A method for positioning using an inclination measuring device and an inclination measuring device

Abstract

The embodiment of the present application discloses a method and a tilt measurement device for positioning using a tilt measurement device. The method includes: initializing the GNSS / INS combined navigation system with the heading angle of INS as 0; obtaining the combined solution result of the GNSS / INS combined navigation system at the i-th moment; determining the heading angle error of the INS at the i-th moment according to the combined solution result at the i-th moment; correcting the attitude matrix determined by the initialization according to the heading angle error to obtain the estimated value of the attitude matrix at the i-th moment; obtaining the combined solution result determined by the estimated value of the attitude matrix at the i-th moment; correcting the estimated value of the attitude matrix according to the error corresponding to the combined solution result determined by the estimated value of the attitude matrix to obtain the accurate value of the attitude matrix; and performing positioning operation on the position to be measured using the accurate value of the attitude matrix.

Description

Technical Field

[0001] The embodiments of the present application relate to the field of information processing, and more particularly to a method for positioning using a tilt measurement device and a tilt measurement device. Background Art

[0002] With the development of the Global Navigation Satellite System (GNSS), four major satellite navigation systems have been formed, including the Global Positioning System (GPS), the Global Navigation Satellite System (GLONASS), the Galileo, and the Beidou Navigation Satellite System (BDS). The products of real-time differential positioning (RTK) based on GNSS high-precision positioning are becoming more and more mature, and are widely used in the fields of surveying and mapping, precision navigation, etc., playing an increasingly important role in the fields of people's livelihood and national defense. Among them, the surveying and mapping receiver based on RTK is usually in an open scene, and the GNSS antenna is not blocked by buildings, shades of trees, etc. Otherwise, the GNSS antenna is blocked, which will make it impossible to track the effective GNSS satellite signal, resulting in high-precision RTK positioning results.

[0003] For traditional surveying receivers, the GNSS antenna is at the top of the measuring rod. The RTK result is the position of the antenna phase center, and the measured point is the position of the rod tip. Therefore, it is usually required that the level bubble on the centering rod be centered during measurement, that is, the measuring rod is perpendicular to the ground, and the longitude and latitude of the RTK positioning are the longitude and latitude of the rod tip. The height of the measuring point is the height of the RTK positioning minus the height of the measuring rod. This operation method requires adjusting the measuring rod to center the level bubble, which has low operation efficiency. In addition, due to environmental restrictions, the centering rod cannot be made vertical at corners, under bridges, pipelines, etc., making it difficult to achieve RTK measurement.

[0004] By using the tilt measurement technology, the measuring rod does not need to be vertically centered, and the system can “stop and measure, and leave after measuring”. This can improve work efficiency, expand the scope of work, and solve the problem that the centering rod cannot measure at special points such as corners and under bridges. There are two existing measurement technology solutions. One is to “shake” the centering rod to collect RTK positioning results at multiple times, use the length of the centering rod as a distance constraint, construct a spatial intersection observation equation, and use least squares and other algorithms to calculate the position information of the tip of the rod; the other is to use the RTK / IMU / magnetometer combination solution to obtain the attitude matrix of the IMU (Inertial Measurement Unit), and convert the RTK position of the antenna phase center to compensate for the rod length to obtain the position information at the tip of the rod.

[0005] In practical applications, existing technical solutions have certain requirements on the use environment, which will limit the measurement efficiency and application scenarios. Summary of the invention

[0006] In order to solve any of the above technical problems, the embodiments of the present application provide a method for positioning using a tilt measurement device and a tilt measurement device.

