CN116878503A - Improved IMU-RTK loose combination navigation method and system based on GPS and IMU gesture transfer matching - Google Patents

Improved IMU-RTK loose combination navigation method and system based on GPS and IMU gesture transfer matching Download PDF

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Publication number
CN116878503A
CN116878503A CN202310956418.9A CN202310956418A CN116878503A CN 116878503 A CN116878503 A CN 116878503A CN 202310956418 A CN202310956418 A CN 202310956418A CN 116878503 A CN116878503 A CN 116878503A
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imu
navigation system
gps
inertial navigation
rtk
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王广才
曹世鹏
边有钢
徐彪
秦晓辉
胡满江
秦洪懋
秦兆博
谢国涛
王晓伟
丁荣军
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Hunan University
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Hunan University
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    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
    • G01C21/00—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00
    • G01C21/10—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 by using measurements of speed or acceleration
    • G01C21/12—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 by using measurements of speed or acceleration executed aboard the object being navigated; Dead reckoning
    • G01C21/16—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 by using measurements of speed or acceleration executed aboard the object being navigated; Dead reckoning by integrating acceleration or speed, i.e. inertial navigation
    • G01C21/165—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 by using measurements of speed or acceleration executed aboard the object being navigated; Dead reckoning by integrating acceleration or speed, i.e. inertial navigation combined with non-inertial navigation instruments
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S19/00—Satellite radio beacon positioning systems; Determining position, velocity or attitude using signals transmitted by such systems
    • G01S19/38—Determining a navigation solution using signals transmitted by a satellite radio beacon positioning system
    • G01S19/39—Determining a navigation solution using signals transmitted by a satellite radio beacon positioning system the satellite radio beacon positioning system transmitting time-stamped messages, e.g. GPS [Global Positioning System], GLONASS [Global Orbiting Navigation Satellite System] or GALILEO
    • G01S19/42—Determining position
    • G01S19/48—Determining position by combining or switching between position solutions derived from the satellite radio beacon positioning system and position solutions derived from a further system
    • G01S19/49—Determining position by combining or switching between position solutions derived from the satellite radio beacon positioning system and position solutions derived from a further system whereby the further system is an inertial position system, e.g. loosely-coupled

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  • Radar, Positioning & Navigation (AREA)
  • Remote Sensing (AREA)
  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • Automation & Control Theory (AREA)
  • Computer Networks & Wireless Communication (AREA)
  • Navigation (AREA)

Abstract

The application provides an improved IMU-RTK loose combined navigation method based on GPS and IMU gesture transfer matching, which is improved on the basis of traditional IMU-RTK loose combination, and by adding an installation error angle between an IMU coordinate system and a carrier coordinate system into a state vector for filtering estimation, an accurate IMU installation error angle estimation result is obtained on the basis of not obviously improving the traditional loose combination algorithm, and further the positioning precision of a combined navigation system is improved. Meanwhile, the accuracy of the estimation result is less influenced by the performance of the IMU, and the method can achieve more effective results than the prior art on the installation error angle estimation problem of the low-cost MEMS-IMU-RTK integrated navigation system. The application also provides an improved IMU-RTK loose combination navigation system based on GPS and IMU gesture transfer matching.

Description

Improved IMU-RTK loose combination navigation method and system based on GPS and IMU gesture transfer matching
Technical Field
The application belongs to the technical field of navigation, and particularly relates to an improved IMU-RTK loose combination navigation method and system based on GPS and IMU gesture transfer matching.
