GNSS-assisted MINS automatic calibration system and method

Abstract

The present invention provides a GNSS-assisted MINS automatic calibration system, which uses the speed and position information of GNSS as an aid, combines the speed, position information and attitude angle information of the MEMS inertial navigation system, uses an automatic calibration method, estimates the installation error angle and accelerometer error, eliminates them, reduces the angle error of the MEMS inertial navigation system, and improves the speed accuracy and position accuracy of the MEMS inertial navigation system. The automatic calibration system and method of the present invention have no strict restrictions on the conditions during the movement of the carrier, have low computational complexity, and are easy to implement.

Description

Technical Field

[0001] The invention relates to the field of inertial technology, and in particular to a calibration technology of a MEMS inertial navigation system in integrated navigation. Background Art

[0002] MEMS inertial navigation system (MINS) is low-cost, highly resistant to interference, has high accuracy in a short period of time, and has a high data update frequency, but its error will diverge over time. Satellite positioning system (GNSS) has high speed and position accuracy over a long period of time, but the data update frequency is low and easily interfered with, especially in places such as between high-rise buildings, in tunnels, and underground parking lots where signals may be lost. In order to complement each other, the MEMS inertial navigation system and the satellite positioning system are combined into a navigation system to perform data fusion, and the information of the satellite positioning system is used to correct the errors in the MEMS inertial navigation system.

[0003] The MEMS integrated navigation system may have an installation error angle in applications such as vehicles, which will affect the calculation accuracy of the inertial navigation system; the accelerometer error of the MEMS inertial navigation system will directly affect the speed and position accuracy of its calculation.

[0004] Therefore, it is necessary to find a calibration method that comprehensively utilizes the information of GNSS and MINS during the movement of the carrier to estimate the installation error angle and the accelerometer error of the MEMS inertial navigation system and eliminate these two errors. Summary of the invention

[0005] The present invention uses the speed and position information of GNSS as an aid, combined with the output of the MEMS inertial navigation system, to provide an automatic calibration method to estimate the installation error angle and the accelerometer error of the MEMS inertial navigation system, and eliminate these two errors.

[0006] The present invention uses the speed and position information of GNSS as an aid, combines the speed, position information and attitude angle information of the MEMS inertial navigation system, uses an automatic calibration method, estimates the installation error angle and accelerometer error and eliminates them, reduces the angle error of the MEMS inertial navigation system, and improves the speed accuracy and position accuracy of the MEMS inertial navigation system. The automatic calibration system and method of the present invention have no strict restrictions on the conditions during the movement of the carrier, have low computational complexity, and are easy to implement. BRIEF DESCRIPTION OF THE DRAWINGS

[0007] Figure 1 GNSS-assisted MINS automatic calibration process (GNSS-assisted MINS automatic calibration system and process) Implementation

[0008] The present invention utilizes the speed and position information when the GNSS signal quality is good as a reference, combines the attitude angle information of the MEMS inertial navigation system and the speed and position information during the monitoring time, performs data preprocessing of two stages of automatic calibration each time the conditions are met, and then calculates a set of calibration parameters. When the storage list of the calibration parameters is full, the weighted average method is used to calculate the installation error angle and the accelerometer error. Referring to Figure 1, a GNSS-assisted MINS automatic calibration system and method are shown. The system includes a GNSS and MINS data acquisition module (1), an automatic calibration first stage data preprocessing module (2), an automatic calibration second stage data preprocessing module (3), an installation error angle and accelerometer error calculation module (4), and an installation error angle and accelerometer error weighting module (5). Among them, the GNSS and MINS data acquisition module (1) is used to collect the data output by GNSS and MINS, the automatic calibration first stage data preprocessing module (2) is used to perform automatic calibration preprocessing on the first stage data, the automatic calibration second stage data preprocessing module (3) is used to perform automatic calibration preprocessing on the second stage data, the installation error angle and accelerometer error calculation module (4) is used to calculate the installation error angle and accelerometer error and store them in a storage list, the installation error angle and accelerometer error weighting module (5) is used to calculate the weighted average of the installation error angle and accelerometer error in the storage list, and return the weighted average calculated installation error angle and accelerometer error to the MEMS inertial navigation system for error elimination. The specific execution process is as follows:

[0009] 1. GNSS and MINS data collection

[0010] Assume that the data sampling period of GNSS is T0 and the data sampling period of MEMS inertial navigation system is T. Collect the eastward velocity V of GNSS at the current moment E , northward speed V N and east position D E , North position D N Collect the eastward velocity V output by the MEMS inertial navigation system at the current moment mE , northward speed V mN and east position D mE , North position D mN , get the direction cosine matrix C corresponding to the attitude angle of the MEMS inertial navigation system at the current moment nb . C nb It is a 3*3 matrix well known in the technical field.

[0011] 2. Data preprocessing in the first stage of automatic calibration

[0012] Set the speed judgment threshold V for automatic calibration th =5.0m / s, the monitoring time of automatic calibration is T c=N c T0(N c is a positive integer, and the monitoring time is greater than or equal to 10s). Nc is the number of samples within the monitoring time Tc.

[0013] When the GNSS positioning precision factor PDOP is less than 5.0, the GNSS signal quality is considered good. When the GNSS signal quality is good, the horizontal speed of the GNSS at the current moment is:

[0014]

[0015] When V>V th , the automatic calibration counter FC starts timing from zero and enters the first stage of automatic calibration processing.

[0016] When the automatic calibration counter FC is equal to zero, the initial speed V of the GNSS is recorded and saved. E1 、V N1 and starting position D E1 , D N1 , record and save the starting speed V of the MEMS inertial navigation system mE1 、V mN1 and starting position D mE1 , D mN1 .

[0017] Each time GNSS data is sampled, the automatic calibration counter FC increases by 1. When FC equals N c When the GNSS end speed V is recorded and saved E2 、V N2 and end position D E2 , D N2 , record and save the end speed V of the MEMS inertial navigation system mE2 、V mN2 and end position D mE2 , D mN2 .

[0018] Calculate and save the east and north acceleration of the navigation coordinate system of the GNSS and MEMS inertial navigation system in the first stage of automatic calibration:

[0019]

[0020]

[0021]

[0022]

[0023] The first stage of data preprocessing for automatic calibration is completed.

[0024] 3. Automatic calibration second stage data preprocessing

[0025] After the first phase of data preprocessing of automatic calibration is completed, when the GNSS positioning precision factor PDOP is less than 5.0, the GNSS signal quality is considered good, and the horizontal speed at the current moment is:

[0026]

[0027] When V>V th , the automatic calibration counter FC starts timing from zero and enters the second stage of automatic calibration processing.

[0028] When the automatic calibration counter FC is equal to zero, the initial speed V of the GNSS is recorded and saved. E3 、V N3 and starting position D E3 , D N3 , record and save the starting speed V of the MEMS inertial navigation system mE3 、V mN3 and starting position D mE3 , D mN3 .

[0029] Each time GNSS data is sampled, the automatic calibration counter FC increases by 1. When FC equals N c When the GNSS end speed V is recorded and saved E4 、V N4 and end position D E4 , D N4 , record and save the end speed V of the MEMS inertial navigation system mE4 、V mN4 and end position D mE4 , D mN4 .

[0030] Calculate and save the east and north acceleration of the navigation coordinate system of the second stage of automatic calibration of GNSS and MEMS inertial navigation system:

[0031]

[0032]

[0033]

[0034]

[0035] The second stage of automatic calibration data preprocessing is completed.

[0036] 4. Calculate the installation error angle and accelerometer error and store them in the storage list

[0037] According to the acceleration obtained by the data preprocessing of the first stage of automatic calibration and the data preprocessing of the second stage of automatic calibration, the installation error angle of this calibration and the accelerometer error of the MEMS inertial navigation system can be calculated.