[0007] In order to achieve the purpose of the embodiment of the present application, the embodiment of the present application provides a method for positioning using a tilt measurement device, wherein the tilt measurement device includes an antenna, a GNSS receiver, an IMU and a measuring rod, wherein the GNSS receiver and the IMU arranged on the measuring rod form a GNSS / INS integrated navigation system, and the method includes:

[0008] Initialize the GNSS / INS integrated navigation system with the INS heading angle as 0;

[0009] Obtain the combined solution result of the GNSS / INS integrated navigation system at the i-th moment;

[0010] According to the combined solution result at the i-th moment, determine the heading angle error at the i-th moment in the INS;

[0011] According to the heading angle error, the attitude matrix determined by initialization is corrected to obtain the estimated value of the attitude matrix at the i-th moment

[0012] Get the estimated value of the posture matrix at the i-th moment The determined combined solution result;

[0013] According to the estimated value of the posture matrix The error corresponding to the determined combined solution result is the estimated value of the attitude matrix Make corrections to obtain the accurate value of the attitude matrix;

[0014] The accurate value of the attitude matrix is ​​used to locate the position to be measured.

[0015] A storage medium stores a computer program, wherein the computer program is configured to execute the method described above when running.

[0016] An electronic device comprises a memory and a processor, wherein the memory stores a computer program, and the processor is configured to run the computer program to execute the method described above.

[0017] A tilt measuring device is provided with a measuring rod, wherein an antenna, a GNSS receiver and an IMU unit are arranged on the measuring rod, and the device also includes the electronic device mentioned above.

[0018] One of the above technical solutions has the following advantages or beneficial effects:

[0019] The error of the attitude matrix is ​​gradually corrected in a coarse-to-fine order, so that the system's combined positioning settlement tends to be high-precision. It is applicable to both consumer-grade IMUs or mid-to-high-end IMUs, and does not require a magnetometer, reducing dependence on the environment and having strong versatility.

[0020] In addition, the arm vector error is estimated, which is compatible with tilted installation of the IMU or bending of the measuring rod, and is robust and practical.

[0021] Other features and advantages of the embodiments of the present application will be described in the subsequent description, and partly become apparent from the description, or can be understood by implementing the embodiments of the present application. The purpose and other advantages of the embodiments of the present application can be achieved and obtained by the structures specifically pointed out in the description, claims and drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] The accompanying drawings are used to provide further understanding of the technical solutions of the embodiments of the present application and constitute a part of the specification. Together with the embodiments of the embodiments of the present application, they are used to explain the technical solutions of the embodiments of the present application and do not constitute a limitation on the technical solutions of the embodiments of the present application.

[0023] Figure 1 A schematic diagram of a GNSS / INS all-in-one surveying and mapping machine provided in an embodiment of the present application;

[0024] Figure 2 A flowchart of a method for positioning using a tilt measurement device provided in an embodiment of the present application;

[0025] Figure 3 A schematic diagram of a method for implementing INS coarse alignment provided in an embodiment of the present application;

[0026] Figure 4 A schematic diagram of a method for implementing INS fine alignment provided in an embodiment of the present application;

[0027] Figure 5 A schematic diagram of a method for determining a rod tip position provided in an embodiment of the present application. DETAILED DESCRIPTION

[0028] In order to make the purpose, technical solution and advantages of the embodiments of the present application more clear, the embodiments of the present application will be described in detail in conjunction with the accompanying drawings. It should be noted that, in the absence of conflict, the embodiments and features in the embodiments of the present application can be combined with each other arbitrarily.

[0029] In the process of implementing this application, a technical analysis of the relevant technologies was conducted and it was found that the relevant technologies have at least the following problems, including:

[0030] The existing tilt measurement technology solution 1 requires the measuring rod to be "shaken", which is not possible in some scenarios, such as corners and points under bridges. This solution solves the problem of not needing to make the centering rod vertical, and requires the working environment to be as open as possible;

[0031] The existing tilt measurement technology solution 2 uses IMU / magnetometer to initialize and solve the attitude angles (pitch angle, roll angle and heading angle). The attitude matrix is ​​easily affected by external magnetic interference. For example, near the transformer or when a car passes by, it will cause a large error in the azimuth angle, making the attitude matrix wrong, resulting in an error in the tilt measurement position.