Background
The global satellite navigation system (GNSS) and the Inertial Navigation System (INS) have good complementary characteristics, so that the integrated combined navigation system of the GNSS and the inertial navigation system fully plays the advantages of the two subsystems and can continuously provide high-precision navigation information including position, speed and gesture in an open environment. The carrier-phase differential (RTK) technology achieves a more accurate positioning effect by utilizing a double-difference technology on the basis of GNSS, and the RTK/INS integrated navigation system also becomes a main solution for the high-precision terrestrial navigation positioning requirement. With the development of micro-electro-mechanical systems (MEMS) technology, inertial Measurement Units (IMUs) have been able to provide location services for land vehicle navigation systems at lower cost and size, and thus have found wide application in civilian vehicle navigation. The working principle of the inertial system requires that the coordinate system is aligned with the carrier coordinate system as much as possible, however, in practical application, the alignment of the coordinate axes of the two is difficult to ensure, which affects the accuracy of the inertial system. Therefore, the correction of the deviation of the coordinate axes of the IMU and the carrier is a key for ensuring the precision of the IMU-RTK integrated navigation system.
In the related art, there are two main solutions to the problem of deviation between the IMU and the carrier coordinate axis. One solution assumes that the vehicle is traveling horizontally at low speeds on land, simplifying the proportional equation and deriving the IMU installation offset angle represented by the IMU raw measurement data by way of a directional cosine array transformation. However, this solution has limited scope of use, and ignores drift of gyroscopes and accelerometers, which has some effect on the resolution accuracy, which is further exaggerated for MEMS-IMUs, subject to the constraints of assumptions. The second solution adopts two-stage kalman filtering, and solves the problem of accurate estimation of the mounting angle of the inertial device by assisting a Dead Reckoning (DR) method. In the method, dead reckoning is performed by using GNSS/INS integral gestures and travel distances, and an estimated result is fused with the GNSS/INS integral positions through a Kalman filter, so that an INS installation error is solved. However, due to the adoption of two-step Kalman filtering, the structure of the filtering algorithm of the integrated navigation system is complicated, and meanwhile, if an MEMS-IMU system is adopted to replace an INS system, the accuracy of a second-step filtering result can be influenced by errors caused by a low-cost IMU in the dead reckoning process.
Therefore, there is a need in the art to provide an improved IMU-RTK loose combined navigation method and system based on GPS and IMU pose transfer matching to solve the above-mentioned problems in the background art.
Disclosure of Invention
The application provides an improved IMU-RTK loose combined navigation method and system based on GPS and IMU gesture transfer matching, which are used for carrying out filtering estimation after the state of an IMU triaxial installation error angle is widened on the basis of a traditional IMU-RTK loose combined filtering algorithm, and improving the estimation precision of the installation error angle between the IMU and a carrier on the basis of not obviously increasing the complexity of the traditional algorithm, thereby improving the gesture measurement precision and the positioning precision of a combined navigation system.
In order to solve the technical problems, the technical scheme of the application is as follows:
the application provides an improved IMU-RTK loose combination navigation method based on GPS and IMU gesture transfer matching, which comprises the following steps:
s1: respectively calculating the position, speed and attitude information of the vehicle carrier by a satellite navigation system and an inertial navigation system;
s2: improving on the basis of an IMU-RTK loose combination basic model, and adding an installation error angle between an inertial navigation system coordinate system and a vehicle carrier coordinate system into a state vector to form an 18-dimensional Kalman filtering state vector;
s3: aiming at the estimation of the gesture, a gesture matching measurement matrix is constructed by considering an installation error angle and a solution error angle, so that gesture transmission matching between a GPS and an IMU is realized, a gesture observation equation is reconstructed by using the gesture matching measurement matrix to form a complete observed quantity, and an H array in an IMU-RTK loose combination basic model is rewritten;
s4: and estimating an installation error angle between the coordinate system of the inertial navigation system and the coordinate system of the vehicle carrier through a Kalman filter, feeding back the estimated installation error angle to the inertial navigation system, and compensating by the inertial navigation system to obtain a final navigation result.
