CN110068853A - A kind of fusion method precisely navigated - Google Patents
A kind of fusion method precisely navigated Download PDFInfo
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- CN110068853A CN110068853A CN201910173678.2A CN201910173678A CN110068853A CN 110068853 A CN110068853 A CN 110068853A CN 201910173678 A CN201910173678 A CN 201910173678A CN 110068853 A CN110068853 A CN 110068853A
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- data
- gps
- fusion method
- mimu
- gyroscope
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Classifications
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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
- G01S19/38—Determining a navigation solution using signals transmitted by a satellite radio beacon positioning system
- G01S19/39—Determining a navigation solution using signals transmitted by a satellite radio beacon positioning system the satellite radio beacon positioning system transmitting time-stamped messages, e.g. GPS [Global Positioning System], GLONASS [Global Orbiting Navigation Satellite System] or GALILEO
- G01S19/42—Determining position
- G01S19/48—Determining position by combining or switching between position solutions derived from the satellite radio beacon positioning system and position solutions derived from a further system
- G01S19/49—Determining position by combining or switching between position solutions derived from the satellite radio beacon positioning system and position solutions derived from a further system whereby the further system is an inertial position system, e.g. loosely-coupled
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- Engineering & Computer Science (AREA)
- Radar, Positioning & Navigation (AREA)
- Remote Sensing (AREA)
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Automation & Control Theory (AREA)
- Computer Networks & Wireless Communication (AREA)
- Navigation (AREA)
Abstract
The present invention relates to navigation integration technology field, especially a kind of fusion method precisely navigated includes the following steps；Step 1: the assembly of GPS, gyroscope and accelerometer；Step 2: soft and hardware is debugged；Step 3: navigation calculation；Step 4: GPS data and gyro data to be fused into the NMEA agreement of standard, it is communicated by serial ports and ARM, the present invention is by using modularization, standardization, using serial communication, in accordance with NMEA standard agreement, reach precision height, satellite-signal is used in outdoor section, inertial guidance data is used in sections such as tunnel, bridges, the two can carry out free installation relative to any established angle of bodywork reference frame with seamless switching, when avoiding through the weak section of the satellite-signals such as bottom of passing a bridge, tunnel, show that vehicle driving trace shifts on the map of onboard system.
Description
Technical field
The present invention relates to navigation integration technology fields, more particularly to a kind of fusion method precisely navigated.
Background technique
Global positioning system (GPS) is to be defended by the space of new generation of land, sea, and air, the U.S. joint research and development the 1970s
Star navigation positioning system, main purpose are that real-time, round-the-clock and global navigation clothes are provided for the big field in land, sea, air three
Business, and for some military purposes such as information acquisition, Nuclear detonation monitoring and emergency communications, in March, 1994, Global coverage rate is up to
Own lay of 98% 24 GPS satellite constellations is completed；
Current onboard system only provides data navigation with GPS chip, and the function that navigates well may be implemented in normal section
Can, meet the needs of client, but when through the weak section of the satellite-signals such as gap bridge bottom, tunnel, shows vehicle on the map of onboard system
Driving trace is easy to happen offset.
Summary of the invention
It is mentioned above in the background art to solve the purpose of the present invention is to provide the fusion method that one kind is precisely navigated
Problem.
