CN105973243A - Vehicle-mounted inertial navigation system - Google Patents
Vehicle-mounted inertial navigation system Download PDFInfo
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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
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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
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- G—PHYSICS
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- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- G01S19/00—Satellite radio beacon positioning systems; Determining position, velocity or attitude using signals transmitted by such systems
- G01S19/38—Determining a navigation solution using signals transmitted by a satellite radio beacon positioning system
- G01S19/39—Determining a navigation solution using signals transmitted by a satellite radio beacon positioning system the satellite radio beacon positioning system transmitting time-stamped messages, e.g. GPS [Global Positioning System], GLONASS [Global Orbiting Navigation Satellite System] or GALILEO
- G01S19/42—Determining position
- G01S19/45—Determining position by combining measurements of signals from the satellite radio beacon positioning system with a supplementary measurement
- G01S19/47—Determining position by combining measurements of signals from the satellite radio beacon positioning system with a supplementary measurement the supplementary measurement being an inertial measurement, e.g. tightly coupled inertial
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Abstract
The invention 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 invention relates to an automobile navigation and vehicle tracking system, in particular to a vehicle-mounted inertial navigation system.
Background
Currently, Global Positioning System (GPS) technology has been applied to car navigation and vehicle tracking systems. However, in some places such as tunnels, indoor and underground parking lots, etc., the intensity of the GPS information is too low to cause the GPS receiver to substantially fail to receive satellite data and thus fail to output position information. The existing solution is to use a car navigation system with inertial navigation.
The utility model discloses a utility model patent that bulletin number is CN202229766U discloses an inertial navigation system based on sensor combines inertial navigation technique and GPS technique, including host system, GPS receiving module, CAN bus control module, gyroscope sensor, speed pulse sensor, tire rotational speed difference sensor etc.. The inertial navigation system combines the information of the automobile steering angle, the automobile speed, the automobile tire rotating speed difference and the like obtained by the sensor with the GPS positioning information, thereby improving the effective position coverage range and the position output precision of the GPS receiver.
However, the inertial navigation system needs to acquire information of the vehicle body, and vehicle refitting is inevitably needed, which increases the difficulty of refitting, destroys the interface of the original vehicle, and generates the risk of spontaneous combustion and the risk of legal dispute. In addition, because a speedometer on the vehicle is used, certain errors can be caused, meanwhile, the errors of measuring distances caused by vehicle slip and bounce, vehicle turning and the like are caused due to the fact that the inflation degree of tires is different, the loads are different, the vehicle speed changes, the abrasion of the tires and the influence of road conditions, and in addition, the angular rate gyro also has error drift and is accumulated along with time, and the errors seriously influence the reliability of navigation positioning.
Disclosure of Invention
The invention aims to provide an inertial navigation system which is high in vehicle reliability and navigation positioning reliability and does not need to be modified by simply reading vehicle body information.
The vehicle-mounted inertial navigation system of the invention combines an inertial navigation system composed of gyroscopes with a GPS, and estimates and corrects the position and speed of the gyroscope system and other errors of the system by continuously providing position and speed information without accumulated errors by means of the GPS, and can overcome the problems of orientation of a GPS receiving antenna, short-time signal loss and the like by means of the attitude information and the angular speed information of the gyroscope system, so that the GPS system can quickly capture or relock satellite signals; and meanwhile, the GPS positioning information and the positioning information of the DR system are further corrected by utilizing a digital map matching technology.
The vehicle navigation system is a system for positioning a vehicle by using positioning technologies such as GPS, Dead Reckoning (DR), Map Matching (MM) and the like on the basis of a road network digital map constructed by applying a geographic information system technology, and the vehicle-mounted inertial navigation system of the invention comprises: the main processor MCU is connected with the CAN bus of the vehicle sound interface through the CAN bus controller to read information, so that vehicle refitting is avoided, and the main processor MCU is connected with the gyroscope through the SPI interface and is connected with the GPS and the map through a serial port.
LPC11C14 of ST company is selected as a main processor by the main processor to complete functions of data processing, external module control and the like. The processor is a microcontroller based on ARM Cotex-M0 and can be used for embedded application with high integration level and low power consumption, and the ARMCotex-M0 is a second generation kernel and provides a simple instruction set to realize deterministic behavior. Operating frequency up to 50mhz the peripherals include up to 32KB of FLASH, 8KB of data storage. The CAN bus controller is connected with the CAN bus through the CAN transceiver. The CAN transceiver uses PCA82C250 to convert between differential and level voltages of the CAN bus, which is fully compatible with the ISO/DIS11898 standard, and the CHAN and CANL dual lines also prevent electrical transients that may occur in a vehicle environment. The gyroscope is completed using the chip L3G4200D from ST Chirp semiconductor corporation, the L3G4200D is a low power consumption triaxial gyroscope providing three alternative full scales (+ -250/+ -500/+ -2000 dps), the sensing element is designed using a special microfabrication process, and IC, SPI interface technology realizes a special circuit design using CMOS, the L3G4200D is packaged using plastic (LGA) and provides excellent temperature stability, and the operating temperature range is extended to (-40 ℃ to +85 ℃).
