ground control point targets or obvious and regular natural terrain features, which is inefficient and unsuitable for complex and ever-changing surveying tasks. Furthermore, the calibration of internal and external parameters is carried out in a step-by-step manner. After the internal parameters are calibrated, the calibrated internal parameters are then used to calibrate the external parameters. As the accuracy of the internal parameters decreases, the accuracy of the external parameters also decreases. Summary of the Invention

[0005] In view of the above problems, this application provides a parameter calibration method and related apparatus to simultaneously calibrate the intrinsic and extrinsic parameters of a lidar scanner system, while ensuring the accuracy of both intrinsic and extrinsic parameters. The specific solution is as follows:

[0006] This application provides a parameter calibration method for a lidar scanner system, the lidar scanner system comprising an integrated navigation system, an aircraft, an inertial measurement system, and a lidar scanner, the lidar scanner being mounted on the aircraft, the method comprising:

[0007] The system acquires raw point cloud data of multiple flight strips collected by the lidar scanner and flight trajectory data collected by the integrated navigation system within the same time period. The raw point cloud data includes the distance and angle values ​​of each laser point in the multiple flight strips in the scanner coordinate system corresponding to the lidar scanner. The flight trajectory data includes the positioning coordinates and attitude angle of each laser point in the projection coordinate system at any time.

[0008] For each laser point, based on the distance measurement value, angle measurement value, attitude angle, positioning coordinates, intrinsic and extrinsic parameters of the laser radar scanner system, the first coordinate vector of the laser point in the projected coordinate system is determined.

[0009] For each laser point in the overlapping area of ​​adjacent flight strips, after constructing a plane using the laser point set of that laser point, the normal vector of that plane is obtained. The laser point set of that laser point includes that laser point and the laser points within a preset local range corresponding to that laser point that are located in the overlapping area.

[0010] For all laser points located within the overlapping region and forming a plane, the laser point features of two laser points that satisfy the preset matching conditions are determined as a matching pair using the first coordinate vector of any two laser points in the projected coordinate system. A matching pair includes two laser point features, and each laser point feature includes the observed value of the laser point.

[0011] Using the observed values ​​of each laser point in the matching pair, calculate the distance from each laser point in the matching pair to the plane;

[0012] An optimization objective is constructed using the distance from the laser point to the plane. The optimization objective is then solved to obtain the first optimized value of the intrinsic parameters and the second optimized value of the extrinsic parameters.

[0013] If the relationship between the first optimized value of the intrinsic parameter and the third optimized value of the previously determined intrinsic parameter satisfies the first preset optimization relationship, and the relationship between the second optimized value of the extrinsic parameter and the fourth optimized value of the previously determined extrinsic parameter satisfies the second preset optimization relationship, then the intrinsic parameter is calibrated using the first optimized value of the intrinsic parameter and the extrinsic parameter is calibrated using the second optimized value of the extrinsic parameter.

[0014] In one possible implementation, obtaining the normal vector of the plane after constructing the plane using the set of laser points includes:

[0015] Obtain at least three feature values ​​of the laser point set, and calculate the flatness based on the at least three feature values ​​of the laser point set;

[0016] If the flatness is greater than a preset flatness threshold, then the laser point is taken as a coordinate point on the plane, and the feature value that satisfies the preset condition among the at least three feature values ​​of the laser point set is taken as the normal vector of the plane where the laser point is located, so as to obtain the plane and the normal vector of the plane.

[0017] In one possible implementation, calculating the flatness based on at least three eigenvalues ​​of the laser point set includes:

[0018] Using formula Calculate the flatness, where p is the flatness. , and The laser point set consists of at least three characteristic values ​​that are sequentially increased in value.

[0019] The step of using the feature value that satisfies the preset condition among the at least three feature values ​​of the laser point set as the normal vector of the plane where the laser point is located includes: using the feature value with the smallest value among the three feature values ​​as the normal vector of the plane where the laser point is located.

[0020] In one possible implementation, determining the laser point features of two laser points satisfying a preset matching condition as a matching pair for all laser points located within the overlapping region and forming a plane, using the first coordinate vectors of any two laser points in the projected coordinate system, includes:

[0021] Based on the first coordinate vector of the two laser points in the projected coordinate system, the similarity of the laser point features of the two laser points is calculated, and the laser point features of the two laser points whose similarity satisfies the preset similarity condition are taken as candidate matching pairs.

[0022] Calculate the standard deviation of similarity using the similarity of all candidate matching pairs;

[0023] Based on the similarity standard deviation and the similarity of each candidate matching pair, candidate matching pairs that meet the preset matching conditions are selected as the matching pairs.

[0024] In one possible implementation, determining the first coordinate vector of each laser point in the projected coordinate system based on the ranging value, the angle value, the attitude angle, the positioning coordinates, and the intrinsic and extrinsic parameters of the lidar scanner system includes:

[0025] Based on the distance measurement value corresponding to the laser point, the angle measurement value corresponding to the laser point, and the intrinsic parameters, calculate the second coordinate vector of the laser point in the scanner coordinate system;

[0026] Based on the placement angle error in the extrinsic parameters, a first rotation matrix is ​​constructed;

[0027] Using the second coordinate vector of the laser point in the scanner coordinate system, the first rotation matrix, and the lever arm offset in the extrinsic parameters, the third coordinate vector of the laser point in the inertial measurement system coordinate system is calculated. The inertial measurement system coordinate system is the coordinate system corresponding to the inertial measurement system.

[0028] The heading angle in the attitude angle corresponding to the laser point is converged and corrected to obtain the corrected attitude angle;

[0029] Based on the corrected attitude angle, a second rotation matrix is ​​constructed from the inertial measurement system coordinate system to the projected coordinate system;

[0030] Based on the third coordinate vector of the laser point in the inertial measurement system coordinate system, the second rotation matrix, and the positioning coordinates, the first coordinate vector of the laser point in the projection coordinate system is determined.

[0031] In one possible implementation, calculating the second coordinate vector of the laser point in the scanner coordinate system based on the ranging value corresponding to the laser point, the angle value corresponding to the laser point, and the intrinsic parameter includes:

[0032] Calculate the second coordinate vector of the laser point in the scanner coordinate system using the formula: In the formula, X l Let l represent the second coordinate vector, α represent the distance value corresponding to the laser point, Δl represent the distance correction amount, and Δα represent the angle correction amount. The intrinsic parameters include the distance correction amount and the angle correction amount.

[0033] And / or,

[0034] The construction of the first rotation matrix based on the placement angle error in the extrinsic parameters includes:

[0035] Construct the first rotation matrix using the formula: In the formula, ( The ) represents the installation angle error, ΔR M Represents the first rotation matrix;

[0036] And / or,

[0037] Using the second coordinate vector of the laser point in the scanner coordinate system, the first rotation matrix, and the lever arm offset in the extrinsic parameters, the third coordinate vector of the laser point in the inertial measurement system coordinate system is calculated as follows:

[0038] Calculate the third coordinate vector of the laser point using the formula: In the formula, X IRepresents the third coordinate vector, ΔR M Let X represent the first rotation matrix. l This represents the second coordinate vector, and Δt represents the offset of the lever arm value;

[0039] And / or,

[0040] The construction of the second rotation matrix from the inertial measurement system coordinate system to the projected coordinate system based on the corrected attitude angle includes: the second rotation matrix is...

[0041] in, , , In the formula, (r, p, H) represents the corrected attitude angle, and R N Indicates the second rotation matrix;

[0042] The step of determining the first coordinate vector of the laser point in the projected coordinate system based on the third coordinate vector of the laser point in the inertial measurement system coordinate system, the second rotation matrix, and the positioning position coordinates includes: calculating the first coordinate vector of the laser point using the formula: In the formula, X I Let X represent the third coordinate vector. p Let X represent the first coordinate vector. g R represents the location coordinates. N This represents the second rotation matrix.

[0043] In one possible implementation, the observed values ​​of the laser point include: the distance measurement value corresponding to the laser point, the angle measurement value corresponding to the laser point, the normal vector of the plane, and the positioning coordinates; calculating the distance from each laser point in the matching pair to the plane using the observed values ​​of each laser point in the matching pair includes:

[0044] The distance from the laser point to the plane is calculated using the formula:

[0045] in,

[0046]

[0047] In the formula, This represents the distance from a point to a plane. This represents the normal vector in the observation value of the first laser point in the matching pair. This represents the second rotation matrix corresponding to the first laser point in the matching pair. This represents the second rotation matrix corresponding to the second laser point in the matching pair. This represents the corrected attitude angle corresponding to the first laser point in the matching pair. ΔR represents the corrected attitude angle corresponding to the second laser point in the matching pair. M Denotes the first rotation matrix. This represents the distance measurement value in the observation of the first laser point in the matching pair. This represents the angle measurement value in the observation of the first laser point in the matching pair. Indicates the distance measurement correction amount. Indicates the angle measurement correction amount. This represents the distance measurement value in the observation of the second laser point in the matching pair. This represents the angle measurement value in the observation of the second laser point in the matching pair. Indicates the offset of the lever arm value. This represents the location coordinates of the first laser point in the matching pair. This represents the location coordinates of the second laser point in the matching pair.