[0032] Based on the above analysis, the embodiment of the present application adopts the RTK / IMU technical solution, and through improved algorithms and designs, adopts a federal filter algorithm architecture to reduce dependence on the test environment and achieve fast and efficient tilt measurement goals. On the one hand, the present application can quickly correct the heading angle error without the need for a magnetometer and is not affected by the environment; on the other hand, it can estimate the arm error of the measuring rod in real time online, reducing the error caused by arm bending or IMU installation deviation. These two key error terms interact through the federal filter architecture to improve the attitude accuracy and arm vector accuracy of the Inertial Navigation System (INS), thereby improving the accuracy of the tilt measurement point.

[0033] Figure 1 Schematic diagram of the GNSS / INS integrated surveying and mapping machine provided in the embodiment of the present application. Figure 1 As shown, the surveying and mapping machine includes a measuring antenna, a GNSS receiver, an IMU and a measuring rod, and obtains the position information of the rod tip through an algorithm. Among them, the IMU used in this application includes a three-axis gyroscope and a three-axis accelerometer, which can be a consumer-grade IMU or a medium-performance IMU, and both are applicable to the solution of this application.

[0034] Figure 2 This is a flow chart of a method for positioning using a tilt measurement device provided in an embodiment of the present application. Figure 2 As shown, a GNSS / INS integrated navigation system composed of a GNSS receiver and an IMU, the method includes:

[0035] Step 201, initializing the GNSS / INS integrated navigation system with the heading angle of INS as 0;

[0036] In an exemplary embodiment, when initializing the integrated navigation system, the surveying pole is kept upright and the tip of the surveying pole is kept in contact with the ground, so that the error of the initialized PVA information is small during the initial alignment of the INS.

[0037] Step 202: Obtain the combined solution result of the GNSS / INS integrated navigation system at the i-th moment;

[0038] In an exemplary embodiment, a Kalman filter corresponding to a GNSS / INS integrated navigation system is constructed to perform a combined solution operation.

[0039] Step 203, determining the heading angle error at the i-th moment in the INS according to the combined solution result at the i-th moment;

[0040] Step 204: According to the heading angle error, the initialization determined attitude matrix is ​​corrected to obtain an estimated value of the attitude matrix at the i-th moment.

[0041] Step 205: Obtain the estimated value of the posture matrix at the i-th moment The determined combined solution result;

[0042] Step 206: Based on the estimated value of the posture matrix The error corresponding to the determined combined solution result is the estimated value of the attitude matrix Make corrections to obtain the accurate value of the attitude matrix;

[0043] Step 207: Use the accurate value of the attitude matrix to perform a positioning operation on the position to be measured.

[0044] The method provided in the embodiment of the present application adopts a coarse-to-fine sequence to gradually correct the error of the attitude matrix, so that the combined positioning settlement of the system tends to be high-precision. It is applicable to consumer-grade IMUs or mid-to-high-end IMUs, and does not require a magnetometer, reducing dependence on the environment and having strong versatility.

[0045] The method provided in the embodiment of the present application is described below:

[0046] The method provided in the embodiment of the present application uses two filters to gradually correct the error in a coarse-to-fine order; wherein:

[0047] The first filter is a GNSS / INS combined solution filter, which is used to provide the initial attitude matrix

[0048] The second filter is a processing filter for attitude error, lever arm error and lever tip position, which corrects the initial attitude matrix The large heading angle error Δψ in the first filter is used to obtain an estimated value of the attitude matrix Then, small errors are corrected, including the rod tip position error ΔP, the attitude error angle vector Φ and the rod arm vector error Δl, so that the system state quantity converges to a high-precision value.