[0038] Acceleration vector:

[0039] Y a =[f E1 f N1 f E2 f N2 ] T

[0040] Factor matrix:

[0041]

[0042] Calculate the vector

[0043] X a =(φ T φ) -1 φ T Y a =[X a (1) X a (2) X a (3) X a (4)] T , T represents the transpose of the matrix, and according to the current Ya and φ, [X a (1) X a (2) X a (3) X a (4)] T .

[0044] Therefore, the installation error angle obtained by this automatic calibration is:

[0045]

[0046] This automatic calibration obtains the east and north acceleration errors in the navigation coordinate system:

[0047] f E0 =X a (1)

[0048] f N0 =X a (2)

[0049] The direction cosine matrix C corresponding to the attitude angle of the known MEMS inertial navigation system nb , the accelerometer errors of the MEMS inertial navigation system X-axis and Y-axis are calculated:

[0050] f bx0 =Cnb (1,1)·f E0 +C nb (1, 2)·f N0

[0051] f by0 =C nb (2, 1)·f E0 +C nb (2, 2)·f N0

[0052] Where C nb (i, j) (i = 1, 2; j = 1, 2) represents the direction cosine matrix C nb The value of the element in the i-th row and j-th column.

[0053] The installation error angle ψ0 and the accelerometer error f obtained by this automatic calibration are bx0 、f by0 Save to storage list.

[0054] 5. Calculate the weighted average of the installation error angle and accelerometer error in the stored list

[0055] Repeat steps 1 to 4 of the above specific process to calculate a total of ten sets of installation error angle and accelerometer error data and store them in the storage list. Suppose the installation error angle storage list ψ0[i] (i = 1, 2, ..., N), the X-axis accelerometer error storage list f bx0 [i] (i=1, 2, ..., N), Y-axis accelerometer error storage list f by0 [i] (i=1, 2, ..., N), the positive integer N=10 means there are 10 points in the storage list.

[0056] When calculating the weighted average, variables that are farther away from the current moment use smaller weights, and variables that are closer to the current moment use larger weights.

[0057] Calculate the weighted average installation error angle:

[0058]

[0059] Calculate the weighted average MEMS inertial navigation system X-axis and Y-axis accelerometer errors:

[0060]

[0061]

[0062] The weighted average of the calculated installation error angle ψc0 and the accelerometer error f x0 、f N0Return to the MEMS inertial navigation system for error elimination: the installation angle error is provided to the MEMS inertial navigation system for heading angle elimination, and the accelerometer error is provided to the MEMS inertial navigation system for acceleration elimination.

[0063] The embodiment of the present invention further provides a computer-readable storage medium, on which a computer program is stored, and when the computer program is executed by a processor, each process of the above-mentioned signal control method embodiment is implemented, and the same technical effect can be achieved. To avoid repetition, it is not repeated here. The computer-readable storage medium is, for example, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk.

[0064] It should be noted that, in this article, the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, an element defined by the sentence "comprises a ..." does not exclude the existence of other identical elements in the process, method, article or device including the element.

[0065] Through the description of the above implementation methods, those skilled in the art can clearly understand that the above-mentioned embodiment methods can be implemented by means of software plus a necessary general hardware platform, and of course can also be implemented by hardware, but in many cases the former is a better implementation method. Based on such an understanding, the technical solution of the present invention is essentially or the part that contributes to the prior art can be embodied in the form of a software product, which is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disk), including a number of instructions for a terminal to execute the methods described in each embodiment of the present invention.

