CN111380521B - Multipath filtering method in GNSS/MEMS inertia combined chip positioning algorithm - Google Patents

Multipath filtering method in GNSS/MEMS inertia combined chip positioning algorithm Download PDF

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CN111380521B
CN111380521B CN202010240143.5A CN202010240143A CN111380521B CN 111380521 B CN111380521 B CN 111380521B CN 202010240143 A CN202010240143 A CN 202010240143A CN 111380521 B CN111380521 B CN 111380521B
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CN111380521A (en
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杨勇
刘华
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BEIJING SANDCANYON TECHNOLOGY Co.,Ltd.
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Suzhou Xinzhigu Intelligent 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
    • G01C21/10—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
    • G01C21/18—Stabilised platforms, e.g. by gyroscope
    • 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
    • G01S19/01—Satellite radio beacon positioning systems transmitting time-stamped messages, e.g. GPS [Global Positioning System], GLONASS [Global Orbiting Navigation Satellite System] or GALILEO
    • G01S19/13—Receivers
    • G01S19/24—Acquisition or tracking or demodulation of signals transmitted by the system
    • 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

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Abstract

The invention discloses a multipath filtering method in a GNSS/MEMS inertia combined chip positioning algorithm, which comprises the following steps of establishing two stages of filters in a navigation positioning unit of a chip: the first-stage filter is used for estimating a multipath value of each satellite observation quantity, and the pseudo range calculated by the IMU is used as an observation input; the second-stage filter uses the GNSS pseudo range and Doppler after multipath correction as observation input; the two-stage filter is carried out in a resolving unit of the integrated navigation chip, and the error of the MEMS sensor is corrected according to an estimated value generated by the second-stage filter; the clock error and the clock drift are fed back to each satellite pseudo range and Doppler observed quantity generated by the GNSS tracking loop, and the other errors of the pseudo range part except the multipath error are reduced. The method can realize the multipath influence resistance in a weak satellite environment (such as an urban canyon) and continuously keep the navigation positioning precision.

Description

Multipath filtering method in GNSS/MEMS inertia combined chip positioning algorithm
Technical Field
The invention belongs to the technical field of satellite navigation and inertial navigation, and particularly relates to a multipath filter technology based on a GNSS/MEMS combined navigation chip positioning algorithm.
Background
Inertial navigation based on MEMS (Micro-Electro-Mechanical System) inertial sensors has the characteristics of undisturbed and fully autonomous navigation, but errors accumulate over time. The significant features of a satellite navigation system (GNSS) are that absolute positioning coordinates are directly provided, and errors do not accumulate over time, but there is a disadvantage that radio signals are susceptible to occlusion and interference. The combination of the inertia and the satellite navigation which are closely combined gives full play to the advantages of the inertia and the satellite navigation, and the combined system can continuously provide the position, the speed and the time information of the system under the weak satellite environment.
In a weak satellite environment, such as an urban canyon or a tall building, the satellite signals in the straight line of sight are refracted to form multipath signals. The pseudo range observation quantity influenced by the multipath is formed by superposing the real pseudo range quantity and the offset quantity. Since multipath signals are caused by increased propagation paths, i.e., increased propagation times, and are typically positively biased, the bias variations have a statistical zero-mean property.
The multipath interference resistance can be carried out in one of any three links of the GNSS receiver, namely an antenna/radio frequency front-end link, a signal tracking link and a navigation resolving link, the special technologies of the first two links can obviously increase the receiving cost, and the actual implementation performance is not realized in the chip GNSS receiver particularly. More advanced algorithms are needed in the chip to achieve the goal of low cost and multipath resistance, and especially how to keep the precision under the weak star environment which is more likely to appear in the popular application scene has great technical challenge. The GNSS/MEMS inertia combined navigation chip can achieve the target more conveniently by means of auxiliary information of the MEMS inertia device.
Disclosure of Invention
1. Objects of the invention
The invention provides a multipath filter technology based on a GNSS/MEMS combined navigation chip positioning algorithm. The filtering technology is composed of two stages of filters, wherein the first stage of filter is used for estimating a multipath value of each satellite observation quantity, and a pseudo range calculated by an IMU is used as an observation input; the second stage filter uses the corrected multipath GNSS pseudoranges and doppler as the observed input. The two-stage filter is carried out in a resolving unit of the integrated navigation chip, so that the multipath influence resistance is realized in a weak satellite environment (such as an urban canyon) and the target of continuously keeping the navigation positioning precision is realized.
