CN115507848A - Positioning method based on wheel speed inertial navigation combined pre-integration and RTK tight combination - Google Patents

Positioning method based on wheel speed inertial navigation combined pre-integration and RTK tight combination Download PDF

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CN115507848A
CN115507848A CN202211402919.4A CN202211402919A CN115507848A CN 115507848 A CN115507848 A CN 115507848A CN 202211402919 A CN202211402919 A CN 202211402919A CN 115507848 A CN115507848 A CN 115507848A
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integration
wheel speed
residual
coordinate system
inertial navigation
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高同跃
李利明
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Suzhou Huami Navigation Technology Co ltd
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Suzhou Huami Navigation Technology Co ltd
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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
    • 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
    • G01C21/005—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 with correlation of navigation data from several sources, e.g. map or contour matching
    • 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
    • G01S19/45—Determining position by combining measurements of signals from the satellite radio beacon positioning system with a supplementary measurement
    • G01S19/47—Determining position by combining measurements of signals from the satellite radio beacon positioning system with a supplementary measurement the supplementary measurement being an inertial measurement, e.g. tightly coupled inertial

Abstract

The invention discloses a positioning method based on wheel speed inertial navigation combined pre-integration and RTK tight combination, which comprises the following steps: receiving data of an inertial sensor and a wheel speed meter, performing combined pre-integration to generate a pre-integration residual error containing an integral error quantity of the sensor and the wheel speed meter, receiving satellite navigation data and constructing an observation residual error representing the satellite navigation error quantity; and step two, tightly combining the pre-integration residual error and the observation residual error to generate a correction factor, and correcting the satellite navigation data according to the correction factor to generate the motion state of the equipment. The invention can tightly combine the wheel speed meter and the pre-integration of the IMU to continuously compensate the error accumulated by the IMU, improve the performance of the pre-integration algorithm and realize long-acting high-precision positioning.