Claims

1. A GNSS-assisted MINS automatic calibration system, the system comprising a GNSS and MINS data acquisition module (1), an automatic calibration first-stage data preprocessing module (2), an automatic calibration second-stage data preprocessing module (3), an installation error angle and accelerometer error calculation module (4), and an installation error angle and accelerometer error weighting module (5), wherein: The GNSS and MINS data acquisition module (1) is used to collect data output by the GNSS and MINS, the automatic calibration first stage data preprocessing module (2) is used to perform automatic calibration preprocessing on the first stage data, the automatic calibration second stage data preprocessing module (3) is used to perform automatic calibration preprocessing on the second stage data, the installation error angle and accelerometer error calculation module (4) is used to calculate the installation error angle and accelerometer error and store them in a storage list, the installation error angle and accelerometer error weighting module (5) is used to calculate the weighted average of the installation error angle and accelerometer error in the storage list, and return the weighted average calculated installation error angle and accelerometer error to the MEMS inertial navigation system for error elimination; in The GNSS and MINS data acquisition module (1) is used to collect the data output by the GNSS and MINS, specifically including: assuming that the data sampling period of the GNSS is T0, the data sampling period of the MEMS inertial navigation system is T, and collecting the eastward speed V of the GNSS at the current moment E , northward speed V N and east position D E , North position D N , collect the eastward velocity V output by the MEMS inertial navigation system at the current moment mE , northward speed V mN and east position D mE , North position D mN , get the direction cosine matrix C corresponding to the attitude angle of the MEMS inertial navigation system at the current moment nb The first stage data preprocessing module (2) of the automatic calibration is used to preprocess the first stage data of the automatic calibration, specifically including: setting the speed judgment threshold V of the automatic calibration th =5.0m / s, the monitoring time of automatic calibration is T c =N c T0, Nc is the number of samples within the monitoring time Tc; when the positioning precision factor of GNSS PDOP <5.0, the GNSS signal quality is considered to be good. When the GNSS signal quality is good, the horizontal speed of GNSS at the current moment is: When V>V th When the automatic calibration counter FC starts counting from zero, the first stage of the automatic calibration process begins. When the automatic calibration counter FC is equal to zero, the initial GNSS velocity V is recorded and saved. E1 、V N1 and starting position D E1 , D N1 , record and save the starting speed V of the MEMS inertial navigation system mE1 、V mN1 and starting position D mE1 , D mN1 ; Each time GNSS data is sampled, the automatic calibration counter FC increases by 1. When FC equals N c When the GNSS end speed V is recorded and saved E2 、V N2 and end position D E2 , D N2 , record and save the end speed V of the MEMS inertial navigation system mE2 、V mN2 and end position D mE2 , D mN2 ; Calculate and save the east and north acceleration of the navigation coordinate system of the GNSS and MEMS inertial navigation system in the first stage of automatic calibration: The first phase of automatic calibration data preprocessing is completed; the second phase of automatic calibration data preprocessing module (3) is used to perform automatic calibration preprocessing on the second phase data, specifically including: after the first phase of automatic calibration data preprocessing is completed, when the positioning precision factor PDOP