Preferably, the resolving process of the inertial navigation system in step S1 includes the following steps:
s111: according to the data collected by the inertial navigation system, the position, the speed and the Euler angle of the vehicle carrier are calculated, and the calculation process is expressed as follows:
P IMU ＝[L IMU λ IMU h IMU ] T ；
V IMU ＝[V Ie V In V Iu ] T ；
Euler IMU ＝[ψ IMU θ IMU γ IMU ] T ；
wherein P is IMU 、V IMU 、Euler IMU Respectively representing the position, the speed and the Euler angle of the vehicle carrier calculated by the inertial navigation system; l (L) IMU 、λ IMU And h IMU Respectively representing the latitude, longitude and altitude calculated by the inertial navigation system; v (V) Ie 、V In And v Iu Respectively representing the east speed, the north speed and the sky speed calculated by the inertial navigation system; psi phi type IMU 、θ IMU 、γ IMU Respectively representing a course angle, a pitch angle and a roll angle which are calculated by an inertial navigation system; t represents matrix transposition;
s112: from EuropeCalculating the conversion relation of the pull angle and the attitude matrix to obtain a calculated attitude matrix of the inertial navigation system
Preferably, in the step S1, the resolving process of the satellite navigation system includes the following steps:
s121: position, speed and heading angle psi of vehicle carrier are calculated according to data acquired by satellite navigation system GPS The process of position and speed calculation is expressed as follows:
P GPS ＝[L GPS λ GPS h GPS ] T ；
V GPS ＝[V Ge V Gn V Gu ] T ；
wherein L is GPS 、λ GPS And h GPS Respectively representing the latitude, longitude and altitude calculated by the satellite navigation system; v (V) Ge 、V Gn And V Gu Respectively representing the east speed, the north speed and the sky speed calculated by the satellite navigation system;
s122: pitch angle theta calculated by the inertial navigation system IMU Roll angle gamma IMU The calculated pitch angle and roll angle of the satellite navigation system are directly used as the calculated Euler angle of the satellite navigation system, and the calculated Euler angle is expressed as:
Euler GPS ＝[ψ GPS θ IMU γ IMU ] T ；
s123: calculating to obtain a satellite navigation system calculated attitude array according to the conversion relation between Euler angles and the attitude array
Preferably, in the step S2, the 18-dimensional kalman filter state vector is expressed as:
in the method, in the process of the application,representing an original state vector of the IMU-RTK loose combination basic model; delta phi T Representing an installation error angle between an inertial navigation system coordinate system and a vehicle carrier coordinate system; δV (delta V) E 、δV n 、δV U Respectively representing the east direction, the north direction and the sky direction speed errors of the inertial navigation system; phi (phi) x 、φ y 、φ z Respectively representing three-axis attitude errors of an inertial navigation system; δl, δλ, δh represent the inertial navigation system latitude, longitude, and altitude errors, respectively; />Respectively representing the constant drift of the triaxial gyro of the inertial navigation system; epsilon x 、ε y 、ε z Respectively representing zero offset of the triaxial accelerometer of the inertial navigation system; delta phi x 、δφ y 、δφ z Representing the mounting error angle of the inertial navigation system triaxial and the vehicle carrier, respectively.
Preferably, in the step S3, the construction process of the posture matching measurement matrix is expressed as follows:
wherein Z is A Representing the pose matching measurement matrix,and->Respectively representing a satellite navigation system output gesture matrix and an inertial navigation system output gesture matrix containing a solution error; />The method comprises the steps of representing a conversion matrix from a satellite navigation system installation coordinate system to an inertial navigation system installation coordinate system; />Representation->Is a transposed matrix of (a);
wherein:
in the method, in the process of the application,representing a satellite navigation system attitude solution error angle; />Representing an inertial navigation system attitude solution error angle;
in the method, in the process of the application,the conversion matrix from the navigation coordinate system n system to the satellite navigation system installation coordinate system is represented; />Representing a posture conversion matrix caused by a satellite navigation system installation error angle; i represents an identity matrix; phi bG Representing an installation error angle of the satellite navigation system; x represents antisymmetryAn array; />Representation->Is a transposed matrix of (a); />Representing a posture transformation matrix caused by an inertial navigation system installation error angle; />Representing a transformation matrix of an inertial system installation coordinate system to a navigation coordinate system n-system.