[0048] In one possible implementation, constructing the optimization objective using the distance from the laser point to the plane, and solving the optimization objective to obtain a first optimized value for the intrinsic parameters and a second optimized value for the extrinsic parameters includes:

[0049] An error equation is constructed using the distance from the laser point to the plane. ;

[0050] Based on the principle of least squares, the intrinsic and extrinsic parameters are optimized to obtain a first optimized value for the intrinsic parameters and a second optimized value for the extrinsic parameters. The optimization process aims to achieve a sum of squares of the distances from the laser point to the plane. Minimum, N is the total number of matching pairs, and the sum of the squares of the distances from the laser points to the plane. The minimum is the optimization objective.

[0051] In one possible implementation, the method further includes: if the relationship between the first optimized value of the intrinsic parameter and the third optimized value of the previously determined intrinsic parameter does not satisfy a first preset optimization relationship, and / or the relationship between the second optimized value of the extrinsic parameter and the fourth optimized value of the previously determined extrinsic parameter does not satisfy a second preset optimization relationship, then the intrinsic parameter is adjusted using the first optimized value of the intrinsic parameter and the extrinsic parameter is adjusted using the second optimized value of the extrinsic parameter, the first optimized value determined this time is used as the third optimized value and the second optimized value determined this time is used as the fourth optimized value, and for each laser point, a first coordinate vector of the laser point in the projected coordinate system is determined based on the ranging value corresponding to the laser point, the angle value corresponding to the laser point, the attitude angle corresponding to the laser point, the positioning coordinates corresponding to the laser point, and the intrinsic and extrinsic parameters of the laser radar scanner system.

[0052] A second aspect of this application provides a parameter calibration device for use in a lidar scanner system. The lidar scanner system includes an integrated navigation system, an aircraft, an inertial measurement system, and a lidar scanner. The lidar scanner is mounted on the aircraft. The device includes:

[0053] The first acquisition unit is used to acquire the original point cloud data of multiple flight strips collected by the lidar scanner, and the flight trajectory data collected by the integrated navigation system within the same time period. The original point cloud data includes the distance and angle values ​​of each laser point in the multiple flight strips in the scanner coordinate system corresponding to the lidar scanner, and the flight trajectory data includes the positioning coordinates and attitude angle of each laser point in the projection coordinate system at any time.

[0054] The first determining unit is used to determine the first coordinate vector of each laser point in the projected coordinate system based on the ranging value, the angle value, the attitude angle, the positioning coordinates, and the intrinsic and extrinsic parameters of the laser radar scanner system.

[0055] The second acquisition unit is used to acquire the normal vector of each laser point in the overlapping area of ​​adjacent flight strips after constructing a plane using the laser point set of the laser point. The laser point set of the laser point includes the laser point and the laser point within a preset local range corresponding to the laser point and located in the overlapping area.

[0056] The second determining unit is used to determine the laser point features of two laser points that satisfy the preset matching conditions as a matching pair for all laser points located in the overlapping area and constructing a plane, using the first coordinate vector of any two laser points in the projection coordinate system. A matching pair includes two laser point features, and each laser point feature includes the observed value of the laser point.

[0057] The first calculation unit is used to calculate the distance from each laser point in the matching pair to the plane using the observed value of each laser point in the matching pair;

[0058] The second calculation unit is used to construct an optimization target using the distance from the laser point to the plane, and solve the optimization target to obtain the first optimized value of the intrinsic parameters and the second optimized value of the extrinsic parameters.

[0059] The calibration unit is configured to calibrate the intrinsic parameter using the first optimized value of the intrinsic parameter and the third optimized value of the previously determined intrinsic parameter if the relationship between the first optimized value of the intrinsic parameter and the third optimized value of the previously determined intrinsic parameter satisfies a first preset optimization relationship, and the relationship between the second optimized value of the extrinsic parameter and the fourth optimized value of the previously determined extrinsic parameter satisfies a second preset optimization relationship.

[0060] A third aspect of this application provides a computer program product including computer-readable instructions that, when executed on an electronic device, cause the electronic device to implement the parameter calibration method of the first aspect or any implementation thereof.

[0061] A fourth aspect of this application provides an electronic device, including at least one processor and a memory connected to the processor, wherein the memory is used to store a computer program;

[0062] The processor is used to execute the computer program so that the electronic device can implement the parameter calibration method of the first aspect or any implementation thereof.

[0063] The fifth aspect of this application provides a computer storage medium carrying one or more computer programs, which, when executed by an electronic device, enable the electronic device to perform the parameter calibration method described in the first aspect or any implementation thereof.

[0064] By employing the above technical solution, the parameter calibration method and related apparatus provided in this application acquire raw point cloud data of multiple flight strips collected by a lidar scanner, as well as flight trajectory data collected within the same time period by a combined navigation system. Using these data, the intrinsic and extrinsic parameters of the lidar scanner system, the distance from the laser point to the plane is obtained through a series of processing steps. An optimization target is constructed using the distance from the laser point to the plane, and the optimization target is solved to obtain the first optimized value of the intrinsic parameter and the second optimized value of the extrinsic parameter. When the relationship between two consecutive optimized values ​​satisfies a preset optimization relationship, the last optimized value is used to calibrate the intrinsic and extrinsic parameters. This not only enables automated and high-precision synchronous calibration of intrinsic and extrinsic parameters, but also does not rely on control point targets or specific natural terrain features, making it more adaptable, more efficient, and lower in cost. It can meet the needs of complex surveying tasks such as uninhabited area surveying and disaster emergency response. Attached Figure Description

[0065] The above and other features, advantages, and aspects of the embodiments of this disclosure will become more apparent from the accompanying drawings and the following detailed description. Throughout the drawings, the same or similar reference numerals denote the same or similar elements. It should be understood that the drawings are schematic, and the originals and elements are not necessarily drawn to scale.

[0066] Figure 1 A flowchart of a parameter calibration method provided in this application;

[0067] Figure 2 A flowchart illustrating the determination of the first coordinate vector in the parameter calibration method provided in this application;

[0068] Figure 3 A schematic diagram of the parameter calibration method provided in this application;

[0069] Figure 4 A schematic diagram of point cloud data computation in the parameter calibration method provided in this application;

[0070] Figure 5 A schematic diagram of feature extraction and matching in the parameter calibration method provided in this application;

[0071] Figure 6 A schematic diagram of a parameter calibration device provided in this application;

[0072] Figure 7 This is a schematic diagram of the structure of an electronic device provided in this application. Detailed Implementation

[0073] The embodiments of this application are described below with reference to the accompanying drawings. The terminology used in the implementation section of this application is for explaining specific embodiments only and is not intended to limit the scope of this application.

[0074] The embodiments of this application will now be described with reference to the accompanying drawings. Those skilled in the art will recognize that, with technological advancements and the emergence of new scenarios, the technical solutions provided in the embodiments of this application are equally applicable to similar technical problems.

[0075] The terms "first," "second," etc., used in the specification, claims, and accompanying drawings of this application are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such terms are interchangeable where appropriate; this is merely a way of distinguishing objects with the same attributes in the embodiments of this application. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion, so that a process, method, system, product, or apparatus that comprises a series of elements is not necessarily limited to those elements but may include other elements not explicitly listed or inherent to such processes, methods, systems, products, or apparatus.

[0076] Currently, the intrinsic parameters of a LiDAR scanner system are completed before the scanner leaves the factory. However, with prolonged use, the accuracy of these intrinsic parameters will continuously decrease. Furthermore, the intrinsic parameters are required during extrinsic parameter calibration, and as the accuracy of the intrinsic parameters decreases, the accuracy of the extrinsic parameters also declines. Moreover, extrinsic parameter calibration relies on manually setting up ground control points or obvious and regular natural terrain features, which is inefficient and lacks adaptability, making it difficult to handle complex and ever-changing surveying tasks.

[0077] To address the aforementioned technical problems, this application provides a parameter calibration method and related apparatus for simultaneously calibrating the intrinsic and extrinsic parameters of a lidar scanner system. This ensures the accuracy of both intrinsic and extrinsic parameters even with long-term use of the lidar scanner system. Furthermore, during the calibration process, an optimization target is constructed using the distance from the laser point to the plane. Solving this target yields a first optimized value for the intrinsic parameters and a second optimized value for the extrinsic parameters. The first optimized value is used to calibrate the intrinsic parameters, and the second optimized value is used to calibrate the extrinsic parameters. This eliminates the need for manually setting up control point targets or requiring clearly defined and regular natural terrain features, resulting in wider applicability, higher efficiency, and lower cost. It can meet the needs of complex and varied surveying tasks such as uninhabited area mapping and disaster emergency response.

