CN105973243A - Vehicle-mounted inertial navigation system - Google Patents
Vehicle-mounted inertial navigation system Download PDFInfo
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- CN105973243A CN105973243A CN201610596714.2A CN201610596714A CN105973243A CN 105973243 A CN105973243 A CN 105973243A CN 201610596714 A CN201610596714 A CN 201610596714A CN 105973243 A CN105973243 A CN 105973243A
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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
- G01C21/26—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 specially adapted for navigation in a road network
- G01C21/28—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 specially adapted for navigation in a road network with correlation of data from several navigational 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
- G01C21/165—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
- G01S19/38—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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- Radar, Positioning & Navigation (AREA)
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- General Physics & Mathematics (AREA)
- Automation & Control Theory (AREA)
- Computer Networks & Wireless Communication (AREA)
- Navigation (AREA)
Abstract
The invention relates to a vehicle-mounted inertial navigation system. According to the system, GPS/DR/MM technologies are combined for vehicle-mounted inertial navigation, vehicle speed pulse signals do not need to be collected, information is directly read through a CAN bus of a vehicle sound port, and vehicle refitting is avoided. The system comprises a main processor MCU, a gyroscope, a GPS and a map, dynamic compensation is adopted for gyroscope zero offset errors, an HDR algorithm is adopted for random drift errors for compensation, the system does not only depend on data basis that inertial navigation is achieved by reading vehicle body information, GPS positioning information and DR system positioning information are further corrected through the map matching technology, and therefore overall vehicle safety and navigation positioning reliability are improved.
Description
Technical field
The present invention relates to auto navigation and vehicle tracking system, particularly relate to a kind of vehicle-mounted inertial navigation system.
Background technology
Global positioning system (global position system is called for short GPS) technology has been applied to automobile and has led at present
In boat and vehicle tracking system.But, in such as tunnel, some place, in the environment such as indoor and underground parking, GPS information is strong
Spend the lowest and cause GPS substantially can not receive satellite data thus cannot output position information.Existing solution
Scheme is to use the onboard navigation system with inertial navigation.
Authorization Notice No. is that the utility model patent of CN202229766U discloses a kind of sensor-based inertial navigation
System, is combined inertial navigation technology with GPS technology, including main control module, GPS receiver module, CAN control module, top
Spiral shell instrument sensor, speed pulse sensor, tire rotational speed gap sensor etc..This inertial navigation system is by the vapour obtained by sensor
Car steering angle, the information such as car speed and automobile tire speed discrepancy is harmonious with GPS location information, thus opens and improve GPS receiver
The active position coverage of machine and position output accuracy.
But, above-mentioned inertial navigation system needs to obtain the information of automobile body, the most inevitably needs to carry out car
Repacking, add the difficulty of repacking and destroy again the interface of former car vehicle, creating the risk of spontaneous combustion, also create
The risk of legal dispute.Additionally, due to the speed meter employed on vehicle, this can cause certain error, simultaneously because tire fills
Gas degree difference and the difference of load, the change of speed, the abrasion of tire, the impact of condition of road surface makes vehicle slip and bullet
Jump and turn inside diameter etc. causes the error measuring distance, it addition, also angular rate gyroscope there is also error drift, and at any time
Between accumulate, these have all had a strong impact on the reliability of navigator fix.
Summary of the invention
The invention aims to provide a kind of and no longer simple rely on that to read over the vehicle that body information of picking up the car realizes reliable
Property high, inertial navigation system that navigator fix reliability is high, simultaneously without vehicle is reequiped.
The vehicle-mounted inertial navigation system of the present invention is combined with GPS by the inertial navigation system formed by gyroscope,
There is provided by means of GPS the position without cumulative error, velocity information to estimate continuously and correct position and the speed of gyroscope system
And other errors of system, attitude information and angular velocity information by gyroscope system can overcome GPS to accept antenna
Orientation and the problem such as signal loss in short-term so that GPS system can be with fast Acquisition or relock satellite-signal；Utilize number simultaneously
The location information of GPS location information and DR system is done correction further by word map matching technique.
Vehicular navigation system is on the basis of the road network digital map of applied geography information systems technology structure, uses
The location technologies such as GPS, reckoning (DR), map match (MM) carry out the system of vehicle location, and the vehicle-mounted inertia of the present invention is led
Boat system includes: primary processor MCU, gyroscope, GPS and map, and primary processor MCU connects vehicle by CAN controller
The CAN of acoustic interface carries out information reading, it is to avoid vehicle refitting, and primary processor MCU connects gyro by SPI interface
Instrument, connects GPS and map by serial ports.