[0049] Figure 3 Schematic diagram of a method for implementing INS coarse alignment provided in an embodiment of the present application. Figure 3 As shown, the GNSS / INS combined positioning system is initialized with a heading angle of 0, and the combined solution operation is completed based on the first filter. The second filter solves the heading angle error based on the combined solution result of the first filter to correct the larger error in the initial attitude matrix. The specific implementation method is as follows:

[0050] Step 301, statically initialize the position, velocity and attitude of INS;

[0051] Specifically, a GNSS / INS combined solution filter is constructed, that is, the first filter mentioned above; wherein the state quantity of the GNSS / INS combined solution filter is as follows:

[0052] where δR n Denotes the three-dimensional position error, δV n represents the three-dimensional velocity error, represents the three-dimensional posture error, ▽ b Indicates the zero bias of the three-axis accelerometer, Indicates the three-axis gyroscope zero bias, a total of 15 dimensions.

[0053] Position error differential equation:

[0054]

[0055] Velocity error differential equation:

[0056]

[0057] Attitude error differential equation:

[0058]

[0059] The zero bias modeling of the three-axis accelerometer and the zero bias modeling of the three-axis gyroscope are both first-order Gauss-Markov processes:

[0060]

[0061]

[0062] where τ ba , τ bg Represents the three-axis acceleration zero bias ▽ b and three-axis gyro bias relevant time.

[0063] Combining the above formulas into the following format:

[0064]

[0065] Discretizing the continuous differential equation, it becomes the following form:

[0066] X(k+1)=(I+FΔT)X(k) (6)

[0067] The (I+FΔT) in the above formula is the transfer matrix under discrete state, which is used to predict the state quantity and error covariance matrix according to the Kalman filter algorithm formula.

[0068] The state quantity can also be expanded by adding the IMU scale factor error, and the state quantity becomes 21 dimensions, that is, where δs a is the three-axis scale factor error of the accelerometer, δs g is the three-axis scale factor error of the gyroscope, which is modeled as a first-order Gauss-Markov process, and its differential equation is:

[0069]

[0070]

[0071] In the scenario with good GNSS signal, RTK can obtain a fixed solution; keep the measuring rod still, initialize the position, velocity and attitude (PVA) information of INS, where the initialization position of INS comes from RTK, and the velocity information of INS is initialized to zero; initialize the attitude information according to the measurement information of accelerometer,

[0072] Pitch Angle

[0073] Roll Angle

[0074] Since the zero bias of the gyro is large, the heading cannot be determined, so the heading angle ψ is initialized to 0. At this time, there is a large error in the heading angle.

[0075] After the INS completes the initial alignment, the GNSS / INS combined filter observation equation is constructed based on the combined solution results of GNSS or the observation information such as pseudorange, carrier, Doppler, etc., and the state quantity X is estimated and corrected using loose combination or tight combination mode to improve the accuracy of each state of INS. The attitude matrix of INS can be obtained This Kalman filter is referred to herein as the first filter.

[0076] During the initial alignment of the INS, the tip of the measuring rod is in contact with the ground and the rod body is kept as upright and still as possible, so that the error of the initialized PVA information is small.

[0077] Step 302: Perform a combined solution operation using the initial posture matrix;

[0078] Step 303, correcting the heading angle error according to the combined solution result corresponding to the initial attitude matrix;

[0079] The position of the rod tip P O In the first step of INS initialization, the rod body remains approximately upright, and the position P of the IMU can be A Subtract the length of the measuring rod l to get May as well is the attitude matrix solved by GNSS / INS fusion; since l x , l y is a smaller value, let l x ≈0,l y ≈0, then

[0080] Get the position information P of the IMU at the same time in the horizontal coordinate system A , measuring the position information of the tip of the rod P O and the lever arm vector;

[0081] According to the IMU position information P A The position information P of the measuring rod tip O The difference between the lever arm vector and the initial posture matrix is ​​obtained to obtain the first difference (Δx1, Δy1, Δz1); and Obtain the second difference (Δx2, Δy2, Δz2);

[0082] The heading angle error is determined using the first difference and the second difference.