Preferably, in the step S3, the construction process of the gesture includes the following steps:
s31: taking into account thatΦ bG Delta phi is small angle, and the second order or more is abandoned to obtain an attitude matching measurement matrix Z A Is the approximation equation of (a):
s32: approximation equation Z A ' is an antisymmetric array, and the antisymmetry is removed to obtain an attitude matching measurement value Z Φ Expressed as:
s33: for Z Φ The expression is transformed to obtain:
s34: defining equivalent observation noise in attitude observation as:
s35: gesture matrix output by inertial navigation systemApproximately replace->Obtaining an attitude observation equation:
preferably, the complete observance is expressed as:
preferably, the H array rewritten in the step S3 is expressed as:
the application also provides an improved IMU-RTK loose combination navigation system based on GPS and IMU gesture transfer matching, which comprises:
positioning system: the positioning system comprises a satellite navigation system and an inertial navigation system, wherein the satellite navigation system and the inertial navigation system are used for resolving the position, speed and gesture information of the vehicle carrier;
improved IMU-RTK loose combined model: improving on the basis of an IMU-RTK loose combination basic model, and adding an installation error angle between an inertial navigation system coordinate system and a vehicle carrier coordinate system into a state vector to form an 18-dimensional Kalman filtering state vector; aiming at the estimation of the gesture, a gesture matching measurement matrix is constructed by considering an installation error angle and a solution error angle, so that gesture transmission matching between a GPS and an IMU is realized, a gesture observation equation is reconstructed by using the gesture matching measurement matrix to form a complete observed quantity, and an H array in an IMU-RTK loose combination basic model is rewritten;
kalman filter: the method is used for estimating the installation error angle between the inertial navigation system coordinate system and the vehicle carrier coordinate system, feeding back the estimated installation error angle to the inertial navigation system, and compensating by the inertial navigation system to obtain a final navigation result.
The application has the beneficial effects that:
the application improves on the basis of the traditional IMU-RTK loose combination, and aims at estimating the gesture, considers the installation error angle and the solution error angle to construct a gesture matching measurement matrix, realizes gesture transmission matching between the GPS and the IMU, obtains an accurate IMU installation error angle estimation result on the basis of not obviously improving the traditional loose combination algorithm, and further improves the positioning accuracy of the combination to the system. Meanwhile, the accuracy of the estimation result is less influenced by the performance of the IMU, and the method can achieve more effective results than the prior art on the installation error angle estimation problem of the low-cost MEMS-IMU-RTK integrated navigation system.
Drawings
FIG. 1 illustrates a flow chart of an improved IMU-RTK loose combined navigation method based on GPS and IMU gesture transfer matching provided by the present application.
Detailed Description
The following description of the embodiments of the present application will be made clearly and fully with reference to the accompanying drawings, in which it is evident that the embodiments described are some, but not all embodiments of the application. All other embodiments, which can be made by those skilled in the art based on the embodiments of the application without making any inventive effort, are intended to be within the scope of the application.
Referring to fig. 1 in combination, the present application provides an improved IMU-RTK loose combined navigation method based on GPS and IMU gesture transfer matching, comprising the steps of:
s1: respectively calculating the position, speed and attitude information of the vehicle carrier by a satellite navigation system and an inertial navigation system;
s2: improving on the basis of an IMU-RTK loose combination basic model, and adding an installation error angle between an inertial navigation system coordinate system and a vehicle carrier coordinate system into a state vector to form an 18-dimensional Kalman filtering state vector;
s3: aiming at the estimation of the gesture, a gesture matching measurement matrix is constructed by considering an installation error angle and a solution error angle, so that gesture transmission matching between a GPS and an IMU is realized, a gesture observation equation is reconstructed by using the gesture matching measurement matrix to form a complete observed quantity, and an H array in an IMU-RTK loose combination basic model is rewritten;
s4: and estimating an installation error angle between the coordinate system of the inertial navigation system and the coordinate system of the vehicle carrier through a Kalman filter, feeding back the estimated installation error angle to the inertial navigation system, and compensating by the inertial navigation system to obtain a final navigation result.
