CN108548535B - Initialization method of low-speed GNSS/MEMS (Global navigation satellite System/micro-electromechanical System) integrated navigation system - Google Patents

Initialization method of low-speed GNSS/MEMS (Global navigation satellite System/micro-electromechanical System) integrated navigation system Download PDF

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CN108548535B
CN108548535B CN201810204702.XA CN201810204702A CN108548535B CN 108548535 B CN108548535 B CN 108548535B CN 201810204702 A CN201810204702 A CN 201810204702A CN 108548535 B CN108548535 B CN 108548535B
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CN108548535A (en
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杨勇
韩晓
刘华
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BEIJING SANDCANYON 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
    • G01C21/20—Instruments for performing navigational calculations
    • 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 an initialization method of a low-speed GNSS/MEMS (global navigation satellite system/micro-electromechanical system) combined navigation system, which comprises the steps of determining the initial position of the combined system by utilizing the position of the GNSS, and determining the horizontal initial attitude, namely a pitch angle and a roll angle, by utilizing a mode of total specific force obtained by gravity field projection and GNSS derivation; dividing low-speed motion observed by GNSS into a plurality of intervals, establishing a single-dimensional filter family with the same number as the intervals, and taking the initial course error as a filter estimation state and the speed as a filter observed quantity for each filter; and determining the course with the minimum estimation error variance as the initial value of the moment by comparing the filtering results, and finishing the initial course when the courses at a plurality of continuous moments are determined by the filter in the same interval, wherein the initial course determined by the filter is the initial course of the combined guided dirty system. The method is not limited by the moving speed of the carrier, and can complete the initialization of the integrated navigation in a low-speed state.

Description

Initialization method of low-speed GNSS/MEMS (Global navigation satellite System/micro-electromechanical System) integrated navigation system
Technical Field
The invention belongs to the technical field of inertial navigation and satellite navigation, and particularly relates to an initialization method of a low-speed GNSS/MEMS (global navigation satellite system/micro-electromechanical system) combined navigation system.
Background
The Beidou satellite navigation System is a globally covering satellite based navigation System (GNSS) that is co-driven with the United states GPS, Russian GLONASS, and European GALILEO. With the gradual improvement of the third-stage Beidou network deployment, the Beidou system is gradually popularized and applied to various navy, army and civil carriers. The satellite navigation system has the remarkable characteristics that absolute positioning coordinates are directly provided, errors do not accumulate along with time, and the defects that radio signals are easy to be shielded and interfered exist. An Inertial Navigation System (INS) can autonomously and covertly carry out continuous three-dimensional space Navigation and attitude measurement, has no electromagnetic interference of signals, can track and reflect the maneuvering of a moving carrier, and has stable output. However, the disadvantage of inertial navigation is that the navigation error is accumulated with time, and when the external world does not give any correction to the inertial navigation, the error is increased unboundedly.
A micro electro Mechanical system (mems) is a micro electromechanical system that integrates a micro sensor, an actuator, a signal processing and control circuit, an interface circuit, a communication circuit, and a power supply, and is developed along with the development of a semiconductor integrated circuit micro processing technology and an ultra-precision machining technology. The MEMS inertial sensor mainly refers to two inertial sensors, namely a silicon micro-accelerometer and a silicon micro-gyroscope, and is used for measuring the linear acceleration and the rotation angular velocity of a moving carrier. The MEMS inertial sensor inherits the characteristics of complete autonomy, strong confidentiality, no signal electromagnetic interference and the like of the traditional inertial sensor, and has the advantages of small size, light weight, low cost, low power consumption, high reliability and the like which cannot be compared with the traditional inertial sensor. But due to the manufacturing process, when used as a navigational fix, errors accumulate rapidly over time.
The combined navigation system combining the GNSS and the inertial sensor gives full play to the advantages of the GNSS and the inertial sensor, and forms organic complementation. The advantages are that: the inertial navigation can keep higher precision in a short time, and random errors generated in the GNSS positioning process can be compensated because the inertial navigation is not influenced by the external working environment; meanwhile, the absolute positioning speed measurement information provided by the GNSS can compensate the error accumulated by inertial navigation along with time, so that the measurement precision in long-distance running is ensured; the dynamic information of inertial navigation in a short time can help to improve the problems of signal lock loss and jump in the GNSS high dynamic and interference environment.