Description

Positioning method based on wheel speed inertial navigation combined pre-integration and RTK tight combination
Technical Field
The invention relates to the technical field of navigation, in particular to a positioning method based on wheel speed inertial navigation combined pre-integration and RTK tight combination.
Background
When the vehicle is automatically driven, it is necessary to obtain the states of the unmanned vehicle, such as position coordinates, speed, posture and the like, and the positioning accuracy of the unmanned vehicle has higher requirements for accurately controlling the automatic driving of the unmanned vehicle. Satellite navigation locates by measuring pseudoranges between satellites and a receiver, but satellite location is usually subject to various error factors, such as: receiver clock errors, satellite clock errors, multipath errors, channel errors, ephemeris errors, internal noise errors, etc., all affect the positioning accuracy of the satellite.
The conventional precision improvement is to better eliminate errors in satellite navigation and improve the positioning precision by combining an RTK technology. However, the positioning method of the RTK is based on the principle that positioning is performed by measuring distances between a plurality of satellites and a GNSS receiver, and an error occurring in positioning of a single satellite is offset, but when a shield exists between the receiver and the satellites, the distance measurement accuracy of the RTK is affected, so that the overall positioning accuracy is reduced. And the RTK positioning technique is based on the very similar errors between the rover station and the reference station, and it uses GNSS carrier phase observations for real-time dynamic positioning, and as the distance between the reference station and the rover station increases, the bit accuracy also becomes lower and lower.
In order to overcome the above problems, it is proposed to combine the satellite positioning technology and inertial navigation, so as to improve the precision of satellite positioning by combining satellite positioning and inertial positioning. However, the inertial navigation uses an Inertial Measurement Unit (IMU) to measure the angular velocity and acceleration of the inertial navigation unit, then uses an inertial navigation algorithm (INS) to realize short-distance accurate positioning, and combines a satellite positioning navigation technology and an inertial navigation technology (i.e., corrects satellite positioning errors) to improve positioning accuracy.
However, the INS algorithm diverges very quickly, and the longer the vehicle moves, the larger the inertial navigation error, resulting in a shorter confidence time for the INS. However, if a high-precision IMU is used, the IMU is expensive, the IMU with low cost has poor precision, and a drift phenomenon occurs when long-time navigation positioning is performed, so that error accumulation is larger and larger, the confidence time of the INS is shorter, and the efficiency of improving the positioning precision is lower.
Disclosure of Invention
In view of this, the present invention provides a positioning method based on a wheel speed inertial navigation combined pre-integration and RTK tight combination, which can tightly combine a wheel speed meter and the pre-integration of an IMU to continuously compensate for an error accumulated by the IMU, improve the performance of a pre-integration algorithm, and achieve long-term high-precision positioning.
In order to solve the technical problems, the invention adopts the technical scheme that:
a positioning method based on wheel speed inertial navigation combined pre-integration and RTK tight combination comprises the following steps that firstly, satellite navigation data are received, and observation residual errors representing satellite navigation error amounts are constructed;
step two, acquiring the mileage increment in each time interval through a wheel speed meter, and performing combined pre-integration by combining an inertial sensor to generate a pre-integration residual error containing the integral error of the sensor and the wheel speed meter;
and step three, tightly combining the pre-integration residual error and the observation residual error to generate a correction factor, and correcting the satellite positioning according to the correction factor.
Further, the joint pre-integration includes a speed increment β, a displacement increment α, an attitude variation q, and a mileage increment s, and propagation equations of β, α, q, and s are respectively constructed, where the propagation equation of the mileage increment s is:
Figure BDA0003934374710000021
wherein:
Figure BDA0003934374710000022
representing the displacement between the moment k-1 and the moment i under the inertial navigation coordinate system b,
Figure BDA0003934374710000023
represents the displacement between the k-1 time and the i-1 time under the inertial navigation coordinate system b, and the displacement is measured by the sensor
Figure BDA0003934374710000024
Representing the displacement between the moment i-1 and the moment i under the inertial navigation coordinate system b, so as to separately acquire the mileage increment in each period,
the propagation equation of the mileage increment is as follows:
Figure BDA0003934374710000025
Figure BDA0003934374710000026
wherein
Figure BDA0003934374710000027
And
Figure BDA0003934374710000028