[0083] The calculation expression is as follows:

[0084]

[0085]

[0086] Substituting equations (9) and (10) into equation (16), we can obtain:

[0087]

[0088] From the above formula, the heading angle error can be obtained as:

[0089] Δψ=atan2(Δy2*Δx1-Δx2*Δy1,Δx2*Δx1+Δy2*Δy1) (12)

[0090] In the process of correcting the heading angle initialization error, the tip of the measuring rod is kept in contact with the ground so that the position of the rod tip remains unchanged. The antenna on the top of the rod is tilted to a certain position, and the heading error angle Δψ is calculated according to formula (12).

[0091] Step 304: Correct the initial attitude matrix using the heading angle error Δψ to obtain an estimated value of the attitude matrix at the i-th moment;

[0092] like Figure 1 As shown, the lever arm vector l OA =[l x l y l] T , l x , l y It is the deviation caused by the bending of the lever arm or the installation error. It is usually a relatively small value and is an unknown quantity. l is the length of the lever arm and is a known quantity. It satisfies the following equation:

[0093]

[0094] Among them, P A(i) is the position information of IMU at time i, P O is the position information of the rod tip. The coordinate system of these two positions is the local horizontal coordinate system. is the exact value of the IMU attitude matrix at time i.

[0095] After the initial alignment of the INS, the heading angle error is large, with a maximum possible error of 180 degrees, which is the attitude matrix determined by the initialization of the INS. There is a large heading angle error Δψ. Using the initial attitude matrix And the preset correction matrix C(Δψ), the initial posture matrix at the i-th moment is obtained

[0096]

[0097]

[0098] Substituting formula (14) into formula (13), we can obtain:

[0099]

[0100] In the above formula, P A(i) is the position information of IMU at time i, which comes from the combined solution of GNSS / INS.

[0101] After obtaining the heading angle error Δψ according to formula (12), the attitude matrix is ​​corrected according to formula (14) to obtain the estimated value of the attitude matrix at the i-th moment with a smaller error:

[0102] Figure 4 Schematic diagram of a method for implementing INS fine alignment provided in an embodiment of the present application. Figure 4 As shown, the first filter performs combined solution using the GNSS / INS combined positioning system after coarse alignment, and provides the combined solution result to the second filter to obtain the convergence of the state quantity, so as to obtain the accurate values ​​of the attitude error angle vector and the lever arm vector; the first filter obtains the accurate value of the attitude matrix based on the attitude error angle vector, and through the interaction between the first filter and the second filter, the accurate value of the attitude matrix and the accurate value of the lever arm vector with high precision can be finally obtained.

[0103] The specific implementation method is as follows:

[0104] Obtaining a position measurement value and an attitude matrix of the IMU determined by a first solution equation, wherein the first solution equation is an equation used for positioning operation of a GNSS / INS integrated navigation system, wherein the state quantity of the first solution equation is an error value of a parameter used by the first solution equation, and the output quantity is the position information and attitude matrix of the IMU;

[0105] Taking the attitude matrix error, the lever arm error and the lever tip position error as state quantities, and the relationship between the position measurement value of the IMU, the attitude matrix and the lever tip position, a second solution equation is constructed;

[0106] Repeat the following operations until the errors of the attitude matrix, the lever arm error, and the position of the rod tip in the second solution equation converge, and obtain the error of the lever arm vector and the error of the attitude matrix, including:

[0107] Step A1, based on the first solution equation, using the estimated value of the lever arm vector and the estimated value of the attitude matrix to obtain an estimated value of the position of the measuring rod tip;

[0108] Step A2, using the estimated value of the lever arm vector, the estimated value of the attitude matrix, the estimated value of the position of the measuring rod tip and the position of the IMU, training the second solution equation to obtain the error of the lever arm vector, the error of the attitude matrix and the error of the rod tip position;

[0109] Step A3, judging whether the error of the lever arm vector, the error of the attitude matrix and the error of the lever tip position have converged according to the observation residual of the second observation equation; if not, proceeding to step A4;

[0110] Step A4, determining the accurate value of the lever arm vector and the accurate value of the attitude matrix according to the error of the lever arm vector and the error of the attitude matrix;

[0111] Step A5, update the accurate value of the lever arm vector to the measured value of the lever arm vector in the second solution equation; and update the accurate value of the attitude matrix to the estimated value of the attitude matrix in the first solution equation, and continue to execute step A1.