To achieve the goals above, present invention employs following technical solutions:
A kind of fusion method precisely navigated is designed, is included the following steps；
Step 1: the assembly of GPS, gyroscope and accelerometer；
S1, gyroscope and accelerometer are tested for the property and are analyzed respectively, integral calibrating has been carried out to MIMU；
S2, frame structure is spread out using change geometry to measure combination calibration system software and hardware, extracts gyroscope with wavelet analysis method
Output data establishes the arma modeling of gyroscopic drift；
S3, the format for analyzing GPS message, for the decoding of different modes and message that GPS data and gyro data combine
Method works out relevant program, and has carried out whole assembly；
Step 2: soft and hardware is debugged；
S1, high speed, high-accuracy data acquisition are carried out to MIMU；
S2, the message that the output of GPS-OEM plate asynchronous serial port is controlled and received, judged and verified using single-chip microcontroller, between each processor
Asynchronous communication is realized by UART shared data；
Step 3: navigation calculation；
S1, according to the combination technique of GPGGA and GPRMC, combined system is determined to the state equation and measurement equation of data combination
Bearing calibration；
S2, it is combined for different assembled schemes with software, realizes that MIMU is synchronous with the data of GPS；
S3, detection data gross error, the failure of GPS velocity jump and filter error estimation, carry out Fault Isolation in time,
Promote system that there is good fault-tolerant ability；
Step 4: GPS data and gyro data to be fused into the NMEA agreement of standard, communicated by serial ports and ARM.
Preferably, in step 3, S3 solves measurement correlation using federal strong tracking Kalman filter algorithm, GPS velocity is jumped
Become the problems such as choosing sensibility with initial value, improves the real-time, robustness and error resilience performance of system.
Preferably, in step 3, data described in S1 are location/velocity combination, pseudorange/pseudorange rates.
Preferably, in step 2, S1 carries out high speed, high-accuracy data acquisition to MIMU using floating point amplifier and FPGA.
Preferably, it in step 4, is adjusted using fuzzy self-adaption method, most using multisensor Linear Minimum Variance
Excellent estimation weighted method realizes the data fusion between subfilter.
The fusion method that one kind proposed by the present invention is precisely navigated, beneficial effect are:
1, the present invention abides by NMEA standard agreement using serial communication by using modularization, standardization, reaches precision height,
Outdoor section uses satellite-signal, uses inertial guidance data in sections such as tunnel, bridges, the two can be with seamless switching, can be opposite
Free installation, when avoiding through the weak section of the satellite-signals such as bottom of passing a bridge, tunnel, vehicle are carried out in any established angle of bodywork reference frame
Show that vehicle driving trace shifts on the map of loading system.
Detailed description of the invention
Fig. 1 is structure of the invention block diagram.
Specific embodiment
Following will be combined with the drawings in the embodiments of the present invention, and technical solution in the embodiment of the present invention carries out clear, complete
Site preparation description, it is clear that described embodiments are only a part of the embodiments of the present invention, instead of all the embodiments.
Referring to Fig.1, a kind of fusion method precisely navigated, includes the following steps；
Step 1: the assembly of GPS, gyroscope and accelerometer；
S1, gyroscope and accelerometer are tested for the property and are analyzed respectively, integral calibrating has been carried out to MIMU；
S2, frame structure is spread out using change geometry to measure combination calibration system software and hardware, extracts gyroscope with wavelet analysis method
Output data establishes the arma modeling of gyroscopic drift；
S3, the format for analyzing GPS message, for the decoding of different modes and message that GPS data and gyro data combine
Method works out relevant program, and has carried out whole assembly；
Step 2: soft and hardware is debugged；
S1, high speed, high-accuracy data acquisition are carried out to MIMU, high speed, high-precision is carried out to MIMU using floating point amplifier and FPGA
Degree is according to acquisition；
S2, the message that the output of GPS-OEM plate asynchronous serial port is controlled and received, judged and verified using single-chip microcontroller, between each processor
Asynchronous communication is realized by UART shared data；
Step 3: navigation calculation；
S1, according to the combination technique of GPGGA and GPRMC, combined system is determined to the state equation and measurement equation of data combination
Bearing calibration, the data be location/velocity combination, pseudorange/pseudorange rates；
S2, it is combined for different assembled schemes with software, realizes that MIMU is synchronous with the data of GPS；
S3, detection data gross error, the failure of GPS velocity jump and filter error estimation, carry out Fault Isolation in time,
Promote system that there is good fault-tolerant ability, solves to measure related, GPS velocity jump using federal strong tracking Kalman filter algorithm
Become the problems such as choosing sensibility with initial value, improves the real-time, robustness and error resilience performance of system；
Step 4: GPS data and gyro data to be fused into the NMEA agreement of standard, communicated by serial ports and ARM, using mould
Self-adaptive fuzzy method is adjusted, and realizes subfilter using multisensor Linear Minimum Variance optimal estimation weighted method
Between data fusion.