Primary processor selects the LPC11C14 of ST company as primary processor, completes data and processes, external module control etc.
Function.This processor is micro controller based on ARM Cotex-M0, can be used for the embedding application of high integration and low-power consumption, ARM
Cotex-M0 is second filial generation kernel, it provides a simple instruction set, it is possible to achieve definitiveness behavior.Operating frequency is up to
50MHZ. peripheral hardware includes the FLASH of up to 32KB, the data storage of 8KB.CAN controller passes through CAN transceiver and CAN
Bus connects.CAN transceiver uses PCA82C250, completes the conversion between the differential voltage of CAN and level voltage, it
Completely compatible with ISO/DIS11898 standard, CHAN and CANL two-wire is also prevented from the most contingent electrical transients
Phenomenon.Gyroscope uses the L3G4200D chip of ST ST Microelectronics to complete, and this L3G4200D is a kind of low-power consumption three axle
Gyroscope, it is provided that three kinds of optional full sizes (± 250/ ± 500/ ± 2000dps), this sensing element is to use the finest adding
Work technique, and IC, SPI interface technology achieve and design a special circuit with CMOS, this L3G4200D uses plastics (LGA)
Encapsulation dress also provides fabulous temperature stability, and operating temperature range expands (-40 DEG C to+85 DEG C) to.
Gyroscope initial condition gives:
Consider two kinds of original states, stationary vehicle and linear motion state, at the beginning of needing to be given below under both states
Beginning state:
1. give initial position λ0, L0, h0, wherein,
For the true initial position of carrier, Δ λ0, Δ L0, Δ h0For initial position error；
2. give initial velocity VE0, VN0, VU0, wherein,
For the true initial velocity of carrier, Δ VE0, Δ VN0, Δ VU0For initial velocity error；
3. given initial attitude angle θ0, ψ0, γ0, wherein,
For the true initial attitude angle of carrier, Δ θ0, Δ ψ0, Δ γ0For initial attitude angle error；
Above-mentioned initial error Δ λ0, Δ L0, Δ h0, Δ VE0, Δ VN0, Δ VU0, Δ θ0, Δ ψ0, Δ γ0By inertial navigation system
Initial alignment condition of uniting determines.
Primary data computing formula is as follows:
Wherein,For X, the measurement of Y direction acceleration
Value, g is acceleration of gravity.
When vehicle is in the original state of linear motion, the acceleration of the X axis of vehicle is that gravity is in this axial dividing
Amount, by formulaCan calculate γ 0, electronic compass can calculate θ according to γ 0 and longitude and latitude0, ψ0。
The error source of inertial navigation specifically includes that error that the approximation of mathematical modeling causes is (such as vehicle Small-angle Rotation bar
Quaternion differential equation is set up under part), the error of inertance element (includes the alignment error of inertia device, scale factor error, top
The drift of spiral shell and the biased error of accelerometer) calculate error, scale factor error, the drift of gyro and the biasing of accelerometer
Error, calculates error, Initial Alignment Error (mainly by the error of inertia sensitive element): environmental error (vibration of vehicle, punching
Hit, the error under the environmental condition such as temperature).
Due to temperature, analog digital conversion error, the impact of the factors such as interference signal, when micro inertial measurement unit MIMU is static
Time, there is null value skew in gyro, if be not handled by, the deviation of the matrix directly calculated by navigation algorithm is big especially,
Thus causing attitude angle, azimuth, speed, longitude and latitude deviation is the biggest.The usually compensation to null value offset error is all compared
Simply, after generally using gyroscope working stability, the average of one section of data-at-rest compensates gyroscope during whole service
Null value offset error.But it is as the impact of the factors such as the change of the increase of the working time of gyroscope, ambient temperature, gyroscope
Null value skew also can produce significantly drift, in order to remove null value offset error more accurately, the present invention proposes a kind of dynamic
State compensation method:
Step 1) preset the renewal time T of the null value migration factor；
Step 2) judge current demand signal stationarity.If signal is stationary signal in the ban, the most desirable current one piece of data
Average update compensating factor, if current demand signal is non-stationary signal.Then should skip and this time update.