[0112] Due to the tip position There is error, attitude matrix There is an error, the lever arm vector There is an error, and the relationship between it and the true value is:

[0113]

[0114]

[0115]

[0116] Where ΔP = [dx dy dz] T is the position error of the rod tip O; I is the unit matrix, Φ = [φ x φ y φ z ] T is the attitude error angle vector, Φ× is the cross product antisymmetric matrix; Δl=[dl x dl y 0] T is the arm vector error; these three error terms are modeled as Gaussian white noise errors and constructed into the state quantity of the Kalman filter. Let the state quantity of this filter be:

[0117] X2=[dx dy φ z φ x φ y φ z dl x dl y ] T (18)

[0118] Substituting formula (17) into formula (13), we can get:

[0119]

[0120] The left side of the above formula is the observed quantity, and the right side is the observation equation, which can be written in the form of Z=HX. Then, the measurement update is performed according to the Kalman filter, and the state quantity X2 is continuously estimated. This filter may be called the second Kalman filter.

[0121] After the state quantity Φ is estimated, the information is sent to the first Kalman filter, such as Figure 4 As shown, in the first filter, the INS attitude matrix is ​​calibrated using the algorithm of formula (17) To perform error correction, or to construct the observation equation in the first filter using Φ as the observation quantity for measurement update, the INS attitude matrix Perform error correction to obtain the corrected As the pose matrix of the first filter.

[0122] When the Kalman filter measurement is updated according to the observation equation (19), the tip of the measuring rod is in contact with the ground so that the position of the tip of the rod remains unchanged, and the antenna on the top of the rod is shaken "front and back, left and right" to speed up the convergence of the state quantity.

[0123] Figure 5 Schematic diagram of a method for determining the rod tip position provided in an embodiment of the present application. Figure 5 As shown, after the first filter determines the position of the rod tip, the compensation value corresponding to the measured value of the position to be measured is determined according to the accurate value of the attitude matrix and the accurate value of the rod arm vector; the measured value of the position to be measured is corrected using the compensation value to obtain high-precision positioning information of the position to be measured.

[0124] Under the joint solution of the first filter and the second filter, after a period of iteration, the accurate value of the lever arm vector l can be converged. OA , the accurate value of the high-precision attitude matrix Then stop the second filter, move the tip of the measuring rod to the point to be measured, and measure the position of the tip of the rod.

[0125] Specifically, when determining the estimated value of the attitude matrix The error of the lever arm vector of the measuring rod is determined at the same time, and the accurate value of the lever arm vector is determined based on the error of the lever arm vector;

[0126] After the position to be measured is positioned using the accurate value of the attitude matrix, a compensation value corresponding to the measured value of the position to be measured is determined according to the accurate value of the attitude matrix and the accurate value of the lever arm vector; the measured value of the position to be measured is corrected using the compensation value to obtain positioning information of the position to be measured,

[0127] The position information P calculated by GNSS / INS A(i) According to formula (20), the position of the rod tip is:

[0128]

[0129] Get the rod tip point P in the local horizontal coordinate system O(i) After finding the location, coordinate conversion can be performed to obtain the longitude, latitude and altitude information of the point.

[0130] The first filter and the second filter can work together and independently, and the accurate value of the attitude matrix and the exact value of the lever arm vector l OA After convergence, the second filter is turned off, and only the first filter is retained to continuously output high-precision attitude information array. After the measuring rod is moved to a new measuring point, the position of the rod tip can be obtained according to formula (20);

[0131] During the tilt test, you only need to perform a static-shaking operation before measurement to complete the INS attitude convergence and arm arm vector estimation. Then you can move the measuring rod to the point to be tested and output the position information of the point to be tested. The whole process is simple to operate and easy to use.