The inertial navigation system measures three-dimensional linear motion of the carrier through the accelerometer, measures three-dimensional angular motion of the carrier through the gyroscope, and then performs integration on a navigation coordinate system to acquire speed, position and attitude. The use of inertial navigation in navigation positioning needs to complete initialization, and then integral calculation is performed on the basis of initial information to obtain a navigation result at the current moment. The initialization information includes three-dimensional position, velocity, and pose. The error of the initial information becomes one of the main error sources of the inertial navigation system, the error is transmitted over time, and after integration, the error is accumulated unbounded.
The inertial navigation system with high precision and high cost can sense the rotation of the earth through a high-precision gyroscope and can autonomously complete initialization by combining the projection of a gravity field on a vehicle carrier coordinate system. However, the precision of the MEMS gyroscope is low, the rotational angular rate of the earth of 15 °/hour is completely annihilated in the noise of the gyroscope, and the inertial navigation system cannot complete autonomous initialization, so that the assistance of GNSS velocity information is required. In a low-speed moving environment (for example, < 3m/s), the relative motion of the doppler shift between the satellite and the carrier observed by the GNSS receiver is not obvious, so the GNSS velocity error calculated according to the doppler is large, and the difficulty in initializing the MEMS inertial navigation increases.
Disclosure of Invention
The invention aims to provide an initialization method of a low-speed GNSS/MEMS combined navigation system, which does not require the driving speed threshold of a vehicle, can start filtering estimation from starting, can greatly shorten the initialization preparation time of the system, enables the initialization of the combined navigation system in a low-speed state to be possible and is not limited by the motion of a carrier.
The technical scheme adopted by the invention is that the initialization method of the low-speed GNSS/MEMS combined navigation system is implemented according to the following steps: determining the initial position of the combined system by utilizing the position of the GNSS, and determining the horizontal initial attitude, namely a pitch angle and a roll angle by utilizing a model of total specific force obtained by gravity field projection and GNSS derivation; dividing the low-speed motion observed by the GNSS into a plurality of intervals, establishing single-dimensional filter families with the same number as the intervals, and performing calculation of a time prediction loop and a measurement updating loop, wherein each filter takes an initial course error as a filter estimation state and takes the speed as a filter observed quantity; determining the course with the minimum estimation error variance as the initial value of the moment by comparing the filtering results, and finishing the initial course when the courses at a plurality of continuous moments are determined by the filter in the same interval, wherein the initial course determined by the filter is the initial course of the combined guided dirty system; and a direction cosine matrix constructed by the initial horizontal attitude and the initial course is the three-dimensional initial attitude information of the integrated navigation system.
The present invention is also characterized in that,
the MEMS inertial sensor comprises three mutually orthogonal MEMS accelerometers and three mutually orthogonal MEMS gyroscopes which are respectively used for measuring the linear acceleration and the angular velocity of the carrier; the GNSS comprises a Beidou, a GPS, a Glonass and a Galileo.
The position of the GNSS is directly obtained by the positioning result of the GNSS, and if the position is in a static state, average smoothing processing is carried out.
The method for determining the horizontal initial attitude, namely the pitch angle and the roll angle, by utilizing the mode of the total specific force obtained by gravity field projection and GNSS derivation comprises the following steps:
in a static or uniform case, the horizontal initial pose may be calculated by the following algorithm:
Figure GDA0003089518000000041
Figure GDA0003089518000000042
Figure GDA0003089518000000043
Figure GDA0003089518000000044
wherein r and p are respectively calculated components of a roll angle and a pitch angle of the horizontal installation angle at the kth moment;
Figure GDA0003089518000000045
are respectively correspondingA filtered estimate at time k; n is a radical ofr,NpRespectively selecting a constant value between 0 and 1 for the corresponding filter gains; f. ofk，i(ii) an accelerometer output of the i, i ═ 0,1,2, axis, at time k, respectively;
Figure GDA0003089518000000046
i is 0,1 and 2, and is an accelerometer zero offset estimation value of the ith axis respectively, and the value is mixed with the projection of the gravity field along each axial direction;
in the dynamic case, the algorithm of the modulus of the total specific force derived from GNSS is as follows:
Figure GDA0003089518000000047
wherein a isGNSS，k，iAcceleration of the GNSS along the ith axis of the navigation coordinate system at the kth moment; vGNSS，k+1，iAnd VGNSS，k，iThe speed of the GNSS along the ith axis of the navigation coordinate system at the k +1 th moment and the k-th moment respectively; t isk+1-TkThe time interval from time k to time k + 1.