are rotation matrixes, are used for rotating the equipment coordinate system v to be under the inertial navigation coordinate system b,
Figure BDA0003934374710000031
which represents the amount of displacement between time i-1 and time i in the device coordinate system v,
Figure BDA0003934374710000032
Figure BDA0003934374710000033
and (b) indicating a lever arm correction error quantity for correcting the position errors of the wheel speed meter and the inertial sensor under the inertial navigation coordinate system b.
Further, the observation residual includes double-difference pseudorange observation residual
Figure BDA0003934374710000034
Sum double difference phase observation residual
Figure BDA0003934374710000035
IMU/wheel speed meter combined pre-integration residual error under satellite coordinate system according to combined pre-integration construction
Figure BDA0003934374710000036
The correction factors are as follows:
Figure BDA0003934374710000037
further, the IMU/wheel speed meter is combined with pre-integration residual error
Figure BDA0003934374710000038
Figure BDA0003934374710000039
Wherein
Figure BDA00039343747100000310
Represents a covariance matrix of IMU/wheel speed meter combined pre-integration observation factors under a geodetic coordinate system,
Figure BDA00039343747100000311
and the residual matrix comprises a position change residual, a speed change residual, an attitude change residual, an accelerometer zero offset residual, a gyroscope zero offset residual and a wheel speed meter displacement residual.
Further, an initialization strategy is added before the first step, wherein the initialization strategy comprises an initial coordinate and an initial posture of the equipment;
the initial coordinates comprise positioning coordinate data of a plurality of groups of satellite navigation, the average value of the positioning coordinate data is obtained, acceleration counting data is obtained to calculate a gravity vector, and an included angle between the gravity vector and a Z axis and an OXY plane of an equipment coordinate system is obtained so as to respectively generate initial states comprising a roll angle and a pitch angle.
The invention has the advantages and positive effects that:
the mileage increment propagation formula obtained by adding the wheel speed meter in the combined pre-integration of the inertial navigation is adopted, and the mileage increment propagation formula can effectively counteract the superposition error generated by the superposition of inertial navigation data in each time interval by independently obtaining the mileage increment in each time interval so as to continuously compensate the error accumulated by the IMU, prolong the dispersion time of the INS algorithm, further improve the performance of the pre-integration algorithm and realize long-term effective high-precision positioning.
Drawings
The accompanying drawings, which are included to provide a further understanding of the invention and are incorporated in and constitute a part of this specification, illustrate embodiments of the invention and together with the description serve to explain the principles of the invention and not to limit the invention. In the drawings:
FIG. 1 is a block diagram of an overall flow of a positioning method based on wheel speed inertial navigation combined pre-integration and RTK tight combination according to the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
It will be understood that when an element is referred to as being "secured to" another element, it can be directly on the other element or intervening elements may also be present. When a component is referred to as being "connected" to another component, it can be directly connected to the other component or intervening components may also be present. When a component is referred to as being "disposed on" another component, it can be directly on the other component or intervening components may also be present. The terms "vertical," "horizontal," "left," "right," and the like as used herein are for illustrative purposes only.
Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs. The terminology used in the description of the invention herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention. As used herein, the term "and/or" includes any and all combinations of one or more of the associated listed items.
The invention provides a positioning method based on wheel speed inertial navigation combined pre-integration and RTK tight combination, as shown in figure 1, a satellite sensor (GNSS receiver) for satellite positioning is arranged on equipment, a double-difference observation equation (double-difference pseudo-range observation equation) is constructed, the double-difference observation equation is used for calculating the position coordinate of mobile equipment under a satellite coordinate system, and then the double-difference pseudo-range observation equation is constructed according to the double-difference pseudo-range observation equationResidual error
Figure BDA0003934374710000051
Double-differenced pseudorange observation residuals are used to indicate the amount of position error that would occur when positioning by pseudoranges (i.e., the error that occurs when positioning by satellites).
In order to improve the positioning precision of the satellite, the RTK technology is combined for positioning, a double-difference carrier phase observation equation is constructed, and a double-difference phase observation residual error is constructed according to the double-difference carrier phase observation equation