2. The technical scheme adopted by the invention
The invention discloses a multipath filtering method in a GNSS/MEMS inertia combined chip positioning algorithm, which comprises the following steps of establishing two-stage filters in a navigation positioning unit of a chip:
the first-stage filter is used for estimating a multipath value of each satellite observation quantity, and the pseudo range calculated by the IMU is used as an observation input; the second-stage filter uses the GNSS pseudo range and Doppler after multipath correction as observation input;
the two-stage filter is carried out in a resolving unit of the integrated navigation chip, and the MEMS sensor error is corrected according to the estimated values of the three-axis accelerometer zero offset and the three-axis gyroscope zero offset generated by the second-stage filter, so that the position and speed error after inertial navigation resolving is restrained, and the pseudo range precision obtained by IMU calculation is improved; the clock error and the clock drift are fed back to each satellite pseudo range and Doppler observed quantity generated by the GNSS tracking loop, and the influence of other errors of the pseudo range part except the multipath error on the GNSS pseudo range input error in the first-stage filter is reduced.
Preferably, the first stage filter establishes a one-dimensional filter to form a filter bank according to each tracked satellite, each single filter takes multipath as a to-be-estimated quantity, and the multipath is an offset of a true pseudorange, assuming that a mathematical model thereof is a random constant. The difference value of the pseudo range obtained by IMU calculation and the GNSS pseudo range is the filter observation updating amount; the results of the multipath estimation for each satellite are used in the second stage filter.
Preferably, 1.1, a one-dimensional filter is established according to each tracked satellite to form a filter family, and each single filter takes multiple paths as a to-be-estimated quantity;
assume that the multipath for each satellite has the following dynamic equation
xk,i＝xk-1，i+vk,iWhere i denotes the ith tracked satellite, vk,iAssume zero mean gaussian noise.
The prediction of the filtering can be expressed as pk,i＝pk-1，i+qk，iWherein q isk，iThe dynamic noise of multipath can be taken out according to actual modeling.
Filtering of ith multipathk，iCan be expressed as:
sk，i＝hk，ipk,ihk,i+rk,i
wherein h isk,i,rk,iRepresenting the filtered design matrix and the observed noise, respectively.
The filter gain can be expressed as: m isk,i＝pk，i/sk,i
The observations of the filtered measurement update are: z is a radical ofk,i＝ρIMU,i-ρi
Where ρ isIMU,i、ρiAnd respectively calculating the pseudo range of the ith satellite obtained by IMU and the original pseudo range generated by GNSS. IMU counterfeitThe following calculation formula can be derived for range and doppler
Figure BDA0002432262390000031
(xI,yI,zI) Indicating the position of the IMU, ecef (Earth Centered Earth fix) coordinate system; (x)s,i,ys,i,zs,i) Indicating the position, ECEF coordinates, of the ith satellite.
1.2: correcting the original pseudo range of each satellite of the GNSS according to the result of the first step;
Figure BDA0002432262390000032
1.3: examination of rhoIMU,i、ρiAnd judging whether to continue to operate the filter of the satellite at the next moment according to the difference value between the two signals, if the satellite tracking is discontinuous or the difference value is smaller than a threshold, resetting the multipath filtering of the satellite, wherein the threshold is selected to be 10m for the GPS satellite and the Galileo satellite, and the threshold is selected to be 15m for the Beidou or the Glonass satellite. The threshold may be adjusted based on actual chip loop noise.
Preferably, the second-stage filtering algorithm selects an error to be estimated as a state, and the 17-dimensional error state vector comprises a three-dimensional position error, a three-dimensional speed error, a three-dimensional attitude error, a three-axis accelerometer zero offset, a three-axis gyroscope zero offset, and a clock error and a clock drift of the receiver.
Preferably, a second stage combined navigation filter is established.
The combined filtering algorithm selects an error to be estimated as a state, and a 17-dimensional error state vector comprises a three-dimensional position error, a three-dimensional speed error, a three-dimensional attitude error, a three-axis accelerometer zero offset, a three-axis gyroscope zero offset, a clock error and a clock drift of a receiver.
Using pseudoranges and doppler of satellites as filter observations
Then each pair of pseudorange and doppler observations is
Figure BDA0002432262390000033
Where ρ isIMU,fdopp-IMUPseudoranges and doppler, p, computed separately for the IMUi,fidopp-GPSM represents m valid satellites for the pseudorange and doppler measurements for the ith satellite.
