CN108344415B - Combined navigation information fusion method - Google Patents

Combined navigation information fusion method Download PDF

Info

Publication number
CN108344415B
CN108344415B CN201810088309.9A CN201810088309A CN108344415B CN 108344415 B CN108344415 B CN 108344415B CN 201810088309 A CN201810088309 A CN 201810088309A CN 108344415 B CN108344415 B CN 108344415B
Authority
CN
China
Prior art keywords
navigation
gnss
sins
representing
combined navigation
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Active
Application number
CN201810088309.9A
Other languages
Chinese (zh)
Other versions
CN108344415A (en
Inventor
朱柏承
孟凡琛
牛尊
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Peking University
Original Assignee
Peking University
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Peking University filed Critical Peking University
Priority to CN201810088309.9A priority Critical patent/CN108344415B/en
Publication of CN108344415A publication Critical patent/CN108344415A/en
Application granted granted Critical
Publication of CN108344415B publication Critical patent/CN108344415B/en
Active legal-status Critical Current
Anticipated expiration legal-status Critical

Links

Images

Classifications

    • 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
    • G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
    • G01C21/00—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00
    • G01C21/10—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 by using measurements of speed or acceleration
    • G01C21/12—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 by using measurements of speed or acceleration executed aboard the object being navigated; Dead reckoning
    • G01C21/16—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 by using measurements of speed or acceleration executed aboard the object being navigated; Dead reckoning by integrating acceleration or speed, i.e. inertial navigation
    • G01C21/165—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 by using measurements of speed or acceleration executed aboard the object being navigated; Dead reckoning by integrating acceleration or speed, i.e. inertial navigation combined with non-inertial navigation instruments
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S19/00—Satellite radio beacon positioning systems; Determining position, velocity or attitude using signals transmitted by such systems
    • G01S19/01—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
    • G01S19/33—Multimode operation in different systems which transmit time stamped messages, e.g. GPS/GLONASS
    • 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

Landscapes

  • Engineering & Computer Science (AREA)
  • Radar, Positioning & Navigation (AREA)
  • Remote Sensing (AREA)
  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • Computer Networks & Wireless Communication (AREA)
  • Automation & Control Theory (AREA)
  • Position Fixing By Use Of Radio Waves (AREA)

Abstract

The invention discloses a combined navigation information fusion method which mainly comprises a GNSS satellite signal processing module, an SINS attitude speed position updating module, an SINS error compensation module, an SINS/GNSS information fusion module, an SINS error correction module and a result output module. The method comprises the steps of updating the position of the high-frequency SINS attitude speed and measuring the low-frequency GNSS innovation, adaptively adjusting an SINS/GNSS combined navigation Kalman filter observation noise matrix in real time by combining the elevation angle of each visible satellite tracked by a combined navigation receiver and the carrier-to-noise ratio of a navigation signal, updating a combined navigation Kalman filter state equation and an error covariance matrix by the GNSS, the SINS pseudo range and the pseudo range rate measurement value, and finally correcting the measurement error of an inertial device by the SINS and GNSS information fusion feedback. The integrated navigation information fusion method provided by the invention can realize complete robust information fusion calculation of the integrated navigation receiver in a complex electromagnetic environment, and has stronger design theoretical value and engineering application value of the integrated navigation receiver.