Figure BDA0003934374710000052
Similarly, the double difference phase observation residual is used to represent the amount of error generated during the positioning process.
During positioning, the GNSS receiver receives positioning data, the positioning data is substituted into the double-difference pseudo-range observation residual and the double-difference phase observation residual to calculate a positioning error (also called a first correction), the positioning data is substituted into the double-difference pseudo-range observation equation and the double-difference carrier phase observation equation to generate positioning coordinates, and the positioning coordinates are corrected through the error, so that the satellite positioning precision is improved.
When the apparatus moves to a position where there is a shield, the alignment degree of the first correction amount decreases, affecting the positioning accuracy. In order to further improve the positioning accuracy of the equipment, an inertial sensor (a gyroscope and an accelerometer) and a wheel speed meter are further mounted on the equipment, the gyroscope is used for acquiring the inclination condition of the equipment (so as to determine the posture of the equipment), the accelerometer is used for acquiring the acceleration whole amount of the movement of the equipment (so as to determine the movement distance of the equipment or the position vector of the equipment), and the wheel speed meter acquires the travel distance of the equipment. And an IMU/wheel speed meter combined pre-integration formula is constructed together:
Figure BDA0003934374710000053
Figure BDA0003934374710000054
Figure BDA0003934374710000055
Figure BDA0003934374710000056
Figure BDA0003934374710000057
among them are: a pre-integration equation representing β for velocity increments, α for displacement increments, q for attitude change amounts, and s for mileage increments, wherein:
Figure BDA0003934374710000058
representing the variation of the velocity (obtained from the parameters of the accelerometer) between time k-1 and time i in the inertial frame,
Figure BDA0003934374710000059
representing the amount of change in position (taken from the accelerometer parameters) between time k-1 and time i in the inertial frame,
Figure BDA00039343747100000510
representing the amount of change in attitude (taken from the parameters of the gyroscope) between time k-1 and time i in the inertial frame.
A displacement variation formula for calculating the path displacement is added in the combined pre-integration,
Figure BDA0003934374710000061
the displacement (obtained by the parameters of the wheel speed meter) of the path from the moment k-1 to the moment i shown in the inertial coordinate system can be independently calculated, and the displacement variation between the two moments can be independently calculated (instead of calculating the integral displacement, the error accumulation caused by data superposition is avoided). By increasing the displacement variation of the device recorded by the wheel speed meter within the joint pre-integration, the error increment in the inertial positioning can be counteracted, and the divergence of the inertial positioning is prolongedTime, the pre-integration precision can be effectively improved.
Figure BDA0003934374710000062
Is a propagation equation of
Figure BDA0003934374710000063
Wherein
Figure BDA0003934374710000064
Which represents the displacement between the time k-1 and the time i-1 under the inertial navigation coordinate system b,
Figure BDA0003934374710000065
the displacement between the moment i-1 and the moment i is represented under an inertial navigation coordinate system b, so that the displacement between each moment k-1 and the moment i-1 and the displacement between the moment i-1 and the moment i are independently obtained and superposed, and the displacement between the moment k-1 and the moment i-1 is calculated by independently obtaining the displacements between two adjacent periods (the independent displacements of the device from the moment k-1 to the moment i-1 and from the moment i-1 to the moment i) instead of independently obtaining the displacement of the device at the moment k-1 and the displacement of the device at the moment i, so that the superposition error of the wheel speed meter caused by the superposition of the paths is greatly reduced, and the precision of the combined pre-integration of the IMU/wheel speed meter is further improved (the superposition error of partial inertial navigation is counteracted).
Figure BDA0003934374710000066
Wherein
Figure BDA0003934374710000067
And
Figure BDA0003934374710000068
are rotation matrixes, are used for rotating the equipment coordinate system v to be under the inertial navigation coordinate system b,
Figure BDA0003934374710000069
is shown in the deviceUnder the coordinate system v, the displacement between the moment i-1 and the moment i,
Figure BDA00039343747100000610
Figure BDA00039343747100000611
and (b) indicating a lever arm correction error quantity for correcting the position errors of the wheel speed meter and the inertial sensor under the inertial navigation coordinate system b.
Constructing a combined pre-integration residual error of the IMU/wheel speed meter according to the combined pre-integration of the IMU/wheel speed meter and the formula
Figure BDA00039343747100000612
Wherein
Figure BDA00039343747100000613
Represents a covariance matrix representing the IMU/wheel speed meter combined pre-integration observation factor under the geodetic coordinate system,