Where pseudorange and doppler of the IMU may be derived the following calculation
Figure BDA0002432262390000034
Figure BDA0002432262390000035
Wherein (v)INS,x,vINS,y,vINS,z) Representing the velocity of the IMU, ECEF coordinate system;
(vsv,xi,vsv,yi,vsv,zi) Representing the velocity, ECEF coordinate system, of the ith satellite; λ is the wavelength of the satellite signal; (e)ix,eiy,eiz) Is the line-of-sight vector for the ith star.
Its corresponding design matrix can be written as
Figure BDA0002432262390000041
Where E is a line-of-sight matrix consisting of line-of-sight vectors determined by the current estimated position and the satellite positions.
Preferably, a step of feedback correction of the sensor error is also included.
Preferably, the method further comprises the steps of feedback correction of clock errors, namely clock error removal in the GNSS raw pseudoranges at the next time and clock drift removal in the GNSS raw Doppler.
3. Advantageous effects adopted by the present invention
The method can inhibit the negative influence on navigation positioning caused by satellite multipath signals in the weak satellite environments such as urban canyons, nearby high-rise buildings, dense trees and the like. The first-stage filter is used for estimating a multipath value of each satellite observation quantity, and the pseudo range calculated by the IMU is used as an observation input; the second stage filter uses the corrected multipath GNSS pseudoranges and doppler as the observed input. The two-stage filter is carried out in a resolving unit of the integrated navigation chip, so that the multipath influence resistance is realized in a weak satellite environment (such as an urban canyon) and the target of continuously keeping the navigation positioning precision is realized.
Drawings
FIG. 1 is a schematic diagram of a multipath filter in a GNSS/MEMS chip positioning algorithm of the present invention.
Fig. 2 shows the result of the Est-MP multipath estimation of GNSS using the first-stage filter proposed by the present invention.
FIG. 3 is a schematic diagram of IMU and GNSS observation information input to the second stage filter after multipath compensation.
Detailed Description
The technical solutions in the examples of the present invention are clearly and completely described below with reference to the drawings in the examples 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 of the present invention without inventive step, are within the scope of the present invention.
The present invention will be described in further detail with reference to the accompanying drawings.
Examples
Establishing a multipath filter for each continuously tracked satellite, and directly using a pseudo-range multipath value of the satellite as a state to be estimated; the pseudo range calculated by the IMU is used as the observation input of a multipath filter for Kalman filtering calculation, the multipath filter is essentially a filter family and consists of a plurality of single filters, the number of the filtering units in the filter family is dynamically determined according to the number of the tracked satellites, and each filtering unit is initialized when the satellites are not tracked any more or multipath influence does not exist; triggering and initializing each satellite multipath filter, and performing threshold judgment by an IMU (inertial measurement unit); and establishing a tight combination filter for the GNSS/MEMS combined navigation, and performing Kalman filtering calculation by using the GNSS pseudo range and Doppler after multipath correction as observation input.
Two stages of filters are established in a navigation positioning unit of a chip, wherein the first stage is used for determining multipath observed quantity, and the second stage is used for providing continuous navigation positioning results. The first stage filter operates and initializes pseudorange and doppler determinations derived by the IMU. The two-stage filter is carried out in a resolving unit of the integrated navigation chip, so that the influence of the multipath effect of satellite signals can be resisted in a weak satellite environment (such as an urban canyon) and the navigation positioning precision can be continuously kept. The principle is shown in fig. 1. The filtering technology is composed of two stages of filters, wherein the first stage of filter is used for estimating the multipath value of each satellite observation quantity; the second-stage filter uses the corrected GNSS pseudo range and Doppler after multipath as observation input, thereby realizing multipath influence resistance in a weak satellite environment (such as an urban canyon) and continuously keeping the target of navigation positioning precision. The two-stage filter is carried out in a resolving unit of the integrated navigation chip,
the first step is as follows: one-dimensional filters are established to form a filter bank according to each tracked satellite, and each single filter takes multipath as a to-be-estimated quantity.
Assume that the multipath for each satellite has the following dynamic equation
xk，i＝xk-1，i+vk，iWhere i denotes the ith tracked satellite, vk，iAssume zero mean gaussian noise.
The prediction of the filtering can be expressed as pk，i＝pk-1，i+qk，iWherein q isk，iThe dynamic noise of multipath can be taken out according to actual modeling.
Filtering of ith multipathk，iCan be expressed as:
sk，i＝hk,ipk,ihk,i+rk,i
wherein h isk,i,rk,iRepresenting the filtered design matrix and the observed noise, respectively.