Description

Combined navigation information fusion method
Technical Field
The invention belongs to the technical field of satellite navigation, and particularly relates to a combined navigation information fusion method which can effectively improve the positioning accuracy of a strapdown inertial navigation and satellite navigation receiver.
Background
A Global Navigation Satellite System (GNSS) can provide positioning, Navigation and time service for a receiver, and plays an extremely important role in various industry fields. The global satellite navigation system mainly comprises a GPS in the United states, a BDS in China, GALILEO in Europe and GLONASS in Russia at present, and a signal processing end of a navigation receiver calculates the space position and the speed of a satellite according to Interface Control files (ICDs) of various navigation systems by extracting GNSS navigation messages, so that the positioning and resolving of the receiver are realized. An Inertial Navigation System (INS) is an autonomous dead reckoning Navigation System that determines carrier attitude, velocity, and position using Inertial sensors (gyroscopes and accelerometers), a reference azimuth, and initial position attitude information. The Inertial Navigation systems are classified into a Platform Inertial Navigation System (PINS) and a Strapdown Inertial Navigation System (SINS). The PINS is used for installing a gyroscope and an accelerometer on a solid stable platform and measuring a navigation system of the motion parameters of the carrier by using a platform coordinate system as a reference; SINS mounts gyroscopes and accelerometers directly on a carrier, without the need for a physical platform, with platform alignment done by a processor. The PINS has large volume, heavy mass, complex mechanical structure, poor reliability and maintainability, the system performance is restricted by the inertial sensor, and the system cost is very expensive. The SINS has the advantages of short reaction time, small volume, light weight, simple structure, capability of effectively improving the precision and reliability of the system through proper redundant configuration, autonomy, concealment, interference resistance, continuity, completeness and the like. However, the SINS error is accumulated and increased with time, and usually, the micro-mechanical gyroscope and the accelerometer can reach an error of "hundred seconds and hundred meters", so that the SINS and the GNSS are often complemented in advantages, and the method has a wide application prospect.
Aiming at the situation that the measurement noise in the traditional integrated navigation system is counted roughly and cannot be timely used for the complex electromagnetic environment or the violent change of the mobile carrier, the invention provides the integrated navigation information fusion method which can effectively solve the problem of the reduction of the filtering precision and even the Kalman filtering divergence caused by the violent motion of the mobile carrier and is a new technical requirement at present.
Disclosure of Invention
Technical problem to be solved
In order to solve the problems in the prior art, the invention provides a combined navigation information fusion method which mainly comprises the steps of GNSS navigation message extraction, GNSS navigation signal carrier-to-noise ratio calculation, receiver visible satellite elevation calculation, SINS attitude speed position updating, SINS/GNSS combined navigation Kalman filter design, measurement noise adaptive design and the like.
(II) technical scheme
The invention provides a combined navigation information fusion method, which mainly comprises the following steps:
step 1: the combined navigation receiver carries out down-conversion, capturing and tracking and data synchronization processing on the GNSS satellite signals, and extracts GNSS navigation messages;
step 2: acquiring coherent integration values of in-phase and orthogonal branches through a GNSS signal processing loop, and extracting a GNSS navigation signal carrier-to-noise ratio;
and step 3: calculating the space position and the speed of the visible satellite through the GNSS navigation message and the visible satellite signal emission time, and calculating the elevation angle of the visible satellite according to the position of the combined navigation receiver;
and 4, step 4: updating SINS attitude, speed and position information through SINS gyroscope and accelerometer measurement values;
and 5: designing a state transition matrix and a measurement equation of the integrated navigation Kalman filter through an SINS attitude, speed, position, error propagation model and a GNSS clock error model;
step 6: and designing and measuring a noise matrix through the carrier-to-noise ratio and the elevation angle of the GNSS navigation signal, and performing Kalman filtering updating, SINS error correction and result output.
Preferably, the GNSS in step 1 is GPS.
Optionally, the GNSS in step 1 may be GPS, BDS, GALILEO, or any combination of the three.
Optionally, if the GNSS in step 1 is combined by GLONASS and GPS/BDS/GALILEO, the GPS uses WGS-84 coordinate system, the GALILEO uses GTRF coordinate system, and the BDS uses CGCS2000 coordinate system, and the origins and coordinate axes of the three coordinate systems are substantially the same, and the error between the coordinate systems is very small and can be ignored under non-precise positioning; GLONASS adopts PZ-90 coordinate system, and needs coordinate conversion with GPS/BDS/GALILEO.
Preferably, in step 2, the GNSS navigation signal carrier-to-noise ratio is calculated by a narrow-wide power ratio method in a navigation message data bit period τaNIn the method, coherent accumulation narrowband power P is calculatedNSum non-coherent accumulated wideband power PWThe calculation formula is as follows:
Figure BDA0001563013200000031
Figure BDA0001563013200000032
wherein, the navigation message data bit period tauaNDivided into N segments, each segment having a time of
Figure BDA0001563013200000033
Number of points of coherent integration time M, IP,iAnd QP,iAre each tauaWAccumulated value over time. Then, the power ratio is calculated, and after n times of accumulation, the average value is taken to reduce noise, and the formula is as follows:
Figure BDA0001563013200000034
the carrier-to-noise power density ratio measurements are:
Figure BDA0001563013200000035
finally, the GNSS navigation signal carrier to noise ratio is:
Figure BDA0001563013200000036
wherein lg represents a base-10 logarithmic operation.
Preferably, in step 2,. tau.aWIs the time for 1ms, and the time for the second time,
Figure BDA0001563013200000037
the average time was 1 s.
Preferably, in step 3, the spatial position and the velocity of the visible satellite are calculated by using the GNSS navigation message and the visible satellite signal transmission time, where the visible satellite signal transmission time is the visible satellite signal transmission time constructed by combining the navigation receiver signal processing tracking loop, and specifically includes the current subframe week inner second, the number of navigation message data code words, the navigation message bit number of the current navigation message data code words, the number of code pieces of the current navigation message bit number, and the phase of the current navigation message code piece.