The invention also discloses employing HDR algorithm to carry out Random Drift Error compensation, gyroscope Output speed signal,
But due to the restriction of gyroscope precision, containing certain error in the angular velocity signal of output, this error packet offsets containing null value
Error ε0With Random Drift Error εd.Random Drift Error εdThen represent the random drift of gyroscope, the increasing of gyroscope working time
Adding, the change of temperature environment etc. all can make gyroscope produce small rotation and then make to produce between output valve and actual value
Deviation, these deviations are referred to as random drift, and this is also the main object that HDR estimates and compensates.ωtrueFor true output,
In order to record ω accuratelytrue, it is necessary to from the data measured, go null value offset error ε0With Random Drift Error εd.Work as carrier
Angular velocity of rotation is ωtrueTime, the angular velocity that gyroscope actually exports is ωtrue+ε0+εd.Null value offset error ε0Compensation
Have been carried out above describing, so the angular velocity after null value offset error compensation is ωtrue+εd, afterwards by a double low pass
The flapping issue during motion of wave filter resolved vector, the angular velocity after double low pass filters becomes ω "+εd.The setting of input
Angular velocity is 0, i.e. ωset=0.The ω in a upper momentiIt is worth by a z-transform, on the one hand feeds back to set with degenerative form
Determine input, obtain error signal E, on the other hand by a deamplification controller and integral controller.Error signal E is led to
The integration crossing integral controller can be compensated factor I.Compensating factor I and the ω "+ε that will try to achievedIt is added, then obtains current
The angular velocity omega in momenti；
Gyroscope angular velocity after HDR algorithm compensation is:
ωi=ω "+εd+Ii, ω is " for angular velocity omegatrueMagnitude of angular velocity through double low pass filters；
Compensating factor calculates:
Ii=Ii-1-Aisign(ωi-1)ic, Ii-1For the compensating factor in a upper moment, IiFor the compensating factor of current time,
Sign for taking sign function, icFor constant, AiFor attenuation function,
Wherein ωi-1For the angular velocity in a upper moment, θωFor the threshold value set, p is
The decay factor set.
In order to add the speed of rapid convergence, preferably identify that small angle input reduces error present on theory, carry
The accuracy of high algorithm, improves threshold function table.
In above-mentioned algorithm, the selection of p value is the most crucial, when p value select the biggest, convergence rate is the fastest, but the effect of HDR
Scope will reduce, in actual applications, as long as selecting suitable p and θω, can make to export result closer to the most defeated
Enter, obtain the output of preferable angular velocity.
The present invention merges GPS and DR, constitutes GPS/DR integrated navigation system, mutually compensating for by system, utilizes it
Respective advantage, makes up for each other's deficiencies and learn from each other such that it is able to obtain the navigation accuracy being better than any independent a kind of navigation system with reliable
Property.Using federated Kalman filtering to calculate maximum likelihood estimate, in multisensor syste, federated Kalman filtering utilizes letter simultaneously
Breath distribution principle is capable of the optimal synthesis of multi-sensor information, and makes whole system have certain fault-tolerant ability, from
And it is obtained in that performance optimum on the whole.The thought of federated Kalman filtering itself originates from the appearance solving integrated navigation system
Mistake and optimal information synthtic price index.Integrated navigation system is separate by GPS alignment system and inertial navigation system two
The multisensor syste that subsystem is constituted, therefore, federated Kalman filtering technology is applied to onboard combined navigation system can
Realize the optimal synthesis of locating navigation information and mutually correct.If but inertial navigation system and GPS are exported directly with card
Family name filters, then the amount of calculation of its equation is the biggest.If but use indirect feedback method will calculate the cycle greatly, filtering effective
Performance is not exposed to impact.Specific practice is that the value of calculation of the error with inertia navigation system goes to correct inertia navigation system mechanics
Corresponding navigational parameter in layout, will feed back to the inside of inertial navigation system, to obtain the optimum of navigational parameter by error estimate
Estimate.
The invention also discloses utilize numerical map matching technique GPS location information and the location information of DR system are done into
One step correction:
The function of map match disclosed by the invention be vehicle driving trace by framing signal is determined with electronically
The geometric properties of running section relevant in figure compares, thus select that a vehicle most possibly travels, be positioned at road
Coupling track on some section of transportation network.This matching process is to be realized by certain matching algorithm.