of the GNSS is less than 5.0, it is considered that the GNSS signal quality is good, and the horizontal speed at the current moment is: When V>V th When the automatic calibration counter FC starts counting from zero, the second stage of the automatic calibration process begins. When the automatic calibration counter FC is equal to zero, the initial speed V of the GNSS is recorded and saved. E3 、V N3 and starting position D E3 , D N3 , record and save the starting speed V of the MEMS inertial navigation system mE3 、V mN3 and starting position D mE3 , D mN3 ; Each time GNSS data is sampled, the automatic calibration counter FC increases by 1. When FC equals N c When the GNSS end speed V is recorded and saved E4 、V N4 and end position D E4 , D N4 , record and save the end speed V of the MEMS inertial navigation system mE4 、V mN4 and end position D mE4 , D mN4 ; Calculate and save the east and north acceleration of the navigation coordinate system of the second stage of automatic calibration of GNSS and MEMS inertial navigation system: The second stage data preprocessing of the automatic calibration is completed; the installation error angle and accelerometer error calculation module (4) is used to calculate the installation error angle and the accelerometer error and store them in the storage list, specifically including: according to the acceleration obtained by the first stage data preprocessing of the automatic calibration and the second stage data preprocessing of the automatic calibration, the installation error angle of this calibration and the accelerometer error of the MEMS inertial navigation system can be calculated, and the acceleration vector Y a =[f E1 f N1 f E2 f N2 ] T , the factor matrix Calculate the vector X a =(φ T φ) -1 φ T Y a = [X a (1)X a (2)X a (3)X a (4)] T , T represents the transpose of the matrix, according to the current Y a and φ can be calculated to get [X a (1)X a (2)X a (3)X a (4)] T , so the installation error angle obtained by this automatic calibration is This automatic calibration obtains the east and north acceleration errors f in the navigation coordinate system. E0 =X a (1), f N0 =X a (2) The direction cosine matrix C corresponding to the attitude angle of the known MEMS inertial navigation system nb , calculate the accelerometer error of the MEMS inertial navigation system X-axis and Y-axis: f bx0 =C nb (1,1)·f E0 +C nb (1, 2)·f N0 , f by0 =C nb (2, 1)·f E0 +C nb (2, 2)·f N0 , where C nb (i,j), i = 1, 2, j = 1, 2, represents the direction cosine matrix C nb The value of the element in the i-th row and j-th column; the installation error angle ψ0 and the accelerometer error f obtained by this automatic calibration bx0 、f by0 The weighted module (5) for calculating the weighted average of the installation error angle and accelerometer error in the storage list, and returning the weighted average calculated installation error angle and accelerometer error to the MEMS inertial navigation system for error elimination, specifically comprising: calculating N groups of installation error angle and accelerometer error data, and storing them in the storage list; assuming that the installation error angle storage list ψ0[i], i = 1, 2, ..., N, the X-axis accelerometer error storage list f bx0 [i], i = 1, 2, ..., N, Y-axis accelerometer error storage list f by0 [i], i = 1, 2, ..., N, calculate the weighted average installation error angle: Calculate the weighted average MEMS inertial navigation system X-axis and Y-axis accelerometer errors: The weighted average calculated installation error angle ψ c0 and the accelerometer error f x0 、f y0 Return to the MEMS inertial navigation system for error elimination: the installation angle error is provided to the MEMS inertial navigation system for heading angle elimination, and the accelerometer error is provided to the MEMS inertial navigation system for acceleration elimination.