Preferably, in step 3, the position and the speed of the visible satellite in the geocentric geostationary coordinate system are calculated through the GNSS navigation message and the visible satellite signal emission time according to the official ICD interface document of each satellite navigation system, and the visible satellite elevation angle is calculated according to the position of the combined navigation receiver.
Preferably, the SINS pose, velocity and position information is updated in step 4 by a quadtype method.
Optionally, the update frequency of the SINS in the step 4 is 20-100 Hz.
Preferably, the updating of the attitude of the strapdown inertial navigation system in the step 4 is performed by a quaternion method.
Optionally, the attitude updating algorithm of the strapdown inertial navigation system in the step 4 may adopt a direction cosine method or an euler angle method.
Preferably, the SINS attitude error propagation model in step 5 is:
Figure BDA0001563013200000041
wherein the content of the first and second substances,
Figure BDA0001563013200000042
and is the attitude error under the SINS navigation coordinate system, "×" represents the matrix cross product,
Figure BDA0001563013200000043
the projection of the rotational angular velocity of the earth relative to the rotational angular velocity of the earth system in a navigation coordinate system is obtained;
Figure BDA0001563013200000044
for rotation of the navigational system relative to the terrestrial systemProjection of the dynamic angular velocity in a navigation coordinate system; δ represents the vector differential;
Figure BDA0001563013200000045
representing a matrix of strapdowns,
Figure BDA0001563013200000046
representing the amount of attitude noise in the carrier coordinate system,
Figure BDA0001563013200000047
the superscript "." denotes the differential, and the same reference signs used in the following text represent the same meanings.
Preferably, the SINS velocity error propagation model in step 5 is:
Figure BDA0001563013200000048
wherein the content of the first and second substances,
Figure BDA0001563013200000049
representing specific force measurements made by the accelerometer in the navigational coordinate system,
Figure BDA00015630132000000410
representing the specific force measurement noise amount in the carrier coordinate system.
Preferably, the SINS position error propagation model in step 5 is:
Figure BDA00015630132000000411
wherein, (L, lambda, h) represents the latitude, longitude and elevation of SINS, and RMRepresents the radius of the meridian, RNRepresenting the radius of the unitary mortise ring.
Preferably, the GNSS clock difference model in step 5 is:
Figure BDA00015630132000000412
Figure BDA00015630132000000413
wherein, bclkRepresenting combined navigation receiver clock error, omegabRepresenting combined navigation receiver clock error noise, dclkRepresenting combined navigation receiver frequency drift, omegadRepresenting combined navigation receiver frequency drift noise, TclkRepresenting the clock relative time.
Preferably, the state transition matrix of the integrated navigation kalman filter in step 5 is:
Figure BDA0001563013200000051
wherein, FSINS/CNSSRepresents the combined navigation Kalman filter state transition matrix, wherein 03×30 matrix representing 3 rows and 3 columns, 03×20 matrix representing 3 rows and 2 columns, 02×3Represents a 0 matrix of 2 rows and 3 columns, and
Figure BDA0001563013200000052
M13＝M′+M″
wherein the content of the first and second substances,
Figure BDA0001563013200000053
Figure BDA0001563013200000054
M23＝(vn×)(2M′+M″)
Figure BDA0001563013200000055
Figure BDA0001563013200000056
preferably, the measurement equation of the integrated navigation kalman filter in step 5 is divided into a pseudorange measurement equation and a pseudorange rate measurement equation.
Preferably, the pseudorange measurement equation in step 5 is as follows:
Figure BDA0001563013200000057
wherein, deltaρRepresenting a pseudo range obtained by SINS measurement and a pseudo range difference vector obtained by GNSS measurement; li,mi,ni(i ═ 1,2 … N) represents the direction cosine matrix of the ith visible satellite, δxRepresenting the position error of the x axis of the combined navigation receiver under the geocentric geostationary coordinate system; deltayRepresenting the y-axis position error of the combined navigation receiver under the geocentric geostationary coordinate system; deltazRepresenting the position error of the combined navigation receiver on the z axis under the geocentric geostationary coordinate system; bclkRepresenting the clock error of the combined navigation receiver,
Figure BDA0001563013200000061
representing the pseudorange difference noise figure for the ith satellite.
Preferably, the pseudorange rate measurement equation in step 5 is as follows:
Figure BDA0001563013200000062
wherein the content of the first and second substances,
Figure BDA0001563013200000063
representing a pseudo range rate obtained by SINS measurement and a pseudo range difference vector obtained by GNSS measurement;
Figure BDA0001563013200000064
representing the x-axis speed error of the combined navigation receiver under the geocentric geostationary coordinate system;
Figure BDA0001563013200000065
representing the y-axis speed error of the combined navigation receiver under the geocentric geostationary coordinate system;
Figure BDA0001563013200000066
representing the z-axis speed error of the combined navigation receiver under the geocentric geostationary coordinate system; dclkRepresenting the frequency drift of the combined navigation receiver,
Figure BDA0001563013200000067
representing the pseudorange delta noise magnitude for the ith satellite.
Preferably, the measured noise matrix designed by the carrier-to-noise ratio and the elevation angle of the GNSS navigation signal in step 6 is as follows:
Figure BDA0001563013200000068
wherein, R represents a measurement noise matrix,
Figure BDA0001563013200000069
represents the square of the elevation of the ith satellite in view, ReferCN0Representing a reference carrier-to-noise ratio of the combined navigation receiver; (C/N)0)i(i-1, 2 … N) represents the carrier to noise ratio at the elevation angle of the ith visible satellite.
(III) advantageous effects
The integrated navigation information fusion method provided by the invention can produce positive beneficial effects, the method can adaptively adjust the observation noise distribution of the SINS/GNSS integrated navigation filter in real time by combining the space distribution of visible satellites and the intensity of navigation signals through the high-frequency SINS attitude speed position updating and the low-frequency GNSS innovation measurement, and timely updates the integrated navigation Kalman filter and corrects the measurement error of an SINS inertial device, can realize complete and robust information fusion resolving of the integrated navigation receiver in a complex electromagnetic environment, and has strong design theoretical value and engineering application value of the integrated navigation receiver.
Drawings
FIG. 1 is a schematic diagram of an integrated navigation information fusion module according to a preferred embodiment of the present invention;