The resolving process of the inertial navigation system in the step S1 includes the following steps:
s111: according to the data collected by the inertial navigation system, the position, the speed and the Euler angle of the vehicle carrier are calculated, and the calculation process is expressed as follows:
P IMU ＝[L IMU λ IMU h IMU ] T ；
V IMU ＝[V Ie V In V Iu ] T ；
Euler IMU ＝[ψ IMU θ IMU γ IMU ] T ；
wherein P is IMU 、V IMU 、Euler IMU Respectively representing the position, the speed and the Euler angle of the vehicle carrier calculated by the inertial navigation system; l (L) IMU 、λ IMU And h IMU Respectively representing the latitude, longitude and altitude calculated by the inertial navigation system; v (V) Ie 、V In And V Iu Respectively representing the east speed, the north speed and the sky speed calculated by the inertial navigation system; psi phi type IMU 、θ IMU 、γ IMU Respectively representing a course angle, a pitch angle and a roll angle which are calculated by an inertial navigation system; t represents matrix transposition;
s112: calculating to obtain a calculated attitude array of the inertial navigation system by using the conversion relation between Euler angles and the attitude array
In the step S1, the resolving process of the satellite navigation system includes the following steps:
s121: position, speed and heading angle psi of vehicle carrier are calculated according to data acquired by satellite navigation system GPS The process of position and speed calculation is expressed as follows:
P GPS ＝[L GPS λ GPS h GPS ] T ；
V GPS ＝[V Ge V Gn V Gu ] T ；
wherein L is GPS 、λ GPS And h GPS Respectively representing the latitude, longitude and altitude calculated by the satellite navigation system; v (V) Ge 、V Gn And V Gu Respectively representing the east speed, the north speed and the sky speed calculated by the satellite navigation system;
s122: pitch angle theta calculated by the inertial navigation system IMU Roll angle gamma IMU The calculated pitch angle and roll angle of the satellite navigation system are directly used as the calculated Euler angle of the satellite navigation system, and the calculated Euler angle is expressed as:
Euler GPS ＝[ψ GPS θ IMU γ IMU ] T ；
s123: calculating to obtain a satellite navigation system calculated attitude array according to the conversion relation between Euler angles and the attitude array
The resolving process of the satellite navigation system is executed by an RTK module, the RTK module includes two GNSS antennas, a satellite board card and a wireless data transmission device, and the resolving process of the RTK module adopts a conventional technology in the art, which is not described in detail in this embodiment.
In the process of resolving the satellite navigation system, although the two GNSS antennas can effectively acquire the course angle, pitch angle or roll angle of the vehicle carrier, three attitude angles cannot be acquired at the same time, and the course angle is the main factor for determining the attitude of the vehicle due to the fact that the pitch angle and roll angle of the land vehicle are less in change in the running process, so that the satellite system directly resolves the course angle, and the inertial navigation system resolves the pitch angle theta IMU Roll angle gamma IMU And directly serving as a pitch angle and a roll angle calculated by the satellite navigation system to obtain an Euler angle calculated by the satellite navigation system.
In the step S2, the 18-dimensional kalman filter state vector is expressed as:
in the method, in the process of the application,representing an original state vector of the IMU-RTK loose combination basic model; delta phi T Representing an installation error angle between an inertial navigation system coordinate system and a vehicle carrier coordinate system; δV (delta V) E 、δV n 、δV U Respectively representing the east direction, the north direction and the sky direction speed errors of the inertial navigation system; phi (phi) x 、φ y 、φ z Respectively representing three-axis attitude errors of an inertial navigation system; δl, δλ, δh represent the inertial navigation system latitude, longitude, and altitude errors, respectively; />Respectively representing the constant drift of the triaxial gyro of the inertial navigation system; epsilon x 、ε y 、ε z Respectively representing zero offset of the triaxial accelerometer of the inertial navigation system; delta phi x 、δφ y 、δφ z Representing the mounting error angle of the inertial navigation system triaxial and the vehicle carrier, respectively.