[0132] In summary, this application uses the GNSS / IMU hardware solution to achieve tilt measurement, which is applicable to consumer-grade IMU or mid-to-high-end IMU. It does not require a magnetometer, reduces dependence on the environment, and has strong versatility. In addition, the federal filter architecture design is adopted to gradually correct the error in a coarse-to-fine order, that is, the first filter provides an initial attitude matrix The second filter first corrects The large heading angle error Δψ is corrected, and then the smaller errors, including the rod tip position error ΔP, the attitude error angle vector Φ and the rod arm vector error Δl, are corrected, so that the state quantity of the system converges to a high-precision value.

[0133] An embodiment of the present application provides a storage medium, in which a computer program is stored, wherein the computer program is configured to execute any of the methods described above when running.

[0134] An embodiment of the present application provides an electronic device, including a memory and a processor, wherein the memory stores a computer program, and the processor is configured to run the computer program to execute any of the methods described above.

[0135] An embodiment of the present application provides a tilt measuring device, wherein the device is provided with a measuring rod, wherein an antenna, a GNSS receiver and an IMU unit are provided on the measuring rod, and the device also includes the electronic device described above.

[0136] It will be appreciated by those skilled in the art that all or some of the steps, systems, and functional modules / units in the methods disclosed above may be implemented as software, firmware, hardware, and appropriate combinations thereof. In hardware implementations, the division between the functional modules / units mentioned in the above description does not necessarily correspond to the division of physical components; for example, a physical component may have multiple functions, or a function or step may be performed by several physical components in cooperation. Some or all components may be implemented as software executed by a processor, such as a digital signal processor or a microprocessor, or implemented as hardware, or implemented as an integrated circuit, such as an application-specific integrated circuit. Such software may be distributed on a computer-readable medium, which may include a computer storage medium (or non-transitory medium) and a communication medium (or temporary medium). As known to those skilled in the art, the term computer storage medium includes volatile and non-volatile, removable and non-removable media implemented in any method or technology for storing information (such as computer-readable instructions, data structures, program modules, or other data). Computer storage media include, but are not limited to, RAM, ROM, EEPROM, flash memory or other memory technology, CD-ROM, digital versatile disks (DVD) or other optical disk storage, magnetic cassettes, magnetic tapes, magnetic disk storage or other magnetic storage devices, or any other medium that can be used to store the desired information and can be accessed by a computer. In addition, it is well known to those of ordinary skill in the art that communication media typically contain computer-readable instructions, data structures, program modules, or other data in a modulated data signal such as a carrier wave or other transport mechanism, and may include any information delivery media.

Claims

1. A method for positioning using a tilt measuring device, characterized in that: The tilt measurement device comprises an antenna, a GNSS receiver, an IMU and a measuring rod, wherein the GNSS receiver and the IMU arranged on the measuring rod form a GNSS / INS integrated navigation system, and the method comprises: Initialize the GNSS / INS integrated navigation system with the INS heading angle as 0; Obtain the combined solution result of the GNSS / INS integrated navigation system at the i-th moment; According to the combined solution result at the i-th moment, determine the heading angle error at the i-th moment in the INS; According to the heading angle error, the attitude matrix determined by initialization is corrected to obtain the estimated value of the attitude matrix at the i-th moment ; Get the estimated value of the posture matrix at the i-th moment The determined combined solution result; According to the estimated value of the posture matrix The error corresponding to the determined combined solution result is the estimated value of the attitude matrix Make corrections to obtain the accurate value of the attitude matrix; Use the accurate value of the attitude matrix to locate the position to be measured; The method also includes: determining the error of the estimated value of the attitude matrix and the error of the lever arm vector of the measuring rod, and determining the accurate value of the lever arm vector based on the error of the lever arm vector; after using the accurate value of the attitude matrix to perform a positioning operation on the position to be measured, determining the compensation value corresponding to the measured value of the position to be measured based on the accurate value of the attitude matrix and the accurate value of the lever arm vector, and using the compensation value to correct the measured value of the position to be measured to obtain the positioning information of the position to be measured.