fig. 2 shows a flow chart of the integrated navigation information fusion method according to the preferred embodiment of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention will be described in further detail with reference to the accompanying drawings in conjunction with the following detailed description. It should be understood that the description is intended to be exemplary only, and is not intended to limit the scope of the present invention. Moreover, in the following description, descriptions of well-known structures and techniques are omitted so as to not unnecessarily obscure the concepts of the present invention.
Fig. 1 shows a schematic diagram of a combined navigation information fusion module according to a preferred embodiment of the present invention.
As shown in FIG. 1, the integrated navigation information fusion module of the preferred embodiment of the present invention mainly comprises a GNSS satellite signal processing module M1, an SINS attitude velocity and position updating module M2, an SINS error compensation module M3, an SINS/GNSS information fusion module M4, an SINS error correction module M5 and a result output module M6. The GNSS satellite signal processing module M1 extracts a GNSS satellite signal navigation message through capturing, tracking, bit synchronization, and frame synchronization operations in the GNSS satellite signal processing process, which takes GPS as an example in the specific embodiment of the present invention. After a GNSS receiver tracking channel acquires a navigation message of a tracked satellite, calculating the carrier-to-noise ratio of the tracked visible satellite signal by adopting a narrow-wide power ratio method. The SINS attitude velocity position update module M2 obtains the angular velocity and specific force measurement values through the inertial measurement unit gyroscope and accelerometer of the SINS, and follows the new SINS attitude velocity position information, before that, an accurate initial position and attitude of the SINS are needed to be given, and the strapdown inertial navigation coarse alignment and fine alignment operations are performed. The SINS error compensation module M3 corrects the attitude velocity and position errors through a two-subsampled or four-subsampled algorithm, which is used in the preferred embodiment of the present invention. The SINS/GNSS information fusion module M4 obtains the position, speed, elevation angle, carrier-to-noise ratio, pseudo range and pseudo range rate information of the visible satellite through the GNSS, the SINS obtains the pseudo range and pseudo range rate information of the satellite, and performs state transition matrix calculation, measurement noise matrix calculation, combined navigation Kalman filtering state equation and error covariance matrix updating according to the strapdown inertial navigation system error propagation model. The SINS error correction module M5 feeds back the state error amount calculated by the SINS/GNSS information fusion module M4 to the SINS, and performs SINS state error correction. In the result output module M6, the SINS update frequency is faster, which can generally reach 50Hz, and the SINS/GNSS information fusion frequency is lower, which is generally 10Hz, so the SINS update frequency and the SINS/GNSS fusion frequency are adjusted according to the actual requirement of the integrated navigation receiver, and the result after the SINS error correction is output.
Fig. 2 shows a flow chart of the integrated navigation information fusion method according to the preferred embodiment of the present invention.
As shown in fig. 2, the flowchart of the integrated navigation information fusion method according to the preferred embodiment of the present invention mainly includes the following steps:
step 1: the combined navigation receiver carries out down-conversion, capturing and tracking and data synchronization processing on the GNSS satellite signals, and extracts GNSS navigation messages;
step 2: acquiring coherent integration values of in-phase and orthogonal branches through a GNSS signal processing loop, and extracting a GNSS navigation signal carrier-to-noise ratio;
and step 3: calculating the space position and the speed of the visible satellite through the GNSS navigation message and the visible satellite signal emission time, and calculating the elevation angle of the visible satellite according to the position of the combined navigation receiver;
and 4, step 4: updating SINS attitude, speed and position information through SINS gyroscope and accelerometer measurement values;
and 5: designing a state transition matrix and a measurement equation of the integrated navigation Kalman filter through an SINS attitude, speed, position, error propagation model and a GNSS clock error model;
step 6: and designing and measuring a noise matrix through the carrier-to-noise ratio and the elevation angle of the GNSS navigation signal, and performing Kalman filtering updating, SINS error correction and result output.
In the embodiment of the present invention, the GNSS in step 1 is a GPS.
In the step 2, the GNSS navigation signal carrier-to-noise ratio is calculated by adopting a narrow-wide power ratio method, and in the navigation message data bit period tauaNIn the method, coherent accumulation narrowband power P is calculatedNSum non-coherent accumulated wideband power PWThe calculation formula is as follows:
Figure BDA0001563013200000081
Figure BDA0001563013200000082
wherein, the navigation message data bit period tauaNDivided into N segments, each segment having a time of
Figure BDA0001563013200000083
Number of points of coherent integration time M, IP,iAnd QP,iAre each tauaWAccumulated value over time. Then, the power ratio is calculated, and after n times of accumulation, the average value is taken to reduce noise, and the formula is as follows:
Figure BDA0001563013200000084
the carrier-to-noise power density ratio measurements are:
Figure BDA0001563013200000091
finally, the GNSS navigation signal carrier to noise ratio is:
Figure BDA0001563013200000092
wherein lg represents a base-10 logarithmic operation.
In step 2 τaWIs the time for 1ms, and the time for the second time,
Figure BDA0001563013200000093
the average time was 1 s.
Step 3 said navigation message and visible satellite signal emission time meter by GNSSCalculating the space position and the speed of a visible satellite, wherein the visible satellite signal transmission time is the visible satellite signal transmission time constructed by combining a signal processing and tracking loop of a navigation receiver, and specifically comprises second TOW in the current subframe period, the number omega of navigation message data code words, the navigation message bit number b of the current navigation message data code words, the chip number C of the current navigation message bit number and the phase CP of the current navigation message chips(unit: second) the formula is constructed as follows:
Figure BDA0001563013200000094
and 3, calculating the position and the speed of the visible satellite under the geocentric geostationary coordinate system according to the GNSS navigation message and the visible satellite signal emission time ts and according to official ICD interface documents of each satellite navigation system, and calculating the elevation angle of the visible satellite according to the position of the combined navigation receiver.