The foregoing is only a preferred embodiment of the present invention, but scope of protection of the present invention is not limited thereto,
Anyone skilled in the art in the technical scope disclosed by the present invention, according to the technique and scheme of the present invention and its
Inventive concept is subject to equivalent substitution or change, should be covered by the protection scope of the present invention.
Claims (5)
1. the fusion method that one kind is precisely navigated, it is characterised in that: include the following steps；
Step 1: the assembly of GPS, gyroscope and accelerometer；
S1, gyroscope and accelerometer are tested for the property and are analyzed respectively, integral calibrating has been carried out to MIMU；
S2, frame structure is spread out using change geometry to measure combination calibration system software and hardware, extracts gyroscope with wavelet analysis method
Output data establishes the arma modeling of gyroscopic drift；
S3, the format for analyzing GPS message, for the decoding of different modes and message that GPS data and gyro data combine
Method works out relevant program, and has carried out whole assembly；
Step 2: soft and hardware is debugged；
S1, high speed, high-accuracy data acquisition are carried out to MIMU；
S2, the message that the output of GPS-OEM plate asynchronous serial port is controlled and received, judged and verified using single-chip microcontroller, between each processor
Asynchronous communication is realized by UART shared data；
Step 3: navigation calculation；
S1, according to the combination technique of GPGGA and GPRMC, combined system is determined to the state equation and measurement equation of data combination
Bearing calibration；
S2, it is combined for different assembled schemes with software, realizes that MIMU is synchronous with the data of GPS；
S3, detection data gross error, the failure of GPS velocity jump and filter error estimation, carry out Fault Isolation in time,
Promote system that there is good fault-tolerant ability；
Step 4: GPS data and gyro data to be fused into the NMEA agreement of standard, communicated by serial ports and ARM.
2. the fusion method that one kind according to claim 1 is precisely navigated, it is characterised in that: in step 3, S3 is using connection
Nation's strong tracking Kalman filter algorithm solves the problems such as measuring related, GPS velocity jump and initial value selection sensibility, improves system
Real-time, robustness and error resilience performance.
3. the fusion method that one kind according to claim 1 is precisely navigated, it is characterised in that: counted in step 3, described in S1
According to for location/velocity combination, pseudorange/pseudorange rates.
4. the fusion method that one kind according to claim 1 is precisely navigated, it is characterised in that: in step 2, S1 utilizes floating
Spot magnifier and FPGA carry out high speed, high-accuracy data acquisition to MIMU.
5. the fusion method that one kind according to claim 1 is precisely navigated, it is characterised in that: in step 4, using fuzzy
Adaptive approach is adjusted, using multisensor Linear Minimum Variance optimal estimation weighted method realize subfilter it
Between data fusion.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201910173678.2A CN110068853A (en) | 2019-03-08 | 2019-03-08 | A kind of fusion method precisely navigated |
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| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201910173678.2A CN110068853A (en) | 2019-03-08 | 2019-03-08 | A kind of fusion method precisely navigated |
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| CN110068853A true CN110068853A (en) | 2019-07-30 |
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| CN201910173678.2A Pending CN110068853A (en) | 2019-03-08 | 2019-03-08 | A kind of fusion method precisely navigated |
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| CN (1) | CN110068853A (en) |
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2019
- 2019-03-08 CN CN201910173678.2A patent/CN110068853A/en active Pending
Non-Patent Citations (1)
| Title |
|---|
| 马云峰: "MSINS/GPS组合导航系统及其数据融合技术研究", 《博士电子期刊》 * |
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