When the carrier is in uniform motion, the horizontal initial attitude can be calculated by the following algorithm:
Figure GDA0003089518000000048
Figure GDA0003089518000000049
the calculation of the time prediction loop and the measurement update loop is as follows:
(1) time prediction loop:
Pk+1，k，i＝Pk，i+Qk，i
Kk+1，i＝Pk+1，k，i/(Pk+1，k，i+Rk，i)
(2) a measurement updating loop:
δxk+1，i＝δxk，i+Kk+1，i·zk，i
Pk+1，i＝(1-Kk+1，i)2Pk+1，k，i
wherein, Pk+1，iAnd Pk，iThe filter state variances of the ith interval at the kth +1 and the kth time respectively; pk+1，k，iIs according to Pk，iEstimating the state variance of the filter in the ith interval at the k +1 th moment; qk，iThe system noise of the ith interval at the kth moment; rk，iMeasuring noise of the ith interval at the kth moment; kk+1，iThe filter gain at the k +1 th time; deltaxk+1，iThe error of the initial course angle at the k +1 th moment; z is a radical ofk，iIs filtering information;
(3) the course angle derived from the speed by the GNSS is calculated as follows:
zGNSS，k，i＝tan-1(VGNSS，k，i，e/VGNSS，k，i，n)
zGNSS，k，ithe GNSS course angle of the ith interval at the kth moment; vGNSS，k，i，eAnd VGNSS，k，i，nRespectively representing the east and north speeds of the ith interval GNSS at the kth time.
The specific criterion for comparing the filtering result to determine the heading with the minimum estimation error variance as the initial value at the moment is as follows:
Jm＝min{Pk+1，1，Pk+1，2，…，Pk+1，n}n＝1，2，…6
wherein, Pk+1，iThe filter state variances of the ith interval at the k +1 th moment respectively; j. the design is a squaremAnd m is the interval number corresponding to the minimum variance as a criterion function, and when the minimum variance appears in the same interval for a plurality of times, the initial course estimation is finished.
The matrix elements of the direction cosine matrix are formed by three-dimensional rotation in a rigid Euler angle mode, and the rotation sequence is along a roll angle, a pitch angle and a course angle.
The invention has the beneficial effects that: the method determines a horizontal initial attitude by means of gravity field projection through an online estimation algorithm, and decouples the horizontal initial attitude from an installation error angle; aiming at the low-speed motion environment of the ground vehicle, the low-speed motion observed by the GNSS is divided into a plurality of intervals, and single-dimensional filter families with the same number as the intervals are established, so that the heading with the minimum estimation error variance is determined as an initial value through a filtering result. Initialization of the integrated navigation system is done in conjunction with the position, velocity and estimated attitude of the GNSS. The method does not require the driving speed threshold of the vehicle, and the filtering estimation can be started from the start, so that the initialization preparation time of the system can be greatly shortened, the initialization of the integrated navigation system in a low-speed state becomes possible, and the method is not limited by the motion of a carrier. The method has small calculated amount and strong real-time performance, and is beneficial to realizing the batch application of the GNSS/MEMS combined system on various ground carriers.
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FIG. 1 is a system flow diagram of the present invention.
Detailed Description
The present invention will be described in detail below with reference to the accompanying drawings and specific embodiments.