The filter gain canExpressed as: m isk,i＝pk,i/sk,i
The observations of the filtered measurement update are: z is a radical ofk,i＝ρIMU,i-ρi
Where ρ isIMU,i、ρiAnd respectively calculating the pseudo range of the ith satellite obtained by IMU and the original pseudo range generated by GNSS. The pseudoranges and doppler of the IMU can be derived from the following equations
Figure BDA0002432262390000061
(xI,yI,zI) Indicating the position of the IMU, ecef (Earth Centered Earth fix) coordinate system; (x)s,i,ys,i,zs,i) Indicating the position, ECEF coordinates, of the ith satellite.
The second step is that: correcting the original pseudo range of each satellite of the GNSS according to the result of the first step;
Figure BDA0002432262390000062
the third step: examination of rhoIMU,i、ρiAnd judging whether to continue to operate the filter of the satellite at the next moment according to the difference value between the two signals, if the satellite tracking is discontinuous or the difference value is smaller than a threshold, resetting the multipath filtering of the satellite, wherein the threshold is selected to be 10m for the GPS satellite and the Galileo satellite, and the threshold is selected to be 15m for the Beidou or the Glonass satellite. The threshold may be adjusted based on actual chip loop noise.
The fourth step: and establishing a second-stage combined navigation filter.
The combined filtering algorithm selects an error to be estimated as a state, and a 17-dimensional error state vector comprises a three-dimensional position error, a three-dimensional speed error, a three-dimensional attitude error, a three-axis accelerometer zero offset, a three-axis gyroscope zero offset, a clock error and a clock drift of a receiver.
Using pseudoranges and doppler of satellites as filter observations
Then each pair of pseudorange and doppler observations is
Figure BDA0002432262390000063
Where ρ isIMU,fdopp-IMUPseudoranges and doppler, p, computed separately for the IMUi,fidopp-GPSM represents m valid satellites for the pseudorange and doppler measurements for the ith satellite.
Where pseudorange and doppler of the IMU may be derived the following calculation
Figure BDA0002432262390000064
Figure BDA0002432262390000065
Wherein (v)INS,x,vINS,y,vINS,z) Representing the velocity of the IMU, ECEF coordinate system;
(vsv,xi,vsv,yi，vsv，zi) Representing the velocity, ECEF coordinate system, of the ith satellite; λ is the wavelength of the satellite signal; (e)ix，eiy，eiz) Is the line-of-sight vector for the ith star.
Its corresponding design matrix can be written as
Figure BDA0002432262390000071
Where E is a line-of-sight matrix consisting of line-of-sight vectors determined by the current estimated position and the satellite positions.
The fifth step: feedback correcting sensor errors;
and a sixth step: and (4) feeding back and correcting the clock error, namely removing clock error from the GNSS raw pseudo range in the first step and the second step at the next moment, and removing clock drift from the GNSS raw Doppler in the second step.
The algorithm provided by the invention is subjected to effect test, and the test environment is a dense urban building group environment. Using the high level GNSS/IMU combination as the reference truth, the following results, for example, the Beidou SVID15, are shown. Referring to fig. 2, Est-MP is the result of GNSS multipath estimation using the first-stage filter proposed in the present invention, and Truth-MP represents the GNSS multipath true value calculated based on the reference system. It can be seen that Est-MP is effective for multipath estimation. The IMU and GNSS observation information input to the second stage filter after multipath compensation is shown in fig. 3.
The above description is only for the preferred embodiment of the present invention, but the scope of the present invention is not limited thereto, and any changes or substitutions that can be easily conceived by those skilled in the art within the technical scope of the present invention are included in the scope of the present invention. Therefore, the protection scope of the present invention shall be subject to the protection scope of the claims.