[0078] The following description, in conjunction with the accompanying drawings, illustrates a parameter calibration method and related apparatus provided in an embodiment of this application. Please refer to... Figure 1 This embodiment illustrates an optional flow of the parameter calibration method provided in this application. This parameter calibration method is applied to a lidar scanner system, which includes a combined navigation system, an aircraft, an inertial measurement system, and a lidar scanner. The lidar scanner is mounted on the aircraft. The components of the lidar scanner system and their relationships are not elaborated upon in this embodiment. Figure 1 The parameter calibration method shown may include the following steps:

[0079] S101. Acquire the raw point cloud data of multiple flight strips collected by the lidar scanner, and the flight trajectory data collected by the integrated navigation system within the same time period. The raw point cloud data includes the distance and angle values ​​of each laser point in the multiple flight strips in the scanner coordinate system corresponding to the lidar scanner, and the flight trajectory data includes the positioning coordinates and attitude angles of each laser point in the projection coordinate system at any time.

[0080] In this embodiment, the lidar scanner can be mounted on an aircraft. The aircraft carries the lidar scanner and flies in a flight path. The laser emitter in the lidar scanner emits lasers to form laser points in the flight path. The lidar scanner corresponds to a scanner coordinate system. The lidar scanner can collect the distance and angle values ​​of the laser points in the scanner coordinate system. The lidar scanner can also record the laser emission time.

[0081] The integrated navigation system can collect flight trajectory data of the aircraft while it is flying in the flight path and the collection time of each flight trajectory data. In this embodiment, the flight trajectory data with the same collection time and collection time as the laser emission time can be extracted from all flight trajectory data according to the laser emission time and the collection time of the flight trajectory data. These flight trajectory data are the flight trajectory data collected by the integrated navigation system within the same time period. That is, the same time means that the emission time corresponding to each laser point is the same as the collection time of the flight trajectory data. The corresponding laser point time refers to the emission time corresponding to the laser point.

[0082] In this embodiment, the positioning coordinates are three-dimensional data in the projected coordinate system. The attitude angle includes three attitude data. Where r represents the roll angle, p represents the pitch angle, and h represents the heading angle. Adjacent flight strips may have overlapping areas, and the degree of overlap can be greater than a preset value, such as greater than 30%, to prepare for subsequent plane construction.

[0083] S102. For each laser point, based on the distance measurement value, angle measurement value, attitude angle, positioning coordinates, intrinsic and extrinsic parameters of the laser radar scanner system, determine the first coordinate vector of the laser point in the projected coordinate system.

[0084] In this embodiment, the intrinsic and extrinsic parameters of the LiDAR scanner system are shared by all laser points. However, when determining the first coordinate vector, the ranging value, angle measurement value, attitude angle, and positioning coordinates corresponding to the laser point are also used. These data may differ for different laser points, therefore, the first coordinate vector of each laser point in the projected coordinate system may be different. The ranging value and angle measurement value corresponding to the laser point can be the ranging value and angle measurement value of the laser point in the scanner coordinate system corresponding to the LiDAR scanner. The attitude angle and positioning coordinates corresponding to the laser point can be the positioning coordinates and attitude angle of the laser point at the time of its occurrence.

[0085] In one possible implementation, the process of determining the first coordinate vector of the laser point in the projected coordinate system is as follows: Figure 2 As shown, the following steps may be included:

[0086] S201. Based on the distance measurement value, angle measurement value, and intrinsic parameters corresponding to the laser point, calculate the second coordinate vector of the laser point in the scanner coordinate system.

[0087] Intrinsic parameters are the inherent systematic errors of the laser emitter. These include distance correction and angle correction. The distance correction is the distance measured when the laser emitter emits the laser, and the angle correction is the angle measured when the laser emitter emits the laser. Therefore, the distance value of any laser point needs to be increased by the distance correction, and the angle value of any laser point needs to be increased by the angle correction. Then, using the corrected distance and angle values, the second coordinate vector of the laser point in the scanner coordinate system is calculated. This second coordinate vector records the coordinates of the laser point in the scanner coordinate system, and the coordinates are represented as a vector. The coordinates of the laser point in the scanner coordinate system can be two-dimensional or three-dimensional.

[0088] In one possible implementation, calculating the second coordinate vector includes: calculating the second coordinate vector of the laser point in the scanner coordinate system using the following formula: In the formula, X l Let l represent the second coordinate vector, l represent the distance value corresponding to the laser point, α represent the angle value corresponding to the laser point, Δl represent the distance correction, Δα represent the angle correction, and the intrinsic parameters include the distance correction and the angle correction.

[0089] S202. Based on the installation angle error in the extrinsic parameters, construct a first rotation matrix. The first rotation matrix is ​​used to transform the scanner coordinate system to the inertial measurement system coordinate system, where the inertial measurement system coordinate system is the coordinate system corresponding to the inertial measurement system. In one possible implementation, constructing the first rotation matrix based on the installation angle error in the extrinsic parameters includes:

[0090] Construct the first rotation matrix using the formula:

[0091] In the formula, ( The ) represents the installation angle error, ΔR M This represents the first rotation matrix.

[0092] S203. Using the second coordinate vector of the laser point in the scanner coordinate system, the first rotation matrix, and the lever arm offset in the extrinsic parameters, calculate the third coordinate vector of the laser point in the inertial measurement system coordinate system.

[0093] In this embodiment, the first rotation matrix completes the transformation from the scanner coordinate system to the inertial measurement system coordinate system. However, after the transformation, there is still a certain offset between the two coordinate systems (i.e., lever arm value offset). Therefore, the lever arm value offset can be introduced when calculating the third coordinate vector. For example, the third coordinate vector of the laser point can be calculated using the following formula: In the formula, X I Represents the third coordinate vector, ΔR M Let X represent the first rotation matrix. l The second coordinate vector is represented by Δt, which represents the offset of the lever arm.

[0094] S203. The heading angle in the attitude angle corresponding to the laser point is converged and corrected to obtain the corrected attitude angle.

[0095] S204. Based on the corrected attitude angle, construct the second rotation matrix from the inertial measurement system coordinate system to the projected coordinate system.

[0096] In this embodiment, the attitude angle records the rotation angle of the inertial measurement system coordinate system relative to the navigation system coordinate system. The transformation from the inertial measurement system coordinate system to the navigation system coordinate system can be completed based on the attitude angle. The transformation from the navigation system coordinate system to the projected coordinate system requires reference to the convergence angle. In this embodiment, the convergence correction of the attitude angle can be completed by the convergence angle so that the corrected attitude angle can be added to the convergence angle. Therefore, the transformation from the inertial measurement system coordinate system to the projected coordinate system can be completed by correcting the attitude angle, that is, the second rotation matrix is ​​constructed.

[0097] For example, the second rotation matrix is

[0098] in, , , In the formula, (r, p, H) represents the corrected attitude angle, and R N This represents the second rotation matrix.

[0099] Since the attitude angles in the flight trajectory data are the attitude angles of the inertial measurement system coordinate system relative to the navigation coordinate system, and the north direction of the navigation coordinate system is true north, while the north direction of the projected coordinate system is coordinate north, there is a convergence angle between the navigation coordinate system and the projected coordinate system. Therefore, the convergence angle is needed to correct the heading angle in the attitude angles, while the roll and pitch angles in the attitude angles remain unchanged.

[0100] In this embodiment, the correction value of the heading angle is calculated using the convergence angle, and the correction value is added to the heading angle to obtain the corrected heading angle. Feasible methods for calculating the correction value of the heading angle using the convergence angle include, but are not limited to, the following:

[0101] Calculate the correction using the formula given by Khristov for expanding to the 7th degree:

[0102] in , , The second eccentricity of the Earth, The latitude of the aircraft's location. The corrected heading angle is the difference in longitude between the meridian at the current time and the central meridian of the projected coordinate system. The corrected attitude angles still include roll angle, pitch angle and yaw angle. The yaw angle is the corrected yaw angle, while the roll angle and pitch angle remain unchanged.

[0103] S205. Based on the third coordinate vector of the laser point in the inertial measurement system coordinate system, the second rotation matrix, and the positioning coordinates, determine the first coordinate vector of the laser point in the projection coordinate system.

[0104] In this embodiment, the second rotation matrix is ​​used to transform the inertial measurement coordinate system to the projected coordinate system. However, the origins of the two coordinate systems do not coincide. The positioning coordinates are the coordinates of the origin of the inertial measurement system coordinate system in the projected coordinate system. Therefore, the positioning coordinates can be used to make the origin of the transformed coordinate system coincide with that of the projected coordinate system. Correspondingly, a feasible way to determine the first coordinate vector of the laser point in the projected coordinate system includes: calculating the first coordinate vector of the laser point using the formula: In the formula, X I Let X represent the third coordinate vector. p Let X represent the first coordinate vector. g R represents the location coordinates. N This represents the second rotation matrix.