The map-matching algorithm flow process of the present invention is as follows:
Step1: with vehicle point as the center of circle, choosing suitable value is that radius draws implicit circle, it is judged that this circle and highway map layer
If whether the object in intersects, then calculating in highway map layer has several object to intersect with this circle.If found more than one
Individual object, the most suitably reduces radius of circle, the most suitably strengthens radius of circle as do not met the highway map layer object of condition, until finding
Only one meets the object of condition, obtains the highway field of this object.If the radius of circle is more than a certain thresholding, it is considered as this
Time vehicle oneself through enter a certain region, such as bigger square or parking lot etc., now using the center of circle as check point, directly turn
step4。
Step2: in judging to circulate title and the last time of highway object in this circulation, highway object is the most identical, identical
Then represent that two points, on same highway, forward step3 to.If it is different, so vehicle is likely to be turning, but not
Judging that well vehicle is turned left or turned right, so taking this is put the way not processed, skipping this point, but still
Record and the nearest highway object of vehicle point in case recycle ratio next time is relatively used.Take next point, return step1.
Step3: read all flex points on this highway object, calculate the line segment that vehicle o'clock is linked to be to two adjacent comers
Intersection point and vehicle point and intersection point between distance, if intersection point between these adjacent 2 and distance is minimum, then take this and hang down
Foot is as check point.
Step4: draw a mark on the check point tried to achieve.Take next vehicle point, continue to run with.
Compared with prior art, technical scheme has the advantage that
1, the vehicle-mounted inertial navigation system of the present invention directly carries out information reading by the CAN of vehicle sound interface,
Thus avoid the repacking of car, improve the overall security of vehicle.
2, the present invention is by the dynamic compensation of the null value offset error to gyroscope and the compensation of Random Drift Error, carries
The high reliability of navigator fix.
3, the present invention is without collection vehicle pulse signal, so further avoid acquisition pulse and being converted into the mistake of speed
Acquisition Error in journey, it is to avoid the problem of driftage.
4, present configuration is simple, also has low cost and installs the advantages such as convenient.
5, the present invention also uses Ka Shi filtering indirect feedback and numerical map matching technique to GPS location information and DR
The location information of system does correction further, further increases the accurate reliability of navigation.
Accompanying drawing explanation
Fig. 1 is the structured flowchart of one embodiment of the present of invention.
Fig. 2 is CAN interface circuit in one embodiment of the present of invention.
Fig. 3 is null value offset error dynamic compensation block diagram of the present invention.
Fig. 4 is Random Drift Error offset data process chart of the present invention.
Fig. 5 is that the present invention utilizes Ka Shi filtering indirect feedback method filtering schematic diagram.
Detailed description of the invention
Seeing Fig. 1, the vehicle-mounted inertial navigation system of the present invention includes: primary processor MCU, gyroscope, GPS and map, main
The CAN that processor MCU connects vehicle sound interface by CAN controller carries out information reading, and primary processor passes through
SPI interface connects gyroscope, connects GPS and map by serial ports.
The primary processor MCU of the present invention selects the LPC11C14 of ST company as primary processor, completes data and processes, outside
The functions such as module control.This processor is micro controller based on ARM Cotex-M0, can be used for the embedding of high integration and low-power consumption
Entering application, ARM Cotex-M0 is second filial generation kernel, it provides a simple instruction set, it is possible to achieve definitiveness behavior.
Operating frequency up to 50MHZ. peripheral hardware includes the data storage of the FLASH, 8KB of up to 32KB.CAN controller passes through
CAN transceiver is connected with CAN.CAN transceiver uses PCA82C250, completes differential voltage and the level voltage of CAN
Between conversion, it is completely compatible with ISO/DIS11898 standard, CHAN and CANL two-wire be also prevented from the vehicle context may
The electrical transients phenomenon occurred, CAN interface circuit sees Fig. 2.
The gyroscope of the present invention uses the L3G4200D chip of ST ST Microelectronics to complete, and this L3G4200D is a kind of
Low-power consumption three-axis gyroscope, it is provided that three kinds of optional full sizes (± 250/ ± 500/ ± 2000dps), this sensing element is to use
Special fine process, and IC, SPI interface technology achieve and design a special circuit with CMOS, this L3G4200D adopts
Filling with plastics (LGA) encapsulation and provide fabulous temperature stability, operating temperature range expands (-40 DEG C to+85 DEG C) to.