The invention provides an initialization method of a low-speed GNSS/MEMS (global navigation satellite system/micro-electromechanical system) combined navigation system, a flow chart of the system is shown in figure 1, and carriers relate to, but are not limited to, bicycles, electric vehicles, low-speed agricultural vehicles, sanitation vehicles, construction engineering vehicles, unmanned delivery vehicles, self-service cabinets and the like. The technology for estimating the initialization information of the integrated navigation system on line is implemented according to the following steps: determining the initial position of the combined system by utilizing the position of the GNSS, and determining the horizontal initial attitude, namely a pitch angle and a roll angle by utilizing a model of total specific force obtained by gravity field projection and GNSS derivation; dividing the low-speed motion observed by the GNSS into a plurality of intervals, establishing single-dimensional filter families with the same number as the intervals, and performing calculation of a time prediction loop and a measurement updating loop, wherein each filter takes an initial course error as a filter estimation state and takes the speed as a filter observed quantity; determining the course with the minimum estimation error variance as the initial value of the moment by comparing the filtering results, and finishing the initial course when the courses at a plurality of continuous moments are determined by the filter in the same interval, wherein the initial course determined by the filter is the initial course of the integrated navigation system; and a direction cosine matrix constructed by the initial horizontal attitude and the initial course is the three-dimensional initial attitude information of the integrated navigation system.
The MEMS refers to a micro-electro-mechanical system, and the MEMS inertial sensor is a core component forming an MEMS inertial navigation system and comprises an MEMS accelerometer and an MEMS gyroscope.
The MEMS IMU refers to a measuring unit formed by MEMS inertial sensors, wherein the MEMS inertial sensors are three mutually orthogonal MEMS accelerometers and three mutually orthogonal MEMS gyroscopes which are respectively used for measuring the linear acceleration and the angular velocity of a carrier; the GNSS comprises a Beidou, a GPS, a Glonass and a Galileo.
The position of the GNSS is directly obtained by the positioning result of the GNSS, and if the position is in a static state, average smoothing processing is carried out.
Firstly, determining a horizontal initial attitude, namely a pitch angle and a roll angle by utilizing a model of total specific force obtained by gravity field projection and GNSS derivation, wherein the determination method comprises the following steps:
in a static or uniform case, the horizontal initial pose may be calculated by the following algorithm:
Figure GDA0003089518000000071
Figure GDA0003089518000000072
Figure GDA0003089518000000073
Figure GDA0003089518000000074
wherein r and p are respectively calculated components of a roll angle and a pitch angle of the horizontal installation angle at the kth moment;
Figure GDA0003089518000000075
respectively corresponding filtering estimators at the k-th moment; n is a radical ofr,NpRespectively selecting a constant value between 0 and 1 for the corresponding filter gains; f. ofk，i(ii) an accelerometer output of the i, i ═ 0,1,2, axis, at time k, respectively;
Figure GDA0003089518000000076
i is 0,1 and 2, and is an accelerometer zero offset estimation value of the ith axis respectively, and the value is mixed with the projection of the gravity field along each axial direction;
in the dynamic case, the algorithm of the modulus of the total specific force derived from GNSS is as follows:
Figure GDA0003089518000000081
wherein a isGNSS，k，iAcceleration of the GNSS along the ith axis of the navigation coordinate system at the kth moment; vGNSS，k+1，iAnd VGNSS，k，iThe speed of the GNSS along the ith axis of the navigation coordinate system at the k +1 th moment and the k-th moment respectively; t isk+1-TkThe time interval from k to k + 1;
when the carrier is in uniform motion, the horizontal initial attitude can be calculated by the following algorithm:
Figure GDA0003089518000000082
Figure GDA0003089518000000083
secondly, dividing the low-speed motion observed by the GNSS into a plurality of intervals, which is implemented as follows:
table 1: partitioning motion state intervals according to GNSS speed and uncertainty thereof
Figure GDA0003089518000000084
It should be noted that the selection of the speed and its uncertainty threshold may be adjusted based on the data, and the values listed above may be selected.