In the step S3, the construction process of the posture matching measurement matrix is expressed as follows:
wherein Z is A Representing the pose matching measurement matrix,and->Respectively representing a satellite navigation system output gesture matrix and an inertial navigation system output gesture matrix containing a solution error; />The method comprises the steps of representing a conversion matrix from a satellite navigation system installation coordinate system to an inertial navigation system installation coordinate system; />Representation->Is a transposed matrix of (a);
wherein:
in the method, in the process of the application,representing a satellite navigation system attitude solution error angle; />Representing inertial navigation systemCalculating an error angle by the system posture;
in the method, in the process of the application,the conversion matrix from the navigation coordinate system n system to the satellite navigation system installation coordinate system is represented; />Representing a posture conversion matrix caused by a satellite navigation system installation error angle; i represents an identity matrix; phi bG Representing an installation error angle of the satellite navigation system; x represents an antisymmetric array; />Representation->Is a transposed matrix of (a); />Representing a posture transformation matrix caused by an inertial navigation system installation error angle; />Representing a transformation matrix of an inertial system installation coordinate system to a navigation coordinate system n-system.
In the step S3, the construction process of the gesture includes the following steps:
s31: taking into account thatΦ bG Delta phi is small, and the second order and the small amount above the second order are abandonedObtaining an attitude matching measurement matrix Z A Is the approximation equation of (a):
s32: approximation equation Z A ' is an antisymmetric array, and the antisymmetry is removed to obtain an attitude matching measurement value Z Φ Expressed as:
s33: for Z Φ The expression is transformed to obtain:
s34: defining equivalent observation noise in attitude observation as:
s35: gesture matrix output by inertial navigation systemApproximately replace->Obtaining an attitude observation equation:
the complete observance is expressed as:
the H array after overwriting is expressed as:
the application also provides an improved IMU-RTK loose combination navigation system based on GPS and IMU gesture transfer matching, which comprises:
positioning system: the positioning system comprises a satellite navigation system and an inertial navigation system, wherein the satellite navigation system and the inertial navigation system are used for resolving the position, speed and gesture information of the vehicle carrier;
improved IMU-RTK loose combined model: improving on the basis of an IMU-RTK loose combination basic model, and adding an installation error angle between an inertial navigation system coordinate system and a vehicle carrier coordinate system into a state vector to form an 18-dimensional Kalman filtering state vector; aiming at the estimation of the gesture, a gesture matching measurement matrix is constructed by considering an installation error angle and a solution error angle, so that gesture transmission matching between a GPS and an IMU is realized, a gesture observation equation is reconstructed by using the gesture matching measurement matrix to form a complete observed quantity, and an H array in an IMU-RTK loose combination basic model is rewritten;
kalman filter: the method is used for estimating the installation error angle between the inertial navigation system coordinate system and the vehicle carrier coordinate system, feeding back the estimated installation error angle to the inertial navigation system, and compensating by the inertial navigation system to obtain a final navigation result.
The embodiments of the present application have been described above with reference to the accompanying drawings, but the present application is not limited to the above-described embodiments, which are merely illustrative and not restrictive, and many forms may be made by those having ordinary skill in the art without departing from the spirit of the present application and the scope of the claims, which are to be protected by the present application.

Claims (9)

1. An improved IMU-RTK loose combination navigation method based on GPS and IMU gesture transfer matching is characterized by comprising the following steps:
s1: respectively calculating the position, speed and attitude information of the vehicle carrier by a satellite navigation system and an inertial navigation system;
s2: improving on the basis of an IMU-RTK loose combination basic model, and adding an installation error angle between an inertial navigation system coordinate system and a vehicle carrier coordinate system into a state vector to form an 18-dimensional Kalman filtering state vector;
s3: aiming at the estimation of the gesture, a gesture matching measurement matrix is constructed by considering an installation error angle and a solution error angle, so that gesture transmission matching between a GPS and an IMU is realized, a gesture observation equation is reconstructed by using the gesture matching measurement matrix to form a complete observed quantity, and an H array in an IMU-RTK loose combination basic model is rewritten;
s4: and estimating an installation error angle between the coordinate system of the inertial navigation system and the coordinate system of the vehicle carrier through a Kalman filter, feeding back the estimated installation error angle to the inertial navigation system, and compensating by the inertial navigation system to obtain a final navigation result.