Gyroscope initial condition of the present invention gives:
Consider two kinds of original states, stationary vehicle and linear motion state, at the beginning of needing to be given below under both states
Beginning state:
1. give initial position λ0, L0, h0, wherein,
For the true initial position of carrier, Δ λ0, Δ L0, Δ h0For initial position error；
2. give initial velocity VE0, VN0, VU0, wherein,
For the true initial velocity of carrier, Δ VE0, Δ VN0, Δ VU0For initial velocity error；
3. give initial attitude angle θ0, ψ0, γ0, wherein,
For the true initial attitude angle of carrier, Δ θ0, Δ ψ0, Δ γ0For initial attitude angle error；
Above-mentioned initial error Δ λ0, Δ L0, Δ h0, Δ VE0, Δ VN0, Δ VU0, Δ θ0, Δ ψ0, Δ γ0By inertial navigation system
Initial alignment condition of uniting determines.
Due to temperature, analog digital conversion error, the impact of the factors such as interference signal, when micro inertial measurement unit MIMU is static
Time, there is null value skew in gyro, if be not handled by, the deviation of the matrix directly calculated by navigation algorithm is big especially,
Thus causing attitude angle, azimuth, speed, longitude and latitude deviation is the biggest.The usually compensation to null value offset error is all compared
Simply, after generally using gyroscope working stability, the average of one section of data-at-rest compensates gyroscope during whole service
Null value offset error.But it is as the impact of the factors such as the change of the increase of the working time of gyroscope, ambient temperature, gyroscope
Null value skew also can produce significantly drift, in order to remove null value offset error more accurately, the present invention proposes a kind of dynamic
State compensation method, sees Fig. 3:
Step 1) preset the renewal time T of the null value migration factor；
Step 2) judge current demand signal stationarity.If signal is stationary signal in the ban, the most desirable current one piece of data
Average update compensating factor, if current demand signal is non-stationary signal.Then should skip and this time update.
The invention also discloses a kind of Gyroscope Random Drift Compensation method, this Random Drift Error compensation method is adopted
Design closed network with HDR algorithm, increase double low pass filter and remove the deviation produced due to gyroscopic roll, significantly reduce top
The Random Drift Error of spiral shell instrument, reduces gyroscope noise, improves output precision of gyroscope.
See Fig. 4, the present invention use HDR algorithm to carry out Random Drift Error compensation, gyroscope Output speed signal,
But due to the restriction of gyroscope precision, containing certain error in the angular velocity signal of output, this error packet offsets containing null value
Error ε0With Random Drift Error εd.Random Drift Error εdThen represent the random drift of gyroscope, the increasing of gyroscope working time
Adding, the change of temperature environment etc. all can make gyroscope produce small rotation and then make to produce between output valve and actual value
Deviation, these deviations are referred to as random drift, and this is also the main object that HDR estimates and compensates.ω in Fig. 4trueFor the most defeated
Go out value, in order to record ω accuratelytrue, it is necessary to from the data measured, go null value offset error ε0With Random Drift Error εd.By
Fig. 4 understands, when carrier angular velocity of rotation is ωtrueTime, the angular velocity that gyroscope actually exports is ωtrue+ε0+εd.Null value is inclined
Shift error ε0Compensation above have been carried out describe, so the angular velocity after null value offset error compensation is ωtrue+εd, afterwards
By flapping issue during a double low pass filter resolved vector motion, the angular velocity after double low pass filters becomes ω "+
εd.The set angle speed of input is 0, i.e. ωset=0.The ω in a upper momentiIt is worth by a z-transform, on the one hand with degenerative
Form feeds back to set input, obtains error signal E, on the other hand by a deamplification controller and integration control
Device.Error signal E can be compensated factor I by the integration of integral controller.Compensating factor I and the ω "+ε that will try to achievedPhase
Add, then obtain the angular velocity omega of current timei；
Gyroscope angular velocity after HDR algorithm compensation is:
ωi=ω "+εd+Ii, ω is " for angular velocity omegatrueMagnitude of angular velocity through double low pass filters；
Compensating factor calculates:
Ii=Ii-1-Aisign(ωi-1)ic, Ii-1For the compensating factor in a upper moment, IiFor the compensating factor of current time,
Sign for taking sign function, icFor constant, AiFor attenuation function,
Wherein ωi-1For the angular velocity in a upper moment, θωFor the threshold value set, p is
The decay factor set.
In order to add the speed of rapid convergence, preferably identify that small angle input reduces error present on theory, carry
The accuracy of high algorithm, improves threshold function table.