2. A method implemented in the GNSS-assisted MINS automatic calibration system as claimed in claim 1, comprising: (1) GNSS and MINS data collection: Assume that the GNSS data sampling period is T0, the MEMS inertial navigation system data sampling period is T, and collect the GNSS eastward velocity V at the current moment. E , northward speed V N and east position D E , North position D N , collect the eastward velocity V output by the MEMS inertial navigation system at the current moment mE , northward speed V mN and east position D mE , North position D mN , get the direction cosine matrix C corresponding to the attitude angle of the MEMS inertial navigation system at the current moment nb ; (2) Data preprocessing in the first stage of automatic calibration, specifically: setting the speed judgment threshold V of automatic calibration th =5.0m / s, the monitoring time of automatic calibration is T c =N c T0,N c is a positive integer, Nc is the number of samples within the monitoring time Tc; When the GNSS positioning precision factor PDOP < 5.0, the GNSS signal quality is considered good. When the GNSS signal quality is good, the horizontal speed of the GNSS at the current moment When V>V th When the automatic calibration counter FC starts counting from zero, the first stage of the automatic calibration process begins. When the automatic calibration counter FC is equal to zero, the initial GNSS velocity V is recorded and saved. E1 、V N1 and starting position D E1 , D N1 , record and save the starting speed V of the MEMS inertial navigation system mE1 、V mN1 and starting position D mE1 , D mN1 Each time GNSS data is sampled, the automatic calibration counter FC increases by 1. When FC equals N c When the GNSS end speed V is recorded and saved E2 、V N2 and end position D E2 , D N2 , record and save the end speed V of the MEMS inertial navigation system mE2 、V mN2 and end position D mE2 , D mN2 ; Calculate and save the east and north acceleration of the navigation coordinate system of the GNSS and MEMS inertial navigation system in the first stage of automatic calibration: The first phase of automatic calibration data preprocessing is completed; (3) the second phase of automatic calibration data preprocessing, specifically: after the first phase of automatic calibration data preprocessing is completed, when the GNSS positioning precision factor PDOP <5.0, the GNSS signal quality is considered to be good, and the horizontal speed at the current moment is: When V>V th When the automatic calibration counter FC starts counting from zero, the second stage of the automatic calibration process begins. When the automatic calibration counter FC is equal to zero, the initial GNSS velocity V is recorded and saved. E3 、V N3 and starting position D E3 , D N3 , record and save the starting speed V of the MEMS inertial navigation system mE3 、V mN3 and starting position D mE3 , D mN3 ; Each time GNSS data is sampled, the automatic calibration counter FC increases by 1. When FC equals N c When the GNSS end speed V is recorded and saved E4 、V N4 and end position D E4 , D N4 , record and save the end speed V of the MEMS inertial navigation system mE4 、V mN4 and end position D mE4 , D mN4 ; Calculate and save the east and north acceleration of the navigation coordinate system of the second stage of automatic calibration of GNSS and MEMS inertial navigation system: The second stage of automatic calibration data preprocessing is completed; (4) the installation error angle and accelerometer error are calculated and stored in the storage list, specifically: according to the acceleration obtained by the first stage of automatic calibration data preprocessing and the second stage of automatic calibration data preprocessing, the installation error angle and the accelerometer error of the MEMS inertial navigation system of this calibration can be calculated, and the acceleration vector Y a =[f E1 f N1 f E2 f N2 ] T , the factor matrix Calculate the vector X a =(φ T φ) -1 φ T Y a =[X a (1)X a (2)X a (3)X a (4)] T , T represents the transpose of the matrix, according to the current Y a and φ can be calculated to get [X a (1)X a (2)X a (3)X a (4)] T , so the installation error angle obtained by this automatic calibration is This automatic calibration obtains the east and north acceleration errors in the navigation coordinate system: f E0 =X a (1),f N0 =X a (2) The direction cosine matrix C corresponding to the attitude angle of the known MEMS inertial navigation system nb , calculate the accelerometer error of the MEMS inertial navigation system X-axis and Y-axis: f bx0 =C nb (1,1)·f E0 +C nb (1, 2)·f N0 , f by0 =C nb (2, 1)·f E0 +C nb (2, 2)·f N0 , where C nb (i, j), i = 1, 2, j = 1, 2 represents the direction cosine matrix C nb The value of the element in the i-th row and j-th column is the installation error angle ψ0 and the accelerometer error f obtained by this automatic calibration. bx0 、f by0 (5) Calculate the weighted average of the installation error angle and accelerometer error in the storage list, specifically: repeat steps 1 to 4 of the above specific process, calculate a total of N groups of installation error angle and accelerometer error data, and store them in the storage list, assuming that the installation error angle storage list ψ0[i], i = 1, 2, ..., N, the X-axis accelerometer error storage list f bx0 [i], i = 1, 2, ..., N, Y-axis accelerometer error storage list f by0 [i], i = 1, 2, ..., N; calculate the weighted average installation error angle Calculate the weighted average MEMS inertial navigation system X-axis and Y-axis accelerometer errors: The weighted average calculated installation error angle ψ c0 and the accelerometer error f x0 、f y0 Return to the MEMS inertial navigation system for error elimination: the installation angle error is provided to the MEMS inertial navigation system for heading angle elimination, and the accelerometer error is provided to the MEMS inertial navigation system for acceleration elimination.

3. A computer-readable storage medium storing a computer program, wherein the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the method according to claim 2 is implemented.

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