Initial conditions of the gyroscope are given:
two initial states, a vehicle stationary state and a linear motion state, are considered, in which the following initial states need to be given:
1. given an initial position λ0，L0，h0Wherein is the true initial position of the carrier, Δ λ0，ΔL0，Δh0Is the initial position error;
2. given initial velocity VE0，VN0，VU0Wherein for the true initial velocity of the carrier, Δ VE0，ΔVN0，ΔVU0Is the initial velocity error;
3. given an initial attitude angle θ0，ψ0，γ0Wherein is the true initial attitude angle of the carrier, Delta theta0，Δψ0，Δγ0Is the initial attitude angle error;
the above initial error Δ λ0，ΔL0，Δh0，ΔVE0，ΔVN0，ΔVU0，Δθ0，Δψ0，Δγ0Determined by the inertial navigation system initial alignment conditions.
The initial data calculation formula is as follows:
wherein,acceleration in the direction of X, Y axisThe measured value of degree, g, is the acceleration of gravity.
When the vehicle is in the initial state of linear motion, the acceleration of the vehicle in the X axial direction is the component of gravity in the axial direction, and the formulaCan calculate gamma 0, and the electronic compass can calculate theta according to gamma 0 and longitude and latitude0，ψ0。
The error sources of inertial navigation mainly include: errors caused by approximation of mathematical modeling (e.g., establishing quaternion differential equations under small angle rotation conditions of a vehicle), errors of inertial components (including mounting errors of inertial devices, scale factor errors, drift of a gyroscope and offset errors of an accelerometer), calculation errors, scale factor errors, drift of a gyroscope and offset errors of an accelerometer, calculation errors, initial alignment errors (errors mainly caused by inertia sensitive components): environmental errors (errors under environmental conditions such as vibration, shock, temperature, etc. of the vehicle).
Due to the influence of factors such as temperature, analog-to-digital conversion errors, interference signals and the like, when the MIMU is static, the gyroscope has zero value offset, and if the MIMU is not processed, the matrix offset directly calculated through a navigation algorithm is extremely large, so that the attitude angle, the azimuth angle, the speed and the longitude and latitude are extremely large. Generally, the compensation for the zero offset error is simple, and the zero offset error of the gyroscope in the whole operation process is usually compensated by adopting the average value of a section of stationary data after the gyroscope works stably. However, as the working time of the gyroscope increases, the ambient temperature changes and other factors affect, the zero offset of the gyroscope also generates obvious drift, and in order to remove the zero offset error more accurately, the invention provides a dynamic compensation method:
step 1) presetting the updating time T of a zero offset compensation factor;
and 2) judging the stationarity of the current signal. If the current signal is a stationary signal, the average value of the current segment of data can be taken to update the compensation factor, and if the current signal is a non-stationary signal. This update should be skipped.
The invention also discloses a method for compensating random drift error by adopting HDR algorithm, wherein the gyroscope outputs angular velocity signals, but due to the limitation of the gyroscope precision, the output angular velocity signals contain certain errors, and the errors comprise zero offset errors0And random drift errord. Random drift errordIt means that the random drift of the gyroscope, the increase of the operating time of the gyroscope, the change of the temperature environment, etc. will make the gyroscope rotate slightly and further make the deviation between the output value and the actual value, and these deviations are called random drift, which is also the main object of HDR estimation and compensation. OmegatrueFor true output values, in order to measure accurate ωtrueZero offset error must be removed from the measured data0And random drift errord. When the rotational angular velocity of the carrier is ωtrueAt time, the gyroscope actually outputs an angular velocity of ωtrue+0+d. Zero value offset error0Has been described above, so that the zero-value offset error compensated angular velocity is ωtrue+dThen, a double low-pass filter is used to solve the problem of swing during carrier motion, and the angular velocity after passing through the double low-pass filter becomes omega +d. The input is set to an angular velocity of 0, i.e. ωset0. Omega of the last momentiThe value is fed back to the set input in the form of negative feedback by a z-transform, on the one hand, to obtain the error signal E, and on the other hand, by an attenuated signal controller and an integral controller. The error signal E is integrated by an integral controller to obtain a compensation factor I. The obtained compensation factors I and omega +dAdding to obtain the angular velocity omega of the current momenti；
The gyroscope angular velocity compensated by the HDR algorithm is as follows:
ωi＝ω″+d+Iiand ω "is the angular velocity ωtrueAngular velocity through dual low pass filtersA value of the metric;
and (3) calculating a compensation factor:
Ii＝Ii-1-Aisign(ωi-1)ic，Ii-1is a compensation factor at the previous moment, IiFor the compensation factor at the current time, sign is the sign-taking function, icIs a constant number, AiIn order to be a function of the attenuation,
wherein ω isi-1Angular velocity, θ, at the previous momentωFor a set threshold, p is a set attenuation factor.