In above-mentioned algorithm, the selection of p value is the most crucial, when p value select the biggest, convergence rate is the fastest, but the effect of HDR
Scope will reduce, in actual applications, as long as selecting suitable p and θω, can make to export result closer to the most defeated
Enter, obtain the output of preferable angular velocity.
The present invention merges GPS and DR, constitutes GPS/DR integrated navigation system, mutually compensating for by system, utilizes it
Respective advantage, makes up for each other's deficiencies and learn from each other such that it is able to obtain the navigation accuracy being better than any independent a kind of navigation system with reliable
Property.Using federated Kalman filtering to calculate maximum likelihood estimate, in multisensor syste, federated Kalman filtering utilizes letter simultaneously
Breath distribution principle is capable of the optimal synthesis of multi-sensor information, and makes whole system have certain fault-tolerant ability, from
And it is obtained in that performance optimum on the whole.The thought of federated Kalman filtering itself originates from the appearance solving integrated navigation system
Mistake and optimal information synthtic price index.Integrated navigation system is separate by GPS alignment system and inertial navigation system two
The multisensor syste that subsystem is constituted, therefore, federated Kalman filtering technology is applied to onboard combined navigation system can
Realize the optimal synthesis of locating navigation information and mutually correct.If but inertial navigation system and GPS are exported directly with card
Family name filters, then the amount of calculation of its equation is the biggest.If but use indirect feedback method will calculate the cycle greatly, filtering effective
Performance is not exposed to impact.Specific practice is that the value of calculation of the error with inertia navigation system goes to correct inertia navigation system mechanics
Corresponding navigational parameter in layout, will feed back to the inside of inertial navigation system, to obtain the optimum of navigational parameter by error estimate
Estimate, see Fig. 5.
The invention also discloses utilize numerical map matching technique GPS location information and the location information of DR system are done into
One step correction:
The function of map match disclosed by the invention be vehicle driving trace by framing signal is determined with electronically
The geometric properties of running section relevant in figure compares, thus select that a vehicle most possibly travels, be positioned at road
Coupling track on some section of transportation network.This matching process is to be realized by certain matching algorithm.
The map-matching algorithm flow process of the present invention is as follows:
Step1: with vehicle point as the center of circle, choosing suitable value is that radius draws implicit circle, it is judged that this circle and highway map layer
If whether the object in intersects, then calculating in highway map layer has several object to intersect with this circle.If found more than one
Individual object, the most suitably reduces radius of circle, the most suitably strengthens radius of circle as do not met the highway map layer object of condition, until finding
Only one meets the object of condition, obtains the highway field of this object.If the radius of circle is more than a certain thresholding, it is considered as this
Time vehicle oneself through enter a certain region, such as bigger square or parking lot etc., now using the center of circle as check point, directly turn
step4。
Step2: in judging to circulate title and the last time of highway object in this circulation, highway object is the most identical, identical
Then represent that two points, on same highway, forward step3 to.If it is different, so vehicle is likely to be turning, but not
Judging that well vehicle is turned left or turned right, so taking this is put the way not processed, skipping this point, but still
Record and the nearest highway object of vehicle point in case recycle ratio next time is relatively used.Take next point, return step1.
Step3: read all flex points on this highway object, calculate the line segment that vehicle o'clock is linked to be to two adjacent comers
Intersection point and vehicle point and intersection point between distance, if intersection point between these adjacent 2 and distance is minimum, then take this and hang down
Foot is as check point.
Step4: draw a mark on the check point tried to achieve.Take next vehicle point, continue to run with.
Use the vehicle-mounted inertial navigation system in above-mentioned numerical procedure, there is at a relatively high navigation accuracy and navigation is reliable
Property.
Although it should be understood by those skilled in the art that the present invention discloses as above with preferred embodiment, but the present invention can be real
Execute into other particular form, without deviating from its spirit or inner characteristic.Above-described embodiment only the most all will be understood as one that
It is only exemplary and nonrestrictive.Therefore, protection scope of the present invention is by appending claims rather than above
Description limits.Change in the implication of fallen with claims equivalent and scope all will be contained in claims
Within the scope of.
Claims (7)
1. a vehicle-mounted inertial navigation system, including primary processor MCU, gyroscope, GPS and map, it is characterised in that: main process
The CAN that device MCU connects vehicle sound interface by CAN controller carries out information reading, and primary processor MCU passes through
SPI interface connects gyroscope, connects GPS and map by serial ports.