[0105] S103. For each laser point in the overlapping area of ​​adjacent flight strips, after constructing a plane using the laser point set of the laser point, obtain the normal vector of the plane. The laser point set of the laser point includes the laser point and the laser points within the preset local range corresponding to the laser point and located in the overlapping area.

[0106] In one possible implementation, for each laser point within the overlapping area of ​​adjacent flight strips, all laser points located within the overlapping area and at a distance less than a preset distance threshold are identified. This allows for the construction of a plane using these closely spaced laser points within the overlapping area. This plane does not need to possess obvious and regular natural terrain features, thus improving adaptability. The preset distance threshold can be, but is not limited to, 1 meter.

[0107] Constructing a plane using a set of laser points mainly involves determining the laser points that can serve as coordinate points on the plane and the normal vector of the plane. One feasible approach is as follows:

[0108] At least three feature values ​​of the laser point set are obtained, and the flatness is calculated based on these three feature values. If the flatness is greater than a preset flatness threshold, the laser point is used as a coordinate point on the plane, and the feature value among the at least three feature values ​​of the laser point set that satisfies a preset condition is used as the normal vector of the plane containing the laser point. If the flatness is less than or equal to the preset flatness threshold, all laser points in the laser point set are prohibited from being used to determine matching pairs; that is, if the flatness is less than or equal to the preset flatness threshold, all laser points in the laser point set are prohibited from participating in parameter calibration.

[0109] If principal component analysis is performed on the laser point set, three eigenvalues ​​are obtained. Correspondingly, the flatness can be calculated based on these three eigenvalues. The calculation formula is as follows: Calculate flatness, where p is the flatness. , and These are three eigenvalues ​​that increase sequentially.

[0110] If the flatness is greater than a preset flatness threshold, the smallest of the three eigenvalues ​​is taken as the normal vector of the plane containing the laser point. Furthermore, if the flatness is greater than the preset flatness threshold, it indicates that the laser points in the set can construct a plane. The value of the preset flatness threshold is not limited in this embodiment.

[0111] S104. For all laser points located within the overlapping region and forming a plane, use the first coordinate vector of any two laser points in the projected coordinate system to determine the laser point features of two laser points that satisfy the preset matching conditions as a matching pair. A matching pair includes two laser point features, and each laser point feature includes the observed value of the laser point.

[0112] In this embodiment, one form of the preset matching condition can be the similarity between the laser point features of two laser points. Correspondingly, a feasible way to determine the matching pair is as follows: calculate the similarity of the laser point features of the two laser points based on the first coordinate vector of the two laser points in the projected coordinate system, and take the laser point features of the two laser points whose similarity satisfies the preset similarity condition as candidate matching pairs; calculate the similarity standard deviation using the similarity of all candidate matching pairs; and select the candidate matching pairs that satisfy the preset matching condition as matching pairs based on the similarity standard deviation and the similarity of each candidate matching pair.

[0113] For example, a preset matching condition can be used to limit the threshold of the similarity standard deviation. If the similarity standard deviation of a candidate matching pair is less than this threshold, the candidate matching pair is considered a matching pair. The preset matching condition can be M times the absolute value of the difference between the similarity standard deviation and the mean, where M is a positive integer.

[0114] In one possible implementation, the similarity between the laser point features of two laser points can be Euclidean distance. Specifically, based on the first coordinate vectors of the two laser points in the projected coordinate system, the Euclidean distance between the two laser points is calculated. Laser point features of two laser points whose Euclidean distance is less than a preset distance (a form of preset similarity condition) are selected as candidate matching pairs. The standard deviation and average distance of the Euclidean distances of all candidate matching pairs are calculated. Candidate matching pairs whose absolute value of the difference between the Euclidean distance and the average distance is greater than M times the standard deviation of the distance are eliminated, where M is a positive integer. The remaining candidate matching pairs are used as matching pairs.

[0115] S105. Using the observation values ​​of each laser point in the matching pair, calculate the distance from each laser point in the matching pair to the plane.

[0116] In one possible implementation, the observed values ​​of the laser point may include: the distance value corresponding to the laser point, the angle value corresponding to the laser point, the normal vector of the plane, and the positioning coordinates; correspondingly, using the observed values ​​of each laser point in the matching pair, calculating the distance from each laser point in the matching pair to the plane includes:

[0117] Calculate the distance from the laser point to the plane using the formula:

[0118] in,

[0119]

[0120] In the formula, This represents the distance from a point to a plane. This represents the normal vector in the observation value of the first laser point in the matching pair. This represents the second rotation matrix corresponding to the first laser point in the matching pair. This represents the second rotation matrix corresponding to the second laser point in the matching pair. This represents the corrected attitude angle corresponding to the first laser point in the matching pair. ΔR represents the corrected attitude angle corresponding to the second laser point in the matching pair. M Denotes the first rotation matrix. This represents the distance measurement value in the observation of the first laser point in the matching pair. This represents the angle measurement value in the observation of the first laser point in the matching pair. Indicates the distance measurement correction amount. Indicates the angle measurement correction amount. This represents the distance measurement value among the observations of the second laser point in the matching points. This represents the angle measurement value in the observation of the second laser point in the matching pair. Indicates the offset of the lever arm value. This represents the location coordinates of the first laser point in the matching pair. This represents the location coordinates of the second laser point in the matching pair.

[0121] S106. Construct an optimization objective using the distance from the laser point to the plane, and solve for the optimization objective to obtain the first optimized value of the intrinsic parameters and the second optimized value of the extrinsic parameters. The optimization objective using the distance from the laser point to the plane can be to minimize the sum of the squares of the distances from the laser point to the plane. For example, an error equation can be constructed using the distance from the laser point to the plane. The optimization objective is to minimize the sum of the squares of the distances from the laser point to the plane. Minimum, where N is the total number of matching pairs.

[0122] In this embodiment, based on the principle of least squares, the intrinsic and extrinsic parameters are optimized to obtain the first optimized value of the intrinsic parameters and the second optimized value of the extrinsic parameters. The optimization process aims to achieve the sum of the squares of the distances from the laser point to the plane. Minimum, that is, when the first and second optimized values ​​are obtained. Minimum.

[0123] Since the error equation is a nonlinear equation, algorithms such as Newton's method, Gauss-Newton method, and Levenberg-Marquardt method can be used to solve the nonlinear least squares problem.

[0124] S107. If the relationship between the first optimized value of the intrinsic parameter and the third optimized value of the intrinsic parameter determined in the previous test satisfies the first preset optimization relationship, and the relationship between the second optimized value of the extrinsic parameter and the fourth optimized value of the extrinsic parameter determined in the previous test satisfies the second preset optimization relationship, then the intrinsic parameter is calibrated using the first optimized value of the intrinsic parameter and the extrinsic parameter is calibrated using the second optimized value of the extrinsic parameter.

[0125] In this embodiment, the intrinsic parameters include distance correction and angle correction, and the extrinsic parameters include lever arm offset and placement angle error. Therefore, step S106 can obtain the first optimized value of the distance correction, the first optimized value of the angle correction, the second optimized value of the lever arm offset, and the second optimized value of the placement angle error. The relationship between the first optimized value of the intrinsic parameters and the previously determined third optimized value of the intrinsic parameters satisfies the first preset optimization relationship, meaning that the first optimized value of the distance correction and the previously determined third optimized value of the distance correction satisfy the first preset optimization relationship, and the first optimized value of the angle correction and the previously determined third optimized value of the angle correction satisfy the first preset optimization relationship. The relationship between the second optimized value of the extrinsic parameters and the previously determined fourth optimized value of the extrinsic parameters satisfies the second preset optimization relationship, meaning that the relationship between the second optimized value of the lever arm offset and the previously determined fourth optimized value of the lever arm offset satisfies the second preset optimization relationship, and the relationship between the second optimized value of the placement angle error and the previously determined fourth optimized value of the placement angle error satisfies the second preset optimization relationship.

[0126] For example, the first and second preset optimization relationships can be used to set thresholds. For any parameter among the intrinsic and extrinsic parameters, the difference between the currently determined optimized value and the previously determined optimized value of the same parameter is calculated. If the difference is less than the threshold, the parameter is determined to satisfy the preset optimization relationship. When the difference of all parameters is less than the threshold, all parameters are determined to satisfy the preset optimization relationship. The optimized value of each parameter can be used to calibrate the parameter. The calibration process will not be detailed in this embodiment. The thresholds for different parameters can be different, and this embodiment does not limit them.

[0127] After each parameter is calibrated, the LiDAR scanner system completes the calibration of its intrinsic and extrinsic parameters for this round. As the LiDAR scanner system is used, the parameter calibration method provided in this embodiment can be used to continue calibrating the intrinsic and extrinsic parameters of the LiDAR scanner system to ensure the accuracy of both intrinsic and extrinsic parameters.