And step 4, updating the SINS attitude, speed and position information by a four-subsample method.
The SINS update frequency in step 4 is 50 Hz.
And 4, updating the attitude of the strapdown inertial navigation system by a quaternion method.
The SINS attitude error propagation model in the step 5 is as follows:
Figure BDA0001563013200000095
wherein the content of the first and second substances,
Figure BDA0001563013200000096
and is the attitude error under the SINS navigation coordinate system, "×" represents the matrix cross product,
Figure BDA0001563013200000097
the projection of the rotational angular velocity of the earth relative to the rotational angular velocity of the earth system in a navigation coordinate system is obtained;
Figure BDA0001563013200000098
is the projection of the rotation angular speed of the navigation system relative to the earth system in a navigation coordinate system; δ represents the vector differential;
Figure BDA0001563013200000099
representing a matrix of strapdowns,
Figure BDA00015630132000000910
representing the amount of attitude noise in the carrier coordinate system,
Figure BDA0001563013200000101
the superscript ". indicates the differential.
The SINS velocity error propagation model in the step 5 is as follows:
Figure BDA0001563013200000102
wherein the content of the first and second substances,
Figure BDA0001563013200000103
representing specific force measurements made by the accelerometer in the navigational coordinate system,
Figure BDA0001563013200000104
representing the specific force measurement noise amount in the carrier coordinate system.
The SINS position error propagation model in the step 5 is as follows:
Figure BDA0001563013200000105
wherein, (L, lambda, h) represents the latitude, longitude and elevation of SINS, and RMRepresents the radius of the meridian, RNRepresenting the radius of the unitary mortise ring.
In step 5, the GNSS clock error model is:
Figure BDA0001563013200000106
Figure BDA0001563013200000107
wherein, bclkRepresenting combined navigation receiver clock error, omegabRepresenting combined navigation receiver clock error noise, dclkRepresenting combined navigation receiver frequency drift, omegadRepresenting combined navigation receiver frequency drift noise, TclkRepresenting the clock relative time.
The state transition matrix of the integrated navigation Kalman filter in the step 5 is as follows:
Figure BDA0001563013200000108
wherein, 03×30 matrix representing 3 rows and 3 columns, 03×20 matrix representing 3 rows and 2 columns, 02×3Represents a 0 matrix of 2 rows and 3 columns, and
Figure BDA0001563013200000109
M13＝M′+M″
wherein the content of the first and second substances,
Figure BDA0001563013200000111
Figure BDA0001563013200000112
M23＝(vn×)(2M′+M″)
Figure BDA0001563013200000113
Figure BDA0001563013200000114
and 5, dividing the measurement equation of the integrated navigation Kalman filter into a pseudo-range measurement equation and a pseudo-range rate measurement equation. The pseudorange measurement equation is as follows:
Figure BDA0001563013200000115
wherein, deltaρRepresenting a pseudo range obtained by SINS measurement and a pseudo range difference vector obtained by GNSS measurement; li,mi,ni(i ═ 1,2 … N) represents the direction cosine matrix of the ith visible satellite, δxRepresenting the position error of the x axis of the combined navigation receiver under the geocentric geostationary coordinate system; deltayRepresenting the y-axis position error of the combined navigation receiver under the geocentric geostationary coordinate system; deltazRepresenting the position error of the combined navigation receiver on the z axis under the geocentric geostationary coordinate system; bclkRepresenting the clock error of the combined navigation receiver,
Figure BDA0001563013200000116
representing the pseudorange difference noise figure for the ith satellite.
The pseudorange rate measurement equation in step 5 is as follows:
Figure BDA0001563013200000117
wherein the content of the first and second substances,
Figure BDA0001563013200000118
representing a pseudo range rate obtained by SINS measurement and a pseudo range difference vector obtained by GNSS measurement;
Figure BDA0001563013200000119
representing the x-axis speed error of the combined navigation receiver under the geocentric geostationary coordinate system;
Figure BDA00015630132000001110
representing the y-axis speed error of the combined navigation receiver under the geocentric geostationary coordinate system;
Figure BDA00015630132000001111
representing the z-axis speed error of the combined navigation receiver under the geocentric geostationary coordinate system; dclkRepresenting the frequency drift of the combined navigation receiver,
Figure BDA0001563013200000121
representing the pseudorange delta noise magnitude for the ith satellite.
The measurement noise matrix designed by the carrier-to-noise ratio and the elevation angle of the GNSS navigation signal in step 6 is as follows:
Figure BDA0001563013200000122
wherein the content of the first and second substances,
Figure BDA0001563013200000123
represents the square of the elevation of the ith satellite in view, ReferCN0The reference carrier-to-noise ratio of the combined navigation receiver is represented, and is 45dB & Hz in the specific embodiment of the invention; (C/N)0)i(i-1, 2 … N) represents the carrier to noise ratio at the elevation angle of the ith visible satellite.
In the step 6, the update frequency of the SINS/GNSS integrated navigation information fusion Kalman filter is 10Hz, and after each update, the SINS is subjected to error correction and result output.
In summary, the present invention provides a combined navigation information fusion method. According to the method, the SINS/GNSS combined navigation Kalman filter observation noise is adaptively adjusted in real time through high-frequency SINS attitude speed position updating and low-frequency GNSS innovation measurement in combination with the space distribution and navigation signal carrier-to-noise ratio of each visible satellite tracked by the combined navigation receiver, the state equation and the error covariance matrix of the combined navigation Kalman filter are updated through the GNSS, the SINS pseudo range and the pseudo range rate measurement value, the inertial device measurement error is corrected through SINS and GNSS information fusion feedback, complete robust information fusion resolving of the combined navigation receiver in a complex electromagnetic environment can be achieved, and the combined navigation receiver has high design theoretical value and engineering application value. It is to be understood that the above-described embodiments of the present invention are merely illustrative of or explaining the principles of the invention and are not to be construed as limiting the invention. Therefore, any modifications and the like made without departing from the spirit and scope of the present invention shall be included in the protection scope of the present invention. It is intended that the appended claims cover all such variations and modifications as fall within the scope and boundaries of the appended claims or the equivalents of such scope and boundaries.