2. The improved IMU-RTK loose combined navigation method based on GPS and IMU pose transfer matching according to claim 1, wherein the inertial navigation system resolving process in step S1 comprises the steps of:
s111: according to the data collected by the inertial navigation system, the position, the speed and the Euler angle of the vehicle carrier are calculated, and the calculation process is expressed as follows:
P IMU ＝[L IMU λ IMU h IMU ] T ；
V IMU ＝[V Ie V In V Iu ] T ；
Euler IMU ＝[ψ IMU θ IMU γ IMU ] T ；
wherein P is IMU 、V IMU 、Euler IMU Respectively representing the position, the speed and the Euler angle of the vehicle carrier calculated by the inertial navigation system; l (L) IMU 、λ IMU And h IMU Respectively represent inertial navigationLatitude, longitude, and altitude resolved by the system; v (V) Ie 、V In And V Iu Respectively representing the east speed, the north speed and the sky speed calculated by the inertial navigation system; psi phi type IMU 、θ IMU 、γ IMU Respectively representing a course angle, a pitch angle and a roll angle which are calculated by an inertial navigation system; t represents matrix transposition;
s112: calculating to obtain a calculated attitude array of the inertial navigation system by using the conversion relation between Euler angles and the attitude array
3. The improved IMU-RTK loose combined navigation method based on GPS and IMU pose transfer matching according to claim 2, wherein in step S1, the solution process of the satellite navigation system comprises the steps of:
s121: position, speed and heading angle psi of vehicle carrier are calculated according to data acquired by satellite navigation system GPS The process of position and speed calculation is expressed as follows:
P GPS ＝[L GPS λ GPS h GPS ] T ；
V GPS ＝[V Ge V Gn V Gu ] T ；
wherein L is GPS 、λ GPS And h GPS Respectively representing the latitude, longitude and altitude calculated by the satellite navigation system; v (V) Ge 、V Gn And V Gu Respectively representing the east speed, the north speed and the sky speed calculated by the satellite navigation system;
s122: pitch angle theta calculated by the inertial navigation system IMU Roll angle gamma IMU The calculated pitch angle and roll angle of the satellite navigation system are directly used as the calculated Euler angle of the satellite navigation system, and the calculated Euler angle is expressed as: euler (Eulter) GPS ＝[ψ GPS θ IMU γ IMU ] T ；
S123: calculating the calculated gesture of the satellite navigation system according to the conversion relation between Euler angle and gesture arrayArray
4. The improved IMU-RTK loose combined navigation method based on GPS and IMU pose transfer matching according to claim 1, wherein in step S2, the 18-dimensional kalman filter state vector is expressed as:
in the method, in the process of the application,representing an original state vector of the IMU-RTK loose combination basic model; delta phi T Representing an installation error angle between an inertial navigation system coordinate system and a vehicle carrier coordinate system; δV (delta V) E 、δV N 、δV U Respectively representing the east direction, the north direction and the sky direction speed errors of the inertial navigation system; phi (phi) x 、φ y 、φ z Respectively representing three-axis attitude errors of an inertial navigation system; δl, δλ, δh represent the inertial navigation system latitude, longitude, and altitude errors, respectively; />Respectively representing the constant drift of the triaxial gyro of the inertial navigation system; epsilon x 、ε y 、ε z Respectively representing zero offset of the triaxial accelerometer of the inertial navigation system; delta phi x 、δφ y 、δφ z Representing the mounting error angle of the inertial navigation system triaxial and the vehicle carrier, respectively.