[0128] S108. If the relationship between the first optimized value of the intrinsic parameter and the third optimized value of the intrinsic parameter determined in the previous step does not satisfy the first preset optimization relationship, and / or the relationship between the second optimized value of the extrinsic parameter and the fourth optimized value of the extrinsic parameter determined in the previous step does not satisfy the second preset optimization relationship, then the intrinsic parameter is adjusted using the first optimized value of the intrinsic parameter and the extrinsic parameter is adjusted using the second optimized value of the extrinsic parameter. The first optimized value determined in this step is taken as the third optimized value, the second optimized value determined in this step is taken as the fourth optimized value, and the process returns to step S102.

[0129] After returning to step S102, steps S102 to S106 are executed repeatedly to obtain the first optimized value of the intrinsic parameter and the second optimized value of the extrinsic parameter. The first optimized value is then compared with the third optimized value of the intrinsic parameter determined previously, and the second optimized value is compared with the fourth optimized value of the extrinsic parameter determined previously. This is to determine whether the relationship between the first optimized value and the third optimized value of the intrinsic parameter determined previously satisfies the first preset optimization relationship, and whether the relationship between the second optimized value of the extrinsic parameter and the fourth optimized value of the extrinsic parameter determined previously satisfies the second preset optimization relationship.

[0130] The parameter calibration method provided in this embodiment can acquire raw point cloud data of multiple flight strips collected by a lidar scanner, as well as flight trajectory data collected by a combined navigation system within the same time period. Using these data, the intrinsic and extrinsic parameters of the lidar scanner system, the distance from the laser point to the plane is obtained through a series of processing steps. An optimization target is constructed using the distance from the laser point to the plane, and the optimization target is solved to obtain the first optimized value of the intrinsic parameter and the second optimized value of the extrinsic parameter. When the relationship between two consecutive optimized values ​​satisfies a preset optimization relationship, the last optimized value is used to calibrate the intrinsic and extrinsic parameters. This method can not only achieve automated and high-precision synchronous calibration of intrinsic and extrinsic parameters, but also does not rely on control point targets or specific natural terrain features. It has wider adaptability, higher efficiency, and lower cost, and can meet complex surveying tasks such as uninhabited area surveying and disaster emergency response.

[0131] In some embodiments, a schematic diagram of the parameter calibration method provided in this embodiment is shown below. Figure 3 As shown, it includes the following steps:

[0132] 1. Data acquisition; 2. Point cloud data processing; 3. Feature extraction and matching; 4. Adjustment calculation; 5. Convergence judgment. If convergence is achieved, proceed to step 6. Calibration parameter output, i.e., output the intrinsic and extrinsic parameters calibrated using the optimized values. If convergence is not achieved, return to step 2. Data acquisition corresponds to step S101 above, point cloud data processing corresponds to step S102 above, feature extraction and matching corresponds to steps S103 to S105 above, adjustment calculation corresponds to step S106 above, and convergence judgment corresponds to steps S107 and S108 above.

[0133] The above steps are explained in detail below. Figure 4 As shown, point cloud data processing specifically includes the following steps:

[0134] Point cloud data processing involves transforming the coordinates of the laser points from the scanner's coordinate system to the projected coordinate system. During the data acquisition phase, the LiDAR scanner obtains the distance measurements of the laser points in the scanner's coordinate system. and angle measurement value To obtain the coordinates of a laser point in the geographic coordinate system, it is necessary to combine the flight trajectory data collected by the integrated navigation system with the intrinsic and extrinsic parameters of the lidar scanner system to calculate the coordinates of the laser point in the geographic coordinate system. The geographic coordinate system is generally a projected coordinate system, such as the Gaussian projection coordinate system or the UTM projection coordinate system. Therefore, the coordinates of the laser point in the geographic coordinate system are the same as the coordinates of the laser point in the projected coordinate system.

[0135] Taking the Gaussian projected coordinate system as an example, let the intrinsic parameters include the distance measurement correction. and angle correction amount The external parameters include the three orientation angle errors of the scanner coordinate system relative to the inertial measurement system coordinate system. ) and 3 lever arm offset values The flight trajectory data includes the position coordinates and attitude angles of each laser point in the projected coordinate system at any given time. For example, the position coordinates are three-dimensional data in the projected coordinate system. The attitude angle includes three attitude data. The point cloud data processing procedure is as follows:

[0136] Using the distance measurement, angle measurement, and intrinsic parameters of each laser point, the second coordinate vector in the scanner coordinate system can be calculated. , ;

[0137] Because the installation of components in a LiDAR scanner system cannot completely guarantee that the scanner coordinate system and the inertial measurement system coordinate system are parallel, a system installation angle error exists between the two coordinate systems. Since this installation angle error is a small angle, the first rotation matrix formed by the installation error can be obtained as follows: ;

[0138] Based on the first coordinate vector of the laser point in the scanner coordinate system , Installation angle error and lever arm offset The third coordinate vector of the laser point in the inertial measurement system coordinate system can be obtained. , ;

[0139] Since the attitude angles in the flight trajectory data are the attitude angles of the inertial measurement system coordinate system relative to the navigation coordinate system, and the north direction of the navigation coordinate system is true north, while the north direction of the projected coordinate system is coordinate north, there is a convergence angle between the two. The inertial measurement system coordinate system cannot be directly transformed to the projected coordinate system using attitude angles. Instead, the heading angle in the attitude angles needs to be corrected for convergence. The convergence correction value can be calculated using the formula for the expansion to the 7th degree given by Khristov. For details, please refer to the above embodiment.

[0140] Based on the corrected attitude angle, construct a second rotation matrix from the inertial measurement system coordinate system to the projected coordinate system. Then, based on the coordinate vector of the laser point in the inertial measurement system coordinate system... , and positioning coordinate vector The first coordinate vector of the laser point in the projected coordinate system can be obtained. .

[0141] like Figure 5 As shown, feature extraction and matching involve extracting and matching features from point cloud data within overlapping regions. Point-to-area matching features are used, requiring only local flatness, and do not rely on regular natural terrain features. Furthermore, the matching pairs are robust, which also helps the adjustment converge quickly. Specifically, the process may include the following steps:

[0142] (1) Feature calculation. For any laser point in the overlapping area of ​​adjacent flight strips, extract the laser points in the preset local range (usually within 1 meter) corresponding to that laser point. Perform principal component decomposition on all laser points (i.e., the set of laser points) to obtain three feature values ​​sorted from smallest to largest. Calculate flatness ,like If the flatness value is greater than the preset flatness threshold, the laser point is considered to be on the plane, and the minimum eigenvalue (i.e., the eigenvalue with the smallest value among the three eigenvalues) is taken as the normal vector of the plane containing the point. .

[0143] (2) Feature matching. For all laser points located in the overlapping area and forming a plane, pairwise matching is performed on the laser points. If the distance between two laser points in different flight zones is less than a threshold, the laser point features of the two laser points with a distance less than the threshold constitute a candidate matching pair. The distance can be Euclidean distance.

[0144] (3) Matching pair screening. For all candidate matching pairs, calculate the standard deviation and mean of the distance, and remove candidate matching pairs whose absolute value of the difference between the Euclidean distance and the mean is greater than 3 times the standard deviation of the distance.

[0145] Adjustment calculations may specifically include the following steps:

[0146] (1) Error Equation Establishment. An error equation is established based on the constraint that the sum of the squares of the distances from the laser point to the plane must be minimized for the point-to-surface features of the matching pair. For the matching pair... Let the two laser points be respectively and The first laser point The corresponding observations include distance measurements. Angular value Normal vector The corresponding location coordinates at that time Attitude angle The second laser point The corresponding observations include distance measurements. Angular value The orbital positioning coordinates at the corresponding time. Attitude angle Based on the point cloud data calculation principle, after incorporating intrinsic and extrinsic parameters, the distance from the two laser points to the plane is... Since the two laser points should represent the same plane, the matching pair Observation equations can be established Then the error equation .

[0147] in, ,

[0148] .

[0149] (2) Adjustment solution. Based on the principle of least squares, the intrinsic and extrinsic parameters to be solved are optimized so that the sum of the squares of the distances from the points to the plane is equal to the sum of the squares of the distances from the points to the plane. Minimum, of which This represents the total number of matching pairs.

[0150] After obtaining the optimized values ​​of intrinsic and extrinsic parameters, a convergence test is performed. If convergence is achieved, the optimized values ​​determined this time are used to calibrate the intrinsic and extrinsic parameters, and the calibrated intrinsic and extrinsic parameters are output. Otherwise, the point cloud data solution step is returned to restart the solution of the optimized values ​​of intrinsic and extrinsic parameters. When restarting the solution of the optimized values ​​of intrinsic and extrinsic parameters, the intrinsic and extrinsic parameters used are those calibrated according to the optimized values ​​determined last time.