Claims (9)

1. A method for fusing combined navigation information is characterized by comprising the following steps:
step 1: the combined navigation receiver carries out down-conversion, capturing and tracking and data synchronization processing on the GNSS satellite signals, and extracts GNSS navigation messages;
step 2: acquiring coherent integration values of in-phase and orthogonal branches through a GNSS signal processing loop, and extracting a GNSS navigation signal carrier-to-noise ratio;
and step 3: calculating the space position and the speed of the visible satellite through the GNSS navigation message and the visible satellite signal emission time, and calculating the elevation angle of the visible satellite according to the position of the combined navigation receiver;
and 4, step 4: updating SINS attitude, speed and position information through SINS gyroscope and accelerometer measurement values;
and 5: designing a state transition matrix and a measurement equation of the integrated navigation Kalman filter through an SINS attitude, speed, position, error propagation model and a GNSS clock error model;
step 6: designing and measuring a noise matrix through a GNSS navigation signal carrier-to-noise ratio and an elevation angle, and performing Kalman filtering updating, SINS error correction and result output;
wherein, the state transition matrix of the integrated navigation kalman filter in step 5 is:
Figure FDA0002991163910000011
wherein, FSINS/GNSSRepresenting the State transition matrix of the Combined navigation Kalman Filter, 03×30 matrix representing 3 rows and 3 columns, 03×20 matrix representing 3 rows and 2 columns, 02×3Represents a 0 matrix of 2 rows and 3 columns, and
Figure FDA0002991163910000012
M13＝M′+M″
wherein the content of the first and second substances,
Figure FDA0002991163910000013
Figure FDA0002991163910000014
M23＝(vn×)(2M′+M″)
Figure FDA0002991163910000021
Figure FDA0002991163910000022
wherein the content of the first and second substances,
Figure FDA0002991163910000023
(L, λ, h) represents the latitude, longitude and elevation of the SINS, RMRepresents the radius of the meridian, RNRepresenting radius of unitclkRepresenting the clock correlation time, and dividing the measurement equation of the integrated navigation Kalman filter in the step 5 into a pseudo-range measurement equation and a pseudo-range rate measurement equation; the pseudorange measurement equation is as follows:
Figure FDA0002991163910000024
wherein, δ ρ represents a pseudorange obtained by SINS measurement and a pseudorange difference vector obtained by GNSS measurement; li，mi，niThe direction cosine matrixes of the ith visible satellite are respectively represented, i is 1, 2.. N, and deltax represents the position error of the x axis of the combined navigation receiver under the geocentric geostationary coordinate system; delta y represents the y-axis position error of the combined navigation receiver under the geocentric geostationary coordinate system; δ z represents the position error of the combined navigation receiver on the z axis under the geocentric geostationary coordinate system; bclkRepresenting combined navigation receiver clock error, thetaρiRepresenting the pseudo range difference noise amount of the ith satellite; the pseudorange rate measurement equation is as follows:
Figure FDA0002991163910000025
wherein the content of the first and second substances,
Figure FDA0002991163910000026
representing a pseudo range rate obtained by SINS measurement and a pseudo range difference vector obtained by GNSS measurement;
Figure FDA0002991163910000027
representing the x-axis speed error of the combined navigation receiver under the geocentric geostationary coordinate system;
Figure FDA0002991163910000028
representing the y-axis speed error of the combined navigation receiver under the geocentric geostationary coordinate system;
Figure FDA0002991163910000029
representing the z-axis speed error of the combined navigation receiver under the geocentric geostationary coordinate system; dclkRepresenting the frequency drift of the combined navigation receiver,
Figure FDA00029911639100000210
representing the pseudorange delta noise magnitude for the ith satellite.
2. The combined navigation information fusion method according to claim 1, wherein: the GNSS in the step 1 is GPS or BDS or GALILEO or any combination of the three.
3. The combined navigation information fusion method according to claim 2, wherein: the GNSS adopts GLONASS and GPS/BDS/GALILEO to combine, the GPS adopts a WGS-84 coordinate system, the GALILEO adopts a GTRF coordinate system, the BDS adopts a CGCS2000 coordinate system, the origin and the coordinate axis of the coordinate systems are basically consistent, and the GLONASS adopts a PZ-90 coordinate system and needs to perform coordinate conversion with the GPS/BDS/GALILEO.
4. The combined navigation information fusion method according to claim 1, wherein: in the step 2, the GNSS navigation signal carrier-to-noise ratio is calculated by adopting a narrow-wide power ratio method, and in the navigation message data bit period tauaNIn the method, coherent accumulation narrowband power P is calculatedNSum non-coherent accumulated wideband power PWThe calculation formula is as follows:
Figure FDA0002991163910000031
Figure FDA0002991163910000032
wherein, the navigation message data bit period tauaNDivided into N segments, each segment having a time of
Figure FDA0002991163910000033
Number of points of coherent integration time M, IP，iAnd QP，iAre all tauaWAccumulated value in time, and then power ratio is calculatedAfter n accumulations, the average is taken to reduce noise, and the formula is:
Figure FDA0002991163910000034
the carrier-to-noise power density ratio measurements are:
Figure FDA0002991163910000035
finally, the GNSS navigation signal carrier to noise ratio is:
Figure FDA0002991163910000036
wherein lg represents a base-10 logarithmic operation.
5. The combined navigation information fusion method according to claim 1, wherein: calculating the space position and the speed of the visible satellite through the GNSS navigation message and the visible satellite signal emission time in the step 3, wherein the visible satellite signal emission time is the visible satellite signal emission time constructed by combining a signal processing and tracking loop of the navigation receiver, and specifically comprises the current subframe week number of seconds, the number of navigation message data code words, the navigation message bit number of the current navigation message data code words, the number of code pieces of the current navigation message bit number and the phase of the current navigation message code pieces; and further, calculating the position and the speed of the visible satellite under the geocentric geostationary coordinate system according to the GNSS navigation message and the visible satellite signal emission time and according to official ICD interface documents of each satellite navigation system, and calculating the visible satellite elevation according to the position of the combined navigation receiver.
6. The combined navigation information fusion method according to claim 1, wherein: and step 4, updating the SINS attitude, speed and position information by a four-subsample method.
7. The combined navigation information fusion method according to claim 1, wherein: the SINS attitude error propagation model in the step 5 is as follows:
Figure FDA0002991163910000041
wherein the content of the first and second substances,
Figure FDA0002991163910000042
and is the attitude error under the SINS navigation coordinate system, "×" represents the matrix cross product,
Figure FDA0002991163910000043
Figure FDA0002991163910000044
the projection of the rotational angular velocity of the earth relative to the rotational angular velocity of the earth system in a navigation coordinate system is obtained;
Figure FDA0002991163910000045
is the projection of the rotation angular speed of the navigation system relative to the earth system in a navigation coordinate system; δ represents the vector differential;
Figure FDA0002991163910000046
representing a matrix of strapdowns,
Figure FDA0002991163910000047
representing the amount of attitude noise in the carrier coordinate system,
Figure FDA0002991163910000048
superscript "-" represents differential;
the SINS velocity error propagation model is:
Figure FDA0002991163910000049
wherein the content of the first and second substances,
Figure FDA00029911639100000410
Figure FDA00029911639100000411
representing specific force measurements made by the accelerometer in the navigational coordinate system,
Figure FDA00029911639100000412
representing specific force measurement noise amount under a carrier coordinate system;
the SINS position error propagation model is as follows:
Figure FDA00029911639100000413
wherein, (L, lambda, h) represents the latitude, longitude and elevation of SINS, and RMRepresents the radius of the meridian, RNRepresenting the radius of the unitary mortise ring.
8. The combined navigation information fusion method according to claim 1, wherein: in step 5, the GNSS clock error model is:
Figure FDA00029911639100000414
Figure FDA00029911639100000415
wherein, bclkRepresenting combined navigation receiver clock error, omegabRepresenting combined navigation receiver clock error noise, dclkRepresenting combined navigation receiver frequency drift, omegadRepresenting combined navigation receiver frequency drift noise, TclkRepresenting the clock relative time.
9. The combined navigation information fusion method according to claim 1, wherein: the measurement noise matrix designed by the carrier-to-noise ratio and the elevation angle of the GNSS navigation signal in step 6 is as follows:
Figure FDA0002991163910000051
wherein, R represents a measurement noise matrix,
Figure FDA0002991163910000052
represents the square of the elevation of the ith satellite in view, ReferCN0Representing a reference carrier-to-noise ratio of the combined navigation receiver; (C/N)0)iThe carrier-to-noise ratio representing the elevation angle of the ith visible satellite.
CN201810088309.9A 2018-01-30 2018-01-30 Combined navigation information fusion method Active CN108344415B (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN201810088309.9A CN108344415B (en) 2018-01-30 2018-01-30 Combined navigation information fusion method