Claims (5)

1. A multipath filtering method in a GNSS/MEMS inertia combined chip positioning algorithm is characterized in that a two-stage filter is established in a navigation positioning unit of a chip:
the first-stage filter is used for estimating a multipath value of each satellite observation quantity, and the pseudo range calculated by the IMU is used as an observation input; the second-stage filter uses the GNSS pseudo range and Doppler after multipath correction as observation input;
the two-stage filter is carried out in a resolving unit of the integrated navigation chip, and the error of the MEMS sensor is corrected according to an estimated value generated by the second-stage filter; the clock error and the clock drift are fed back to the pseudo range and Doppler observed quantity of each satellite generated by the GNSS tracking loop, and the other errors of the pseudo range part except the multipath error are reduced;
in the first-stage filter, a one-dimensional filter is established according to each tracked satellite to form a filter group, each single filter takes multiple paths as a to-be-estimated quantity, the multiple paths are the offsets of true pseudo-ranges, and a mathematical model of the multipath is assumed to be a random constant; the difference value of the pseudo range obtained by IMU calculation and the GNSS pseudo range is the filter observation updating amount; the results of the multipath estimation for each satellite are used in a second stage filter;
1.1 establishing a one-dimensional filter to form a filter family according to each tracked satellite, wherein each single filter takes multipath as a to-be-estimated quantity;
assume that the multipath for each satellite has the following dynamic equation:
xk，i＝xk-1，i+vk，iwhere i denotes the ith tracked satellite, vk，iAssuming zero mean gaussian noise;
the filtered prediction can be expressed as: p is a radical ofk，i＝pk-1，i+qk，iWherein q isk，iTaking values for multipath dynamic noise according to actual modeling;
filtering of ith multipathk，iCan be expressed as:
sk，i＝hk，ipk，ihk，i+rk，i
wherein h isk，i，rk，iRespectively representing a filtered design matrix and observation noise;
the filter gain can be expressed as: m isk，i＝pk，i/sk，i
The observations of the filtered measurement update are: z is a radical ofk，i＝ρIMU，i-ρi
Where ρ isIMU，i、ρiCalculating a pseudo range of the ith satellite and an original pseudo range generated by the GNSS for the IMU respectively; the pseudoranges and doppler of the IMU can be derived from the following equations
Figure FDA0002974643640000011
(xI，yI，zI) Representing the position of the IMU, ECEF coordinate system; (x)s，i，ys，i，zs，i) Indicating the position of the ith satellite, ECEF coordinates;
1.2: correcting the original pseudo range of each satellite of the GNSS according to the result of the first step;
Figure FDA0002974643640000021
1.3: examination of rhoIMU，i、ρiAnd judging whether to continue to operate the filter of the satellite at the next moment according to the difference value, and resetting the multipath filtering of the satellite if the satellite tracking is discontinuous or the difference value is smaller than a threshold.
2. The method for multipath filtering in GNSS/MEMS inertial combined chip positioning algorithm according to claim 1, wherein:
and the second-stage filtering algorithm selects an error to be estimated as a state, and a 17-dimensional error state vector comprises a three-dimensional position error, a three-dimensional speed error, a three-dimensional attitude error, a three-axis accelerometer zero offset, a three-axis gyroscope zero offset, and a clock error and a clock drift of a receiver.
3. The method for multipath filtering in a GNSS/MEMS inertial combined chip positioning algorithm of claim 2, wherein a second stage combined navigation filter is established:
the combined filtering algorithm selects an error to be estimated as a state, and a 17-dimensional error state vector comprises a three-dimensional position error, a three-dimensional speed error, a three-dimensional attitude error, a three-axis accelerometer zero offset, a three-axis gyroscope zero offset, a clock error and a clock drift of a receiver;
using pseudoranges and doppler of satellites as filter observations
Then each pair of pseudorange and doppler observations is
Figure FDA0002974643640000022
Where ρ isIMU,fdopp-IMUPseudoranges and doppler, p, computed separately for the IMUi,fidopp-GPSThe pseudo range and Doppler measured value of the ith satellite are m represents m effective satellites;
where pseudorange and doppler of the IMU may be derived the following calculation
Figure FDA0002974643640000023
Figure FDA0002974643640000024
Wherein (v)INS,x,vINS,y,vINS,z) Representing the velocity of the IMU, ECEF coordinate system;
(vsv,xi,vsv,yi,vsv,zi) Representing the velocity, ECEF coordinate system, of the ith satellite; λ is the wavelength of the satellite signal;
(eix,eiy,eiz) Is the sight distance vector of the ith star;
its corresponding design matrix can be written as
Figure FDA0002974643640000031
Where E is a line-of-sight matrix consisting of line-of-sight vectors determined by the current estimated position and the satellite positions.
4. The method for multipath filtering in GNSS/MEMS inertial combined chip positioning algorithm of any of claims 1-3, wherein: and a step of feedback correction of sensor errors is also included.
5. The method for multipath filtering in GNSS/MEMS inertia combined chip positioning algorithm of claim 4, wherein: and a step of feeding back and correcting clock errors, namely removing clock error in the GNSS raw pseudorange at the next moment and clock drift in the GNSS raw Doppler.
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