The third step: establishing a filter corresponding to the interval, and performing calculation of the time prediction loop and the measurement updating loop, wherein a filter algorithm corresponding to the interval is divided into the time prediction loop and the measurement updating loop, and the specific steps are as follows:
(1) time prediction loop:
Pk+1，k，i＝Pk，i+Qk，i
Kk+1，i＝Pk+1，k，i/(Pk+1，k，i+Rk，i)
(2) a measurement updating loop:
δxk+1，i＝δxk，i+Kk+1，i·zk，i
Pk+1，i＝(1-Kk+1，i)2Pk+1，k，i
wherein, Pk+1，iAnd Pk，iThe filter state variances of the ith interval at the kth +1 and the kth time respectively; pk+1，k，iIs according to Pk，iEstimating the state variance of the filter in the ith interval at the k +1 th moment; qk，iThe system noise of the ith interval at the kth moment; pk，iMeasuring noise of the ith interval at the kth moment; kk+1，iThe filter gain at the k +1 th time; deltaxk+1，iThe error of the initial course angle at the k +1 th moment; z is a radical ofk，iIs filtering information;
the time prediction loop remains running at every moment, but the measurement update loop is only performed when the speed estimated by the GNSS falls within the corresponding interval.
(3) The course angle derived from the speed by the GNSS is calculated as follows:
zGNSS，k，i＝tan-1(VGNSS，k，i，e/VGNSS，k，i，n)
zGNSS，k，ithe GNSS course angle of the ith interval at the kth moment; vGNSS，k，i，eAnd VGNSS，k，i，nThe east (e) and north (n) velocities of the ith interval GNSS at the kth time are respectively indicated.
Fourthly, comparing the filtering results to determine the heading with the minimum estimation error variance as the specific criterion of the initial value at the moment as follows:
Jm＝min{Pk+1，1，Pk+1，2，…，Pk+1，n}n＝1，2，…6
wherein, Pk+1，iThe filter state variances of the ith interval at the k +1 th moment respectively; j. the design is a squaremAnd m is the interval number corresponding to the minimum variance as a criterion function, and when the minimum variance appears in the same interval for a plurality of times, the initial course estimation is finished.
The fifth step: and establishing a direction cosine matrix of a body coordinate system of the carrier and a navigation coordinate system of the system, wherein the direction cosine matrix formed by the three-dimensional initial attitude information establishes a conversion relation from the body coordinate system to the navigation coordinate system, matrix elements of the direction cosine matrix are formed by three-dimensional rotation in a rigid Euler angle mode, and the rotation sequence is along a roll angle, a pitch angle and a course angle.
The invention has the advantages that: the method determines a horizontal initial attitude by means of gravity field projection through an online estimation algorithm, and decouples the horizontal initial attitude from an installation error angle; aiming at the low-speed motion environment of the ground vehicle, the low-speed motion observed by the GNSS is divided into a plurality of intervals, and single-dimensional filter families with the same number as the intervals are established, so that the heading with the minimum estimation error variance is determined as an initial value through a filtering result. Initialization of the integrated navigation system is done in conjunction with the position, velocity and estimated attitude of the GNSS. The method does not require the driving speed threshold of the vehicle, and the filtering estimation can be started from the start, so that the initialization preparation time of the system can be greatly shortened, the initialization of the integrated navigation system in a low-speed state becomes possible, and the method is not limited by the motion of a carrier. The method has small calculated amount and strong real-time performance, and is beneficial to realizing the batch application of the GNSS/MEMS combined system on various ground carriers.