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN201810088309.9A CN108344415B (en) 2018-01-30 2018-01-30 Combined navigation information fusion method

Publications (2)

Publication Number Publication Date
CN108344415A CN108344415A (en) 2018-07-31
CN108344415B true CN108344415B (en) 2021-06-04

Family

ID=62960796

Family Applications (1)

Application Number Title Priority Date Filing Date
CN201810088309.9A Active CN108344415B (en) 2018-01-30 2018-01-30 Combined navigation information fusion method

Country Status (1)

Country Link
CN (1) CN108344415B (en)

Families Citing this family (10)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN109613568B (en) * 2018-11-21 2023-04-14 中国航空工业集团公司西安飞行自动控制研究所 Method for estimating measurement noise of frequency discriminator of satellite navigation receiver
CN109341684A (en) * 2018-11-29 2019-02-15 北京七维航测科技股份有限公司 Combined inertial nevigation equipment
CN109945870B (en) * 2019-03-11 2022-12-06 东南大学 Pseudo-satellite indoor positioning method with pseudo-range observed value and carrier-to-noise ratio fused
CN110133700B (en) * 2019-05-27 2023-01-31 上海海事大学 Shipborne integrated navigation positioning method
CN110988951A (en) * 2019-12-06 2020-04-10 中国地质大学（北京） Multi-source data fusion real-time navigation positioning method and system
CN111999747B (en) * 2020-08-28 2023-06-20 大连海事大学 Robust fault detection method for inertial navigation-satellite integrated navigation system
CN112946711B (en) * 2021-01-29 2022-11-25 中国人民解放军国防科技大学 Navigation method of GNSS/INS integrated navigation system
CN113703026B (en) * 2021-10-28 2022-02-08 中国商用飞机有限责任公司 Method and system for navigation mode selection for an aircraft
CN114167858B (en) * 2021-11-12 2022-11-11 广州文远知行科技有限公司 Navigation control method and device for vehicle, navigation controller and vehicle control system
CN116047551B (en) * 2023-04-03 2023-06-13 江苏北斗信创科技发展有限公司 Navigation simulation test system based on wireless signal transmission