Figure BDA0003934374710000071
and the residual matrix comprises a position change residual, a speed change residual, an attitude change residual, an accelerometer zero offset residual, a gyroscope zero offset residual and a wheel speed meter displacement residual.
The residual matrix is:
Figure BDA0003934374710000072
wherein
Figure BDA0003934374710000073
Representing an attitude rotation matrix between inertial navigation coordinate systems at the moments from N to k-1 of the northeast sky coordinate system;
Figure BDA0003934374710000074
the projection of the position vector of the inertial navigation coordinate system at the time k relative to the N system under the N system is represented;
Figure BDA0003934374710000075
the projection of the position vector of the inertial navigation coordinate system at the moment of k-1 relative to the N system under the N system is represented; Δ t k Is the time between time k-1 and time k; g N Representing the gravity vector under the N system;
Figure BDA0003934374710000076
is the position result of the pre-integration corrected by a first order approximation and the first column of equations calculates the position residual between time k-1 and time k.
In the same way, the first and second,
Figure BDA0003934374710000077
the projection of the inertial navigation coordinate system at the time k relative to the velocity vector of the N system under the N system is represented;
Figure BDA0003934374710000078
the projection of the inertial navigation coordinate system at the time of k-1 relative to the velocity vector of the N system under the N system is represented;
Figure BDA0003934374710000079
is the velocity result of the pre-integration corrected by a first order approximation and the second column of equations calculates the velocity residual between time k-1 and time k.
Figure BDA00039343747100000710
Representing the attitude of the inertial navigation coordinate system at the moment k relative to the N system;
Figure BDA00039343747100000711
representing the attitude of the inertial navigation coordinate system at the moment of k-1 relative to an N system;
Figure BDA00039343747100000712
the pose result of the pre-integration corrected with a first order approximation, and the third column of equations calculates the pose residual between time k-1 and time k.
b a (t k ) Representing the accelerometer zero offset at time k; b a (t k-1 ) When represents k-1The accelerometer at moment zero offset, and the fourth column of formula calculates the accelerometer zero offset residual between the moment k-1 and the moment k. b g (t k ) Zero offset of the gyroscope representing time k, b g (t k-1 ) The gyroscope zero offset at the moment k-1 is represented, and the fifth column of formula calculates the gyroscope zero offset residual between the moment k-1 and the moment k.
Figure BDA0003934374710000081
Is the result of pre-integration mileage corrected by first-order approximation, and the sixth column formula calculates the mileage residual error of the wheel speed meter between the time k-1 and the time k, s odo (t k ) Representing wheel speed meter displacement at time k, s odo (t k-1 ) Representing the wheel speed meter displacement at the time k-1, and the seventh column of equations calculates the wheel speed meter displacement residual between the time k-1 and the time k.
The total correction factor is generated by superposing the double-difference pseudo-range observation residual error, the double-difference phase observation residual error and the IMU/wheel speed meter combined pre-integral residual error, and the correction factor is used for further correcting the satellite positioning coordinate, so that the positioning precision of the satellite can be ensured even if the satellite is driven for a long time or moves to a position with more shelters.
In order to further improve the positioning precision of the equipment, the system can be initialized before the first combined navigation; firstly, an unmanned vehicle is statically placed in an open space, 100 groups of data from RTK are collected to obtain 100 coordinates by using a least square method, and the position is initialized by taking an average value (the initial position of equipment is accurately determined); the initial attitude of the unmanned vehicle is obtained from data of an accelerometer, and a roll angle and a pitch angle are determined by measuring a gravity vector and an angle between a Z axis of a coordinate system of the unmanned vehicle body and an OXY plane; when the unmanned vehicle just starts to move, the course angle of the unmanned vehicle can be obtained through RTK and data of the accelerometer. The formula for obtaining the roll angle and the pitch angle is as follows:
Figure BDA0003934374710000082
in addition, because the IMU, the mounting position of the GNSS antenna and the origin of the coordinate system of the unmanned vehicle-mounted body are not coincident, a homogeneous transformation matrix T of the sensor is required to be calibrated, and the coordinate system of the sensor is converted to a carrier coordinate system;
Figure BDA0003934374710000083
the embodiments of the present invention have been described in detail, but the description is only for the preferred embodiments of the present invention and should not be construed as limiting the scope of the present invention. All equivalent changes and modifications made within the scope of the present invention should be covered by the present patent.