[0151] The above describes a parameter calibration method provided by an embodiment of this application. The following describes the apparatus for performing the above parameter calibration method.

[0152] Please see Figure 6 , Figure 6 This is a schematic diagram of a parameter calibration device provided in an embodiment of this application. Figure 6 As shown, this parameter calibration device can be applied to a lidar scanner system, which includes a combined navigation system, an aircraft, an inertial measurement system, and a lidar scanner, with the lidar scanner mounted on the aircraft. The parameter calibration device includes: a first acquisition unit 10, a first determination unit 20, a second acquisition unit 30, a second determination unit 40, a first calculation unit 50, a second calculation unit 60, and a calibration unit 70.

[0153] The first acquisition unit 10 is used to acquire the original point cloud data of multiple flight strips collected by the lidar scanner, and the flight trajectory data collected by the integrated navigation system within the same time period. The original point cloud data includes the ranging and angle values ​​of each laser point in the multiple flight strips in the scanner coordinate system corresponding to the lidar scanner, and the flight trajectory data includes the positioning coordinates and attitude angles of each laser point in the projection coordinate system at any time.

[0154] The first determining unit 20 is used to determine the first coordinate vector of each laser point in the projected coordinate system based on the ranging value, the angle value, the attitude angle, the positioning coordinates, and the intrinsic and extrinsic parameters of the laser radar scanner system.

[0155] The second acquisition unit 30 is used to acquire the normal vector of each laser point in the overlapping area of ​​adjacent flight strips after constructing a plane using the laser point set of the laser point. The laser point set of the laser point includes the laser point and the laser points in the overlapping area within a preset local range corresponding to the laser point.

[0156] The second determining unit 40 is used to determine the laser point features of two laser points that meet the preset matching conditions as a matching pair for all laser points located in the overlapping area and forming a plane, using the first coordinate vector of any two laser points in the projected coordinate system. A matching pair includes two laser point features, and each laser point feature includes the observed value of the laser point.

[0157] The first calculation unit 50 is used to calculate the distance from each laser point in the matching pair to the plane using the observation value of each laser point in the matching pair.

[0158] The second calculation unit 60 is used to construct an optimization target using the distance from the laser point to the plane, and solve the optimization target to obtain the first optimized value of the intrinsic parameters and the second optimized value of the extrinsic parameters.

[0159] The calibration unit 70 is used to calibrate the internal parameter using the first optimized value of the internal parameter and to calibrate the external parameter using the second optimized value of the external parameter if the relationship between the first optimized value of the internal parameter and the third optimized value of the internal parameter determined in the previous determination satisfies the first preset optimization relationship and the relationship between the second optimized value of the external parameter and the fourth optimized value of the external parameter determined in the previous determination satisfies the second preset optimization relationship.

[0160] In one possible implementation, after the second acquisition unit 30 constructs a plane using the set of laser points, the acquisition of the plane's normal vector includes: acquiring at least three feature values ​​of the set of laser points; calculating the flatness based on the at least three feature values ​​of the set of laser points; if the flatness is greater than a preset flatness threshold, then the laser point is taken as a coordinate point on the plane, and the feature value among the at least three feature values ​​of the set of laser points that satisfies the preset condition is taken as the normal vector of the plane where the laser point is located, so as to obtain the plane and the plane's normal vector.

[0161] In one possible implementation, the second acquisition unit 30 calculates the flatness based on at least three eigenvalues ​​of the laser point set by: using the formula Calculate flatness, where p is the flatness. , and The laser point set consists of at least three eigenvalues ​​whose values ​​increase sequentially. The second acquisition unit 30 uses the eigenvalue that satisfies a preset condition among the at least three eigenvalues ​​of the laser point set as the normal vector of the plane where the laser point is located, including: using the eigenvalue with the smallest value among the three eigenvalues ​​as the normal vector of the plane where the laser point is located.

[0162] In one possible implementation, the second determining unit 40 determines the laser point features of two laser points that satisfy a preset matching condition as a matching pair by using the first coordinate vector of any two laser points in the projection coordinate system, for all laser points located within the overlapping region and forming a plane.

[0163] Based on the first coordinate vectors of the two laser points in the projected coordinate system, the similarity of the laser point features of the two laser points is calculated. The laser point features of the two laser points whose similarity satisfies the preset similarity condition are selected as candidate matching pairs. The similarity standard deviation of all candidate matching pairs is calculated. Based on the similarity standard deviation and the similarity of each candidate matching pair, the candidate matching pairs that satisfy the preset matching condition are selected as matching pairs.

[0164] In one possible implementation, the first determining unit 20, for each laser point, determines the first coordinate vector of the laser point in the projected coordinate system based on the ranging value corresponding to the laser point, the angle value corresponding to the laser point, the attitude angle corresponding to the laser point, the positioning coordinates corresponding to the laser point, and the intrinsic and extrinsic parameters of the lidar scanner system, including:

[0165] Based on the distance measurement value, angle measurement value, and intrinsic parameters corresponding to the laser point, calculate the second coordinate vector of the laser point in the scanner coordinate system; construct the first rotation matrix based on the placement angle error in the extrinsic parameters.

[0166] Using the second coordinate vector of the laser point in the scanner coordinate system, the first rotation matrix, and the lever offset in the extrinsic parameters, the third coordinate vector of the laser point in the inertial measurement system coordinate system is calculated. The inertial measurement system coordinate system is the coordinate system corresponding to the inertial measurement system. The heading angle in the attitude angle corresponding to the laser point is converged and corrected to obtain the corrected attitude angle. Based on the corrected attitude angle, a second rotation matrix from the inertial measurement system coordinate system to the projected coordinate system is constructed. Based on the third coordinate vector of the laser point in the inertial measurement system coordinate system, the second rotation matrix, and the positioning coordinates, the first coordinate vector of the laser point in the projected coordinate system is determined.

[0167] In one possible implementation, the second coordinate vector of the laser point in the scanner coordinate system is calculated based on the distance measurement value, the angle measurement value, and the intrinsic parameters corresponding to the laser point, including:

[0168] Calculate the second coordinate vector of the laser point in the scanner coordinate system using the formula: In the formula, X l The second coordinate vector is represented by l, which represents the distance value corresponding to the laser point, α, which represents the angle value corresponding to the laser point, Δl, which represents the distance correction, and Δα, which represents the angle correction. The intrinsic parameters include the distance correction and the angle correction.

[0169] And / or,

[0170] Based on the placement angle error in the extrinsic parameters, the first rotation matrix is ​​constructed as follows:

[0171] Construct the first rotation matrix using the formula: In the formula, ( The ) represents the installation angle error, ΔR M Represents the first rotation matrix;

[0172] And / or,

[0173] Using the second coordinate vector of the laser point in the scanner coordinate system, the first rotation matrix, and the lever arm offset in the extrinsic parameters, the third coordinate vector of the laser point in the inertial measurement system coordinate system is calculated as follows:

[0174] Calculate the third coordinate vector of the laser point using the formula: In the formula, X I Represents the third coordinate vector, ΔR M Let X represent the first rotation matrix. l This represents the second coordinate vector, and Δt represents the offset of the lever arm value;

[0175] And / or,

[0176] Based on the corrected attitude angle, the second rotation matrix from the inertial measurement system coordinate system to the projected coordinate system is constructed as follows: The second rotation matrix is...

[0177] in, , , In the formula, (r, p, H) represents the corrected attitude angle, and R N Indicates the second rotation matrix;

[0178] Based on the third coordinate vector, second rotation matrix, and positioning coordinates of the laser point in the inertial measurement system coordinate system, the first coordinate vector of the laser point in the projected coordinate system is determined by: calculating the first coordinate vector of the laser point using the formula: In the formula, X I Let X represent the third coordinate vector. p Let X represent the first coordinate vector. g R represents the location coordinates. N This represents the second rotation matrix.

[0179] In one possible implementation, the observed values ​​of the laser point include: the distance value corresponding to the laser point, the angle value corresponding to the laser point, the normal vector of the plane, and the positioning coordinates; the first calculation unit 50 uses the observed values ​​of each laser point in the matching pair to calculate the distance from each laser point in the matching pair to the plane, including:

[0180] Calculate the distance from the laser point to the plane using the formula:

[0181] in,

[0182]

[0183] In the formula, This represents the distance from a point to a plane. This represents the normal vector in the observation value of the first laser point in the matching pair. This represents the second rotation matrix corresponding to the first laser point in the matching pair. This represents the second rotation matrix corresponding to the second laser point in the matching pair. This represents the corrected attitude angle corresponding to the first laser point in the matching pair. ΔR represents the corrected attitude angle corresponding to the second laser point in the matching pair. M Denotes the first rotation matrix. This represents the distance measurement value in the observation of the first laser point in the matching pair. This represents the angle measurement value in the observation of the first laser point in the matching pair. Indicates the distance measurement correction amount. Indicates the angle measurement correction amount. This represents the distance measurement value in the observation of the second laser point in the matching pair. This represents the angle measurement value in the observation of the second laser point in the matching pair. Indicates the offset of the lever arm value. This represents the location coordinates of the first laser point in the matching pair. This represents the location coordinates of the second laser point in the matching pair.