2. The method according to claim 1, characterized in that The error of the arm vector and the error of the attitude matrix are obtained by the following methods, including: Obtaining a position measurement value and an attitude matrix of the IMU determined by a first solution equation, wherein the first solution equation is an equation used for a positioning operation of a GNSS / INS integrated navigation system, wherein a state quantity of the first solution equation is an error value of a parameter used by the first solution equation, and an output quantity is a position measurement value and an attitude matrix of the IMU; The second solution equation is constructed by taking the error of the attitude matrix, the error of the lever arm vector, and the error of the position of the rod tip as state quantities and taking the relationship between the position measurement value of the IMU, the estimated value of the lever arm vector, the attitude matrix, and the position of the rod tip into consideration; Repeat the following operations until the error of the attitude matrix, the error of the lever arm vector, and the error of the rod tip position in the second solution equation converge, and obtain the error of the lever arm vector and the error of the attitude matrix, including: Step A1, based on the first solution equation, using the estimated value of the lever arm vector and the estimated value of the attitude matrix to obtain an estimated value of the position of the measuring rod tip; Step A2, using the estimated value of the lever arm vector, the estimated value of the attitude matrix, the estimated value of the position of the measuring rod tip and the position of the IMU, the second solution equation is trained to obtain the error of the lever arm vector, the error of the attitude matrix and the error of the rod tip position; Step A3, judging whether the error of the lever arm vector, the error of the attitude matrix and the error of the lever tip position have converged according to the observation residual of the second observation equation; if not, proceeding to step A4; Step A4, determining the accurate value of the lever arm vector and the accurate value of the attitude matrix according to the error of the lever arm vector and the error of the attitude matrix; Step A5, update the accurate value of the lever arm vector to the measured value of the lever arm vector in the second solution equation; and update the accurate value of the attitude matrix to the estimated value of the attitude matrix in the first solution equation, and continue to execute step A1.

3. The method according to claim 2, characterized in that The expression of the second solution equation is as follows: ； represents the position information of the IMU at the i-th moment, represents the estimated position of the tip of the measuring rod at the i-th epoch, represents the estimated value of the attitude matrix at the i-th epoch, represents the estimated value of the lever arm vector at the i-th epoch; is the position error of the rod tip point O; is the attitude angle error vector, is the error in the lever arm vector.

4. The method according to claim 1, characterized in that: Determining the heading angle error at the i-th moment in the INS according to the combined solution result at the i-th moment includes: Get the position information of IMU at the same time in the horizontal coordinate system , measuring rod tip position information and the lever arm vector; According to the position information of IMU Position information with the tip of the measuring rod The first difference is obtained ( , , ); and, according to the lever arm vector and the initial posture matrix , and obtain the second difference ( , , ); The heading angle error is determined using the first difference and the second difference.

5. The method according to claim 4, characterized in that The heading angle error is obtained by the following calculation expression ,include: 。 6. The method according to claim 5, characterized in that The estimated value of the posture matrix at the i-th moment is obtained by the following calculation expression: ,include: Using the initial pose matrix and the preset correction matrix , get the estimated value of the posture matrix at the i-th moment ;in: 。 7. A storage medium, characterized in that: The storage medium stores a computer program, wherein the computer program is configured to execute the method according to any one of claims 1 to 6 when executed.

8. An electronic device comprising a memory and a processor, characterized in that: A computer program is stored in the memory, and the processor is configured to run the computer program to perform the method according to any one of claims 1 to 6.

9. A tilt measuring device, characterized in that: The device is provided with a measuring rod, wherein an antenna, a GNSS receiver and an IMU unit are arranged on the measuring rod, and the device also includes the electronic device as claimed in claim 8.

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