Claims (5)

1. A positioning method based on wheel speed inertial navigation combined pre-integration and RTK tight combination is characterized by comprising the following steps:
receiving satellite navigation data and constructing an observation residual error representing a satellite navigation error amount;
step two, acquiring the mileage increment in each time interval through a wheel speed meter, and performing combined pre-integration by combining an inertial sensor to generate a pre-integration residual error containing the integral error of the sensor and the wheel speed meter;
and thirdly, tightly combining the pre-integral residual error and the observation residual error to generate a correction factor, and correcting the satellite positioning according to the correction factor.
2. The positioning method based on wheel speed inertial navigation combined pre-integration and RTK close combination as claimed in claim 1, wherein the combined pre-integration includes velocity increment β, displacement increment α, attitude change q and mileage increment s, and propagation equations of β, α, q and s are constructed respectively, and the propagation equation of mileage increment s is:
Figure FDA0003934374700000011
wherein:
Figure FDA0003934374700000012
representing the displacement between the moment k-1 and the moment i under the inertial navigation coordinate system b,
Figure FDA0003934374700000013
represents the displacement between the k-1 moment and the i-1 moment under the inertial navigation coordinate system b
Figure FDA0003934374700000014
Representing the displacement between the moment i-1 and the moment i under the inertial navigation coordinate system b, so as to separately acquire the mileage increment in each period,
the propagation equation of the mileage increment is as follows:
Figure FDA0003934374700000015
Figure FDA0003934374700000016
wherein
Figure FDA0003934374700000017
And
Figure FDA0003934374700000018
are rotation matrixes, are used for rotating the equipment coordinate system v to be under the inertial navigation coordinate system b,
Figure FDA0003934374700000019
indicating the displacement between the time i-1 and the time i under the coordinate system v of the device,
Figure FDA00039343747000000110
Figure FDA00039343747000000111
indicating errors in the position of the wheel speed meter and inertial sensor corrected in the inertial navigation coordinate system bThe lever arm corrects the error amount.
3. The method of claim 1, wherein the observation residuals include double-difference pseudorange observation residuals
Figure FDA0003934374700000021
Sum double difference phase observation residual
Figure FDA0003934374700000022
IMU/wheel speed meter combined pre-integration residual error under satellite coordinate system according to combined pre-integration construction
Figure FDA0003934374700000023
The correction factors are as follows:
Figure FDA0003934374700000024
4. the method of claim 1, wherein the IMU/wheel speed meter combined pre-integration residual error is based on wheel speed inertial navigation combined pre-integration and RTK tightly combined positioning method
Figure FDA0003934374700000025
Wherein
Figure FDA0003934374700000026
Represents a covariance matrix of the IMU/wheel speed meter combined pre-integration observation factors under the geodetic coordinate system,
Figure FDA0003934374700000027
and the residual matrix comprises a position change residual, a speed change residual, an attitude change residual, an accelerometer zero offset residual, a gyroscope zero offset residual and a wheel speed meter displacement residual.
5. The method for positioning based on wheel speed inertial navigation combined pre-integration and RTK close combination as claimed in claim 1, wherein an initialization strategy is added before the first step, the initialization strategy includes acquiring initial coordinates and initial attitude of the device;
the initial coordinates comprise positioning coordinate data of a plurality of groups of satellite navigation, the average value of the positioning coordinate data is obtained, acceleration count data is obtained to calculate gravity vectors, and included angles between the gravity vectors and a Z axis and an OXY plane of an equipment coordinate system are obtained so as to respectively generate initial states comprising roll angles and pitch angles.
CN202211402919.4A 2022-11-09 2022-11-09 Positioning method based on wheel speed inertial navigation combined pre-integration and RTK tight combination Pending CN115507848A (en)

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Citations (2)

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Publication number Priority date Publication date Assignee Title
CN110007328A (en) * 2019-05-10 2019-07-12 国网浙江省电力有限公司信息通信分公司 Non-combined RTK localization method based on four frequency observation of No. three satellites of Beidou
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Publication number Priority date Publication date Assignee Title
CN110007328A (en) * 2019-05-10 2019-07-12 国网浙江省电力有限公司信息通信分公司 Non-combined RTK localization method based on four frequency observation of No. three satellites of Beidou
CN113175933A (en) * 2021-04-28 2021-07-27 南京航空航天大学 Factor graph combined navigation method based on high-precision inertia pre-integration

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