5. The improved IMU-RTK loose combined navigation method based on GPS and IMU pose transfer matching according to claim 4, wherein in step S3, the process of constructing the pose matching measurement matrix is expressed as:
wherein Z is A Representing the pose matching measurement matrix,and->Respectively representing a satellite navigation system output gesture matrix and an inertial navigation system output gesture matrix containing a solution error; />The method comprises the steps of representing a conversion matrix from a satellite navigation system installation coordinate system to an inertial navigation system installation coordinate system; />Representation->Is a transposed matrix of (a);
wherein:
in the method, in the process of the application,representing a satellite navigation system attitude solution error angle; />Representing an inertial navigation system attitude solution error angle;
in the method, in the process of the application,the conversion matrix from the navigation coordinate system n system to the satellite navigation system installation coordinate system is represented; />Representing a posture conversion matrix caused by a satellite navigation system installation error angle; i represents an identity matrix; phi bG Representing an installation error angle of the satellite navigation system; x represents an antisymmetric array; />Representation->Is a transposed matrix of (a); />Representing a posture transformation matrix caused by an inertial navigation system installation error angle; />Representing a transformation matrix of an inertial system installation coordinate system to a navigation coordinate system n-system.
6. The method for improved IMU-RTK loose combined navigation based on GPS and IMU pose transfer matching according to claim 5, wherein in step S3, the process of constructing the pose comprises the steps of:
s31: taking into account thatΦ bG Delta phi is small angle, and the second order or more is abandoned to obtain an attitude matching measurement matrix Z A Is the approximation equation of (a):
s32: approximation equation Z A ' is an antisymmetric array, and the antisymmetry is removed to obtain an attitude matching measurement value Z φ Expressed as:
s33: for Z φ The expression is transformed to obtain:
s34: defining equivalent observation noise in attitude observation as:
s35: gesture matrix output by inertial navigation systemApproximately replace->Obtaining an attitude observation equation:
7. the improved IMU-RTK loose combined navigation method based on GPS and IMU pose transfer matching of claim 6, wherein the complete observables are expressed as:
8. the improved IMU-RTK loose combined navigation method based on GPS and IMU pose transfer matching according to claim 7, wherein the H-array rewritten in step S3 is represented as:
9. an improved IMU-RTK loose integrated navigation system based on GPS and IMU pose transfer matching, comprising:
positioning system: the positioning system comprises a satellite navigation system and an inertial navigation system, wherein the satellite navigation system and the inertial navigation system are used for resolving the position, speed and gesture information of the vehicle carrier;
improved IMU-RTK loose combined model: improving on the basis of an IMU-RTK loose combination basic model, and adding an installation error angle between an inertial navigation system coordinate system and a vehicle carrier coordinate system into a state vector to form an 18-dimensional Kalman filtering state vector; aiming at the estimation of the gesture, a gesture matching measurement matrix is constructed by considering an installation error angle and a solution error angle, so that gesture transmission matching between a GPS and an IMU is realized, a gesture observation equation is reconstructed by using the gesture matching measurement matrix to form a complete observed quantity, and an H array in an IMU-RTK loose combination basic model is rewritten;
kalman filter: the method is used for estimating the installation error angle between the inertial navigation system coordinate system and the vehicle carrier coordinate system, feeding back the estimated installation error angle to the inertial navigation system, and compensating by the inertial navigation system to obtain a final navigation result.
CN202310956418.9A 2023-08-01 2023-08-01 Improved IMU-RTK loose combination navigation method and system based on GPS and IMU gesture transfer matching Pending CN116878503A (en)

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Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN118311630A (en) * 2024-06-07 2024-07-09 浙江省白马湖实验室有限公司 High-precision positioning method of unmanned loader based on RTK and IMU

Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN118311630A (en) * 2024-06-07 2024-07-09 浙江省白马湖实验室有限公司 High-precision positioning method of unmanned loader based on RTK and IMU

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