Claims (6)

1. The initialization method of the low-speed GNSS/MEMS combined navigation system is characterized by comprising the following steps: determining the initial position of the combined system by utilizing the position of the GNSS, and determining the horizontal initial attitude, namely a pitch angle and a roll angle by utilizing a model of total specific force obtained by gravity field projection and GNSS derivation; dividing the low-speed motion observed by the GNSS into a plurality of intervals, establishing single-dimensional filter families with the same number as the intervals, and performing calculation of a time prediction loop and a measurement updating loop, wherein each filter takes an initial course error as a filter estimation state and takes the speed as a filter observed quantity; determining the course with the minimum estimation error variance as the initial value of the moment by comparing the filtering results, and finishing the initial course when the courses at a plurality of continuous moments are determined by the filter in the same interval, wherein the initial course determined by the filter is the initial course of the integrated navigation system; a direction cosine matrix constructed by the initial horizontal attitude and the initial course is the three-dimensional initial attitude information of the integrated navigation system;
the calculation of the time prediction loop and the measurement update loop is as follows:
(1) time prediction loop:
Pk+1，k，i＝Pk，i+Qk,i
Kk+1，i＝Pk+1，k，i/(Pk+1，k，i+Rk，i)
(2) a measurement updating loop:
δxk+1，i＝δxk，i+Kk+1，i·zk，i
Pk+1，i＝(1-Kk+1，i)2Pk+1，k，i
wherein, Pk+1，iAnd Pk，iThe filter state variances of the ith interval at the kth +1 and the kth time respectively; pk+1，k，iIs according to Pk，iEstimating the state variance of the filter in the ith interval at the k +1 th moment; qk，iThe system noise of the ith interval at the kth moment; rk，iMeasuring noise of the ith interval at the kth moment; kk+1，iThe filter gain at the k +1 th time; deltaxk+1，iIs the k +1 th time point is initialError of course angle; z is a radical ofk，iIs filtering information;
(3) the course angle derived from the speed by the GNSS is calculated as follows:
zGNSS，k，i＝tan-1(VGNSS，k，i，e/VGNSS，k，i，n)
zGNSS，k，ithe GNSS course angle of the ith interval at the kth moment; vGNSS，k，i，eAnd VGNSS，k，i，nRespectively representing the east and north speeds of the ith interval GNSS at the kth time.
2. The initialization method of a low-speed GNSS/MEMS combined navigation system of claim 1, wherein the MEMS inertial sensors are three mutually orthogonal MEMS accelerometers and three mutually orthogonal MEMS gyroscopes for measuring linear acceleration and angular velocity of the carrier respectively; the GNSS comprises a Beidou, a GPS, a Glonass and a Galileo.
3. The initialization method of a low speed GNSS/MEMS integrated navigation system of claim 1, wherein the GNSS position is directly obtained from the GNSS positioning result, and if it is in a static state, the average smoothing process is performed.
4. The method of claim 1, wherein the horizontal initial attitude, i.e. pitch angle and roll angle, is determined by using the gravity field projection and the GNSS derived model of the total specific force, and the method comprises:
in a static or uniform case, the horizontal initial pose may be calculated by the following algorithm:
Figure FDA0003089517990000021
Figure FDA0003089517990000022
Figure FDA0003089517990000023
Figure FDA0003089517990000024
wherein r and p are respectively calculated components of a roll angle and a pitch angle of the horizontal installation angle at the kth moment;
Figure FDA0003089517990000031
respectively corresponding filtering estimators at the k-th moment; n is a radical ofr,NpRespectively selecting a constant value between 0 and 1 for the corresponding filter gains; f. ofk，i(ii) an accelerometer output of the i, i ═ 0,1,2, axis, at time k, respectively;
Figure FDA0003089517990000032
the zero offset estimated values of the accelerometers of the ith axis are mixed with the projection of the gravity field along each axial direction;
in the dynamic case, the algorithm of the modulus of the total specific force derived from the GNSS is as follows:
Figure FDA0003089517990000033
wherein a isGNSS，k，iAcceleration of the GNSS along the ith axis of the navigation coordinate system at the kth moment; vGNSS，k+1，iAnd VGNSS，k，iThe speed of the GNSS along the ith axis of the navigation coordinate system at the k +1 th moment and the k-th moment respectively; t isk+1-TkThe time interval from k to k + 1;
when the carrier is in uniform motion, the horizontal initial attitude can be calculated by the following algorithm:
Figure FDA0003089517990000034
Figure FDA0003089517990000035
5. the initialization method of a low-speed GNSS/MEMS combined navigation system as claimed in claim 1, wherein the specific criteria for determining the heading with the minimum estimation error variance as the initial value at the time point according to the comparison filtering result are as follows:
Jm＝min{Pk+1，1，Pk+1，2，…，Pk+1，n}n＝1，2，…6
wherein, Pk+1，iThe filter state variances of the ith interval at the k +1 th moment respectively; j. the design is a squaremAnd m is the interval number corresponding to the minimum variance as a criterion function, and when the minimum variance appears in the same interval for a plurality of times, the initial course estimation is finished.
6. The method of claim 1, wherein the matrix elements of the direction cosine matrix are formed by three-dimensional rotation in Euler angles, and the rotation sequence is roll angle, pitch angle and course angle.
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