[0184] In one possible implementation, the second computing unit 60 constructs an optimization objective using the distance from the laser point to the plane, and solves the optimization objective to obtain a first optimized value of the intrinsic parameters and a second optimized value of the extrinsic parameters, including:

[0185] An error equation is constructed using the distance from the laser point to the plane. ;

[0186] Based on the principle of least squares, the intrinsic and extrinsic parameters are optimized to obtain the first optimized value of the intrinsic parameters and the second optimized value of the extrinsic parameters. The optimization process aims to achieve the sum of the squares of the distances from the laser point to the plane. Minimum, where N is the total number of matching pairs, and the sum of the squares of the distances from the laser points to the plane. Minimum is the optimization objective.

[0187] In one possible implementation, the calibration unit is further configured to adjust the intrinsic parameter using the first optimized value of the intrinsic parameter and the third optimized value of the previously determined intrinsic parameter if the relationship between the first optimized value of the intrinsic parameter and the third optimized value of the previously determined intrinsic parameter does not satisfy the first preset optimization relationship, and / or the relationship between the second optimized value of the extrinsic parameter and the fourth optimized value of the previously determined extrinsic parameter does not satisfy the second preset optimization relationship. The first optimized value determined this time is used as the third optimized value and the second optimized value determined this time is used as the fourth optimized value. The first determining unit 20 and the second obtaining unit 30 are then triggered to continue calibrating the intrinsic and extrinsic parameters.

[0188] This application also provides an electronic device in its embodiments. (See reference...) Figure 7 The diagram illustrates a structural schematic suitable for implementing the electronic device in the embodiments of this application. The electronic device in the embodiments of this application may include, but is not limited to, fixed terminals such as mobile phones, laptops, PDAs (personal digital assistants), PADs (tablet computers), desktop computers, etc. Figure 7 The electronic device shown is merely an example and should not impose any limitation on the functionality and scope of use of the embodiments of this application.

[0189] like Figure 7As shown, the electronic device may include a processing unit (e.g., a central processing unit, a graphics processing unit, etc.) 301, which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM) 302 or a program loaded from a storage device 308 into a random access memory (RAM) 303. When the electronic device is powered on, the RAM 303 also stores various programs and data required for the operation of the electronic device. The processing unit 301, ROM 302, and RAM 303 are interconnected via a bus 304. An input / output (I / O) interface 305 is also connected to the bus 304. The processing unit 301 can be considered as a processor in the electronic device, and the ROM 302, RAM 303, and storage device 308 can be considered as memory in the electronic device. The memory is used to store computer programs; the processor is used to execute the computer programs to enable the electronic device to implement any of the parameter calibration methods provided in the embodiments of this application.

[0190] Typically, the following devices can be connected to I / O interface 305: input devices 306 including, for example, touchscreens, touchpads, keyboards, mice, cameras, microphones, accelerometers, gyroscopes, etc.; output devices 307 including, for example, liquid crystal displays (LCDs), speakers, vibrators, etc.; storage devices 308 including, for example, memory cards, hard drives, etc.; and communication devices 309. Communication device 309 allows electronic devices to communicate wirelessly or wiredly with other devices to exchange data. Although Figure 7 Electronic devices with various devices are shown, but it should be understood that it is not required to implement or have all of the devices shown. More or fewer devices may be implemented or have alternatively.

[0191] This application also provides a computer program product including computer-readable instructions, which, when executed on an electronic device, cause the electronic device to implement any of the parameter calibration methods provided in this application.

[0192] This application also provides a computer-readable storage medium that carries one or more computer programs. When the one or more computer programs are executed by an electronic device, the electronic device can implement any of the parameter calibration methods provided in this application.

[0193] It should also be noted that the device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate, and the components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs. In addition, in the device embodiment drawings provided in this application, the connection relationship between units indicates that they have a communication connection, which can be implemented as one or more communication buses or signal lines.

[0194] Through the above description of the embodiments, those skilled in the art can clearly understand that this application can be implemented by means of software plus necessary general-purpose hardware, or it can be implemented by special-purpose hardware including application-specific integrated circuits, special-purpose CPUs, special-purpose memory, special-purpose components, etc. Generally, any function performed by a computer program can be easily implemented by corresponding hardware, and the specific hardware structure used to implement the same function can also be diverse, such as analog circuits, digital circuits, or special-purpose circuits. However, for this application, software program implementation is more often the preferred implementation method. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product is stored in a readable storage medium, such as a computer floppy disk, USB flash drive, mobile hard disk, ROM, RAM, magnetic disk, or optical disk, etc., and includes several instructions to cause a computer device (which may be a personal computer, training equipment, or network device, etc.) to execute the methods described in the various embodiments of this application.

[0195] In the above embodiments, implementation can be achieved, in whole or in part, through software, hardware, firmware, or any combination thereof. When implemented in software, it can be implemented, in whole or in part, as a computer program product.

[0196] The computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, all or part of the processes or functions described in the embodiments of this application are generated. The computer may be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions may be stored in a computer-readable storage medium or transferred from one computer-readable storage medium to another. The computer-readable storage medium may be any available medium that a computer can store or a data storage device such as a training device or a data center that integrates one or more available media. The available media may be magnetic media (e.g., floppy disks, hard disks, magnetic tapes), optical media (e.g., DVDs), or semiconductor media (e.g., solid-state drives (SSDs)).

Claims

1. A parameter calibration method, characterized in that, The method is applied to a lidar scanner system, which includes an integrated navigation system, an aircraft, an inertial measurement system, and a lidar scanner, wherein the lidar scanner is mounted on the aircraft. The system acquires raw point cloud data of multiple flight strips collected by the lidar scanner and flight trajectory data collected by the integrated navigation system within the same time period. The raw point cloud data includes the distance and angle values ​​of each laser point in the multiple flight strips in the scanner coordinate system corresponding to the lidar scanner. The flight trajectory data includes the positioning coordinates and attitude angle of each laser point in the projection coordinate system at any time. For each laser point, based on the distance measurement value, angle measurement value, attitude angle, positioning coordinates, intrinsic and extrinsic parameters of the laser radar scanner system, the first coordinate vector of the laser point in the projected coordinate system is determined. For each laser point in the overlapping area of ​​adjacent flight strips, after constructing a plane using the laser point set of that laser point, the normal vector of that plane is obtained. The laser point set of that laser point includes that laser point and the laser points within a preset local range corresponding to that laser point that are located in the overlapping area. For all laser points located within the overlapping region and forming a plane, the laser point features of two laser points that satisfy the preset matching conditions are determined as a matching pair using the first coordinate vector of any two laser points in the projected coordinate system. A matching pair includes two laser point features, and each laser point feature includes the observed value of the laser point. Using the observed values ​​of each laser point in the matching pair, calculate the distance from each laser point in the matching pair to the plane; An optimization objective is constructed using the distance from the laser point to the plane. The optimization objective is then solved to obtain the first optimized value of the intrinsic parameters and the second optimized value of the extrinsic parameters. If the relationship between the first optimized value of the intrinsic parameter and the third optimized value of the previously determined intrinsic parameter satisfies the first preset optimization relationship, and the relationship between the second optimized value of the extrinsic parameter and the fourth optimized value of the previously determined extrinsic parameter satisfies the second preset optimization relationship, then the intrinsic parameter is calibrated using the first optimized value of the intrinsic parameter and the extrinsic parameter is calibrated using the second optimized value of the extrinsic parameter.

2. The method according to claim 1, characterized in that, After constructing a plane using the set of laser points, obtaining the normal vector of the plane includes: Obtain at least three feature values ​​of the laser point set, and calculate the flatness based on the at least three feature values ​​of the laser point set; If the flatness is greater than a preset flatness threshold, then the laser point is taken as a coordinate point on the plane, and the feature value that satisfies the preset condition among the at least three feature values ​​of the laser point set is taken as the normal vector of the plane where the laser point is located, so as to obtain the plane and the normal vector of the plane.

3. The method according to claim 2, characterized in that, The calculation of flatness based on at least three feature values ​​of the laser point set includes: Using formula Calculate the flatness, where p is the flatness. , and The laser point set consists of at least three characteristic values ​​that are sequentially increased in value. The step of using the feature value that satisfies the preset condition among the at least three feature values ​​of the laser point set as the normal vector of the plane where the laser point is located includes: using the feature value with the smallest value among the three feature values ​​as the normal vector of the plane where the laser point is located.