Citations (7)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN103487820A (en) * 2013-09-30 2014-01-01 东南大学 Vehicle-mounted strapdown/satellite tight-combination seamless navigation method
CN104635251A (en) * 2013-11-08 2015-05-20 中国地质大学（北京） Novel INS (inertial navigation system)/ GPS (global position system) combined position and orientation method
CN104697520A (en) * 2015-02-05 2015-06-10 南京航空航天大学 Combined navigation method based on integrated gyroscope free strapdown inertial navigation system and GPS
CN104849735A (en) * 2015-05-27 2015-08-19 中国科学院嘉兴微电子与系统工程中心 Combined navigation receiver frequency false lock detection device and method
CN105137461A (en) * 2015-09-01 2015-12-09 中国人民解放军63655部队 Method for eliminating medium time delay of navigation positioning satellite system
CN106501832A (en) * 2016-12-16 2017-03-15 南京理工大学 A kind of fault-tolerant vector tracking GNSS/SINS deep integrated navigation methods
CN106980130A (en) * 2017-03-03 2017-07-25 哈尔滨工程大学 A kind of SINS/GNSS deep combinations adaptive navigation method

Family Cites Families (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
FR3018121B1 (en) * 2014-02-28 2016-02-12 Thales Sa METHOD FOR TRACKING A TRANSFER ORBIT OR A PHASE FOR ORKING A SPATIAL VEHICLE, IN PARTICULAR AN ELECTRICAL PROPULSION, AND APPARATUS FOR IMPLEMENTING SUCH A METHOD

Patent Citations (7)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN103487820A (en) * 2013-09-30 2014-01-01 东南大学 Vehicle-mounted strapdown/satellite tight-combination seamless navigation method
CN104635251A (en) * 2013-11-08 2015-05-20 中国地质大学（北京） Novel INS (inertial navigation system)/ GPS (global position system) combined position and orientation method
CN104697520A (en) * 2015-02-05 2015-06-10 南京航空航天大学 Combined navigation method based on integrated gyroscope free strapdown inertial navigation system and GPS
CN104849735A (en) * 2015-05-27 2015-08-19 中国科学院嘉兴微电子与系统工程中心 Combined navigation receiver frequency false lock detection device and method
CN105137461A (en) * 2015-09-01 2015-12-09 中国人民解放军63655部队 Method for eliminating medium time delay of navigation positioning satellite system
CN106501832A (en) * 2016-12-16 2017-03-15 南京理工大学 A kind of fault-tolerant vector tracking GNSS/SINS deep integrated navigation methods
CN106980130A (en) * 2017-03-03 2017-07-25 哈尔滨工程大学 A kind of SINS/GNSS deep combinations adaptive navigation method

Non-Patent Citations (1)

* Cited by examiner, † Cited by third party
Title
GNSS接收机矢量跟踪算法研究综述;程俊仁 等;《宇航学报》;20140428;第35卷(第04期);第380-387页 *

Also Published As

Publication number Publication date
CN108344415A (en) 2018-07-31

Similar Documents

Publication Publication Date Title
CN108344415B (en) Combined navigation information fusion method
Han et al. Integrated GPS/INS navigation system with dual-rate Kalman Filter
Noureldin et al. Fundamentals of inertial navigation, satellite-based positioning and their integration
CN101743453B (en) Post-mission high accuracy position and orientation system
US8447517B2 (en) Tightly-coupled GNSS/IMU integration filter having speed scale-factor and heading bias calibration
US20110238308A1 (en) Pedal navigation using leo signals and body-mounted sensors
CN109313272B (en) Improved GNSS receiver using velocity integration
CN108931791B (en) System and method for correcting satellite inertial force combined clock difference
CN113203418B (en) GNSSINS visual fusion positioning method and system based on sequential Kalman filtering
Yang et al. GPS-based onboard real-time orbit determination for LEO satellites using consider Kalman filter
Gao et al. Odometer, low-cost inertial sensors, and four-GNSS data to enhance PPP and attitude determination
Oh et al. Low-cost and high performance ultra-tightly coupled GPS/INS integrated navigation method
Li et al. A low-cost attitude heading reference system by combination of GPS and magnetometers and MEMS inertial sensors for mobile applications
WO2020226862A2 (en) Simultaneous tracking and navigation using leo satellite signals
Yi On improving the accuracy and reliability of GPS/INS-based direct sensor georeferencing
CN113109840A (en) Ionosphere TEC real-time measurement method based on GNSS receiver
Amami The Advantages and Limitations of Low-Cost Single Frequency GPS/MEMS-Based INS Integration
Chi et al. Enabling robust and accurate navigation for UAVs using real-time GNSS precise point positioning and IMU integration
Chen et al. Real-time kinematic positioning of LEO satellites using a single-frequency GPS receiver
Langel et al. Tightly coupled GPS/INS integration for differential carrier phase navigation systems using decentralized estimation
Zhou Low-cost MEMS-INS/GPS integration using nonlinear filtering approaches
JP2008232761A (en) Positioning device for mobile
KR20140142610A (en) Location measurement device and method
Wang et al. A New Efficient Filtering Model for GPS/SINS Ultratight Integration System
Martin Overcoming the challenges of low-cost inertial navigation

Legal Events

Date Code Title Description
PB01 Publication
PB01 Publication
SE01 Entry into force of request for substantive examination
SE01 Entry into force of request for substantive examination
GR01 Patent grant
GR01 Patent grant