Vehicle-mounted inertial navigation system the most according to claim 1, it is characterised in that primary processor MCU selects ST company
LPC11C14 uses the L3G4200D chip of ST ST Microelectronics as primary processor, gyroscope, and CAN transceiver uses
PCA82C250。
Vehicle-mounted inertial navigation system the most according to claim 1 and 2, gyroscope is under stationary vehicle and linear motion state
It is given below original state:
A) given initial position λ0, L0, h0, wherein, For
The true initial position of carrier, Δ λ0, Δ L0, Δ h0For initial position error；
B) given initial velocity VE0, VN0, VU0, wherein, For the true initial velocity of carrier, Δ VE0, Δ VN0, Δ VU0For initial velocity error；
C) given initial attitude angle θ0, ψ0, γ0, wherein, For the true initial attitude angle of carrier, Δ θ0, Δ ψ0, Δ γ0For initial attitude angle error；
Above-mentioned initial error Δ λ0, Δ L0, Δ h0, Δ VE0, Δ VN0, Δ VU0, Δ θ0, Δ ψ0, Δ γ0At the beginning of inertial navigation system
Beginning alignment condition determines, primary data computing formula is as follows:
Wherein,For X, the measured value of Y direction acceleration, g is
Acceleration of gravity；When vehicle is in the original state of linear motion, the acceleration of the X axis of vehicle is that gravity is axial at this
Component, by formulaγ can be calculated0, electronic compass is according to γ0θ can be calculated with longitude and latitude0, ψ0。
Vehicle-mounted inertial navigation system the most according to claim 1 and 2, it is characterised in that the null value offset error of gyroscope
Employing dynamic compensation method compensates, step 1) preset the renewal time T of the null value migration factor；Step 2) judge
The stationarity of current demand signal, if signal is stationary signal in the ban, the average of the most desirable current one piece of data update compensation because of
Son, if current demand signal is non-stationary signal, then should skip and this time update.
Vehicle-mounted inertial navigation system the most according to claim 1 and 2, it is characterised in that use HDR algorithm to carry out at random
Drift error compensation, the gyroscope angular velocity after HDR algorithm compensation is:
ωi=ω "+εd+Ii, ω " and it is angular velocity omegatrueThrough the magnitude of angular velocity of double low pass filters, ωtrueFor true output
Value；
Compensating factor calculates:
Ii=Ii-1-Aisign(ωi-1)ic, Ii-1For the compensating factor in a upper moment, IiFor the compensating factor of current time, sign
For taking sign function, icFor constant, AiFor attenuation function,
Wherein ωi-1For the angular velocity in a upper moment, θωFor the threshold value set, p is for setting
Decay factor.
Vehicle-mounted inertial navigation system the most according to claim 1 and 2, it is characterised in that this inertial navigation system and GPS are fixed
The output of position system also utilizes Ka Shi to filter indirect feedback, to obtain the optimal estimation of navigational parameter.
Vehicle-mounted inertial navigation system the most according to claim 1 and 2, it is characterised in that also include map matching technology, ground
Figure matching algorithm flow process is as follows:
Step1: with vehicle point as the center of circle, choosing suitable value is that radius draws implicit circle, it is judged that in this circle and highway map layer
If whether object intersects, then calculate in highway map layer and have several object to intersect with this circle, if find more than one right
As, the most suitably reduce radius of circle, the most suitably strengthen radius of circle as do not met the highway map layer object of condition, until finding unique
One object meeting condition, obtains the highway field of this object, if the radius of circle is more than a certain thresholding, is considered as now car
Oneself through enter a certain region, such as bigger square or parking lot etc., now using the center of circle as check point, directly turn
step4；
Step2: in judging to circulate title and the last time of highway object in this circulation, highway object is the most identical, identical then table
Show that two points, on same highway, forward step3 to, if it is different, so vehicle is likely to be turning, but bad sentence
Disconnected vehicle is turned left or is turned right, so taking this is put the way that do not processes, skips this point, but still record
The highway object nearest with vehicle point in case recycle ratio relatively use next time, take next point, return step1；
Step3: read all flex points on this highway object, calculates hanging down of the line segment that vehicle o'clock is linked to be to two adjacent comers
Be enough to and distance between vehicle point and intersection point, if intersection point between these adjacent 2 and distance is minimum, then take this intersection point and make
For check point；
Step4: draw a mark on the check point tried to achieve, takes next vehicle point, continues to run with.
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