4. The method according to claim 1, characterized in that, For all laser points located within the overlapping region and forming a plane, the laser point features of two laser points satisfying a preset matching condition are determined as a matching pair using the first coordinate vector of any two laser points in the projected coordinate system. This includes: Based on the first coordinate vector of the two laser points in the projected coordinate system, the similarity of the laser point features of the two laser points is calculated, and the laser point features of the two laser points whose similarity satisfies the preset similarity condition are taken as candidate matching pairs. Calculate the standard deviation of similarity using the similarity of all candidate matching pairs; Based on the similarity standard deviation and the similarity of each candidate matching pair, candidate matching pairs that meet the preset matching conditions are selected as the matching pairs.

5. The method according to claim 1, characterized in that, For each laser point, determining the first coordinate vector of the laser point in the projected coordinate system based on the distance measurement value, angle measurement value, attitude angle, positioning coordinates, and intrinsic and extrinsic parameters of the laser radar scanner system includes: Based on the distance measurement value corresponding to the laser point, the angle measurement value corresponding to the laser point, and the intrinsic parameters, calculate the second coordinate vector of the laser point in the scanner coordinate system; Based on the placement angle error in the extrinsic parameters, a first rotation matrix is ​​constructed; Using the second coordinate vector of the laser point in the scanner coordinate system, the first rotation matrix, and the lever arm offset in the extrinsic parameters, the third coordinate vector of the laser point in the inertial measurement system coordinate system is calculated. The inertial measurement system coordinate system is the coordinate system corresponding to the inertial measurement system. The heading angle in the attitude angle corresponding to the laser point is converged and corrected to obtain the corrected attitude angle; Based on the corrected attitude angle, a second rotation matrix is ​​constructed from the inertial measurement system coordinate system to the projected coordinate system; Based on the third coordinate vector of the laser point in the inertial measurement system coordinate system, the second rotation matrix, and the positioning coordinates, the first coordinate vector of the laser point in the projection coordinate system is determined.

6. The method according to claim 5, characterized in that, The step of calculating the second coordinate vector of the laser point in the scanner coordinate system based on the distance measurement value corresponding to the laser point, the angle measurement value corresponding to the laser point, and the intrinsic parameters includes: Calculate the second coordinate vector of the laser point in the scanner coordinate system using the formula: In the formula, X l Let l represent the second coordinate vector, α represent the distance value corresponding to the laser point, Δl represent the distance correction amount, and Δα represent the angle correction amount. The intrinsic parameters include the distance correction amount and the angle correction amount. And / or, The construction of the first rotation matrix based on the placement angle error in the extrinsic parameters includes: Construct the first rotation matrix using the formula: In the formula, ( The ) represents the installation angle error, ΔR M Represents the first rotation matrix; And / or, Using the second coordinate vector of the laser point in the scanner coordinate system, the first rotation matrix, and the lever arm offset in the extrinsic parameters, the third coordinate vector of the laser point in the inertial measurement system coordinate system is calculated as follows: Calculate the third coordinate vector of the laser point using the formula: In the formula, X I Represents the third coordinate vector, ΔR M Let X represent the first rotation matrix. l This represents the second coordinate vector, and Δt represents the offset of the lever arm value; And / or, The construction of the second rotation matrix from the inertial measurement system coordinate system to the projected coordinate system based on the corrected attitude angle includes: the second rotation matrix is... in, , , In the formula, (r, p, H) represents the corrected attitude angle, and R N Indicates the second rotation matrix; The step of determining the first coordinate vector of the laser point in the projected coordinate system based on the third coordinate vector of the laser point in the inertial measurement system coordinate system, the second rotation matrix, and the positioning position coordinates includes: calculating the first coordinate vector of the laser point using the formula: In the formula, X I Let X represent the third coordinate vector. p Let X represent the first coordinate vector. g R represents the location coordinates. N This represents the second rotation matrix.

7. The method according to claim 1, characterized in that, The observed values ​​of the laser point include: the distance measurement value corresponding to the laser point, the angle measurement value corresponding to the laser point, the normal vector of the plane, and the positioning coordinates; calculating the distance from each laser point in the matching pair to the plane using the observed values ​​of each laser point in the matching pair includes: The distance from the laser point to the plane is calculated using the formula: in, In the formula, This represents the distance from a point to a plane. This represents the normal vector in the observation value of the first laser point in the matching pair. This represents the second rotation matrix corresponding to the first laser point in the matching pair. This represents the second rotation matrix corresponding to the second laser point in the matching pair. This represents the corrected attitude angle corresponding to the first laser point in the matching pair. ΔR represents the corrected attitude angle corresponding to the second laser point in the matching pair. M Denotes the first rotation matrix. This represents the distance measurement value in the observation of the first laser point in the matching pair. This represents the angle measurement value in the observation of the first laser point in the matching pair. Indicates the distance measurement correction amount. Indicates the angle measurement correction amount. This represents the distance measurement value in the observation of the second laser point in the matching pair. This represents the angle measurement value in the observation of the second laser point in the matching pair. Indicates the offset of the lever arm value. This represents the location coordinates of the first laser point in the matching pair. This represents the location coordinates of the second laser point in the matching pair.

8. The method according to claim 7, characterized in that, The step of constructing an optimization objective using the distance from the laser point to the plane, and solving the optimization objective to obtain the first optimized value of the intrinsic parameters and the second optimized value of the extrinsic parameters includes: An error equation is constructed using the distance from the laser point to the plane. ; Based on the principle of least squares, the intrinsic and extrinsic parameters are optimized to obtain a first optimized value for the intrinsic parameters and a second optimized value for the extrinsic parameters. The optimization process aims to achieve a sum of squares of the distances from the laser point to the plane. Minimum, N is the total number of matching pairs, and the sum of the squares of the distances from the laser points to the plane. The minimum is the optimization objective.

9. The method according to any one of claims 1 to 8, characterized in that, The method further includes: if the relationship between the first optimized value of the intrinsic parameter and the third optimized value of the previously determined intrinsic parameter does not satisfy the first preset optimization relationship, and / or the relationship between the second optimized value of the extrinsic parameter and the fourth optimized value of the previously determined extrinsic parameter does not satisfy the second preset optimization relationship, then the intrinsic parameter is adjusted using the first optimized value of the intrinsic parameter and the extrinsic parameter is adjusted using the second optimized value of the extrinsic parameter, the first optimized value determined this time is used as the third optimized value and the second optimized value determined this time is used as the fourth optimized value, and for each laser point, based on the ranging value corresponding to the laser point, the angle value corresponding to the laser point, the attitude angle corresponding to the laser point, the positioning coordinates corresponding to the laser point, and the intrinsic and extrinsic parameters of the laser radar scanner system, the first coordinate vector of the laser point in the projected coordinate system is determined.

10. A parameter calibration device, characterized in that, An application is made in a lidar scanner system, the lidar scanner system comprising an integrated navigation system, an aircraft, an inertial measurement system, and a lidar scanner, the lidar scanner being mounted on the aircraft, the device comprising: The first acquisition unit is used to acquire the original point cloud data of multiple flight strips collected by the lidar scanner, and the flight trajectory data collected by the integrated navigation system within the same time period. The original point cloud data includes the distance and angle values ​​of each laser point in the multiple flight strips in the scanner coordinate system corresponding to the lidar scanner, and the flight trajectory data includes the positioning coordinates and attitude angle of each laser point in the projection coordinate system at any time. The first determining unit is used to determine the first coordinate vector of each laser point in the projected coordinate system based on the ranging value, the angle value, the attitude angle, the positioning coordinates, and the intrinsic and extrinsic parameters of the laser radar scanner system. The second acquisition unit is used to acquire the normal vector of each laser point in the overlapping area of ​​adjacent flight strips after constructing a plane using the laser point set of the laser point. The laser point set of the laser point includes the laser point and the laser point within a preset local range corresponding to the laser point and located in the overlapping area. The second determining unit is used to determine the laser point features of two laser points that satisfy the preset matching conditions as a matching pair for all laser points located in the overlapping area and constructing a plane, using the first coordinate vector of any two laser points in the projection coordinate system. A matching pair includes two laser point features, and each laser point feature includes the observed value of the laser point. The first calculation unit is used to calculate the distance from each laser point in the matching pair to the plane using the observed value of each laser point in the matching pair; The second calculation unit is used to construct an optimization target using the distance from the laser point to the plane, and solve the optimization target to obtain the first optimized value of the intrinsic parameters and the second optimized value of the extrinsic parameters. The calibration unit is configured to calibrate the intrinsic parameter using the first optimized value of the intrinsic parameter and the third optimized value of the previously determined intrinsic parameter if the relationship between the first optimized value of the intrinsic parameter and the third optimized value of the previously determined intrinsic parameter satisfies a first preset optimization relationship, and the relationship between the second optimized value of the extrinsic parameter and the fourth optimized value of the previously determined extrinsic parameter satisfies a second preset optimization relationship.

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