In order to accelerate the convergence speed, the small angle input is better identified, so that the error existing in theory is reduced, the accuracy of the algorithm is improved, and the threshold function is improved.
In the algorithm, the selection of the p value is critical, when the p value is selected to be larger, the convergence rate is faster, but the action range of HDR is reduced, and in practical application, only appropriate p and theta are selectedωThe output result is always closer to the real input, and the ideal angular speed output is obtained.
The invention integrates GPS and DR to form a GPS/DR combined navigation system, and makes use of the respective advantages of the GPS/DR combined navigation system through mutual compensation of the system, thereby obtaining the navigation precision and reliability superior to any single navigation system. Meanwhile, the optimal estimated value is calculated by adopting the combined Kalman filtering, in a multi-sensor system, the combined Kalman filtering can realize the optimal integration of multi-sensor information by utilizing an information distribution principle, and the whole system has certain fault-tolerant capability, so that the overall optimal performance can be obtained. The idea of the joint kalman filtering itself originates from solving the fault-tolerant and optimal information integration problem of the integrated navigation system. The integrated navigation system is a multi-sensor system consisting of two mutually independent subsystems of a GPS positioning system and an inertial navigation system, so that the optimal integration and mutual correction of positioning navigation information can be realized by applying the combined Kalman filtering technology to the vehicle-mounted integrated navigation system. However, if the inertial navigation system and the GPS output are directly filtered by the kalman filter, the equations are computationally expensive. However, if an indirect feedback method is adopted, the calculation period is extremely large, and the effective performance of filtering is not influenced. The method specifically comprises the step of correcting corresponding navigation parameters in the mechanical arrangement of the inertial navigation system by using a calculated value of an error of the inertial navigation system, namely feeding an error estimation value back to the interior of the inertial navigation system to obtain the optimal estimation of the navigation parameters.
The invention also discloses a method for further correcting the GPS positioning information and the positioning information of the DR system by utilizing the digital map matching technology, which comprises the following steps:
the map matching function disclosed by the invention is to select a matching track which is most likely to be driven by a vehicle and is positioned on some road sections of a road traffic network by comparing the vehicle driving track determined by the positioning signal with the geometric characteristics of the related driving road sections in the electronic map. This matching process is implemented by a certain matching algorithm.
The map matching algorithm flow of the invention is as follows:
step 1: and selecting a circle with a proper value as a radius and drawing the hidden circle by taking the vehicle point as the center of the circle, judging whether the circle is intersected with the objects in the road layer, and calculating that a plurality of objects in the road layer are intersected with the circle if the circle is intersected with the objects in the road layer. If more than one object is found, the circle radius is appropriately reduced, and if the road layer object which does not meet the condition is not found, the circle radius is appropriately increased until only one object which meets the condition is found, and the road field of the object is obtained. If the radius of the circle is larger than a certain threshold, the vehicle is considered to enter a certain area, such as a large square or a parking lot, and the center of the circle is used as a correction point to directly transfer to step 4.
Step 2: and judging whether the name of the road object in the current cycle is the same as that of the road object in the previous cycle, if so, indicating that the two points are on the same road, and turning to step 3. If the difference is not the same, the vehicle is likely to turn, but the vehicle is not judged to turn left or turn right, so the point is not processed, the point is skipped, and the road object closest to the vehicle point is recorded for the next cycle comparison. Take the next point and return to step 1.
Step 3: and reading all inflection points on the road object, calculating a foot from a vehicle point to a line segment formed by connecting two adjacent inflection points and the distance between the vehicle point and the foot, and taking the foot as a correction point if the foot is between the two adjacent inflection points and the distance is the minimum.
Step 4: and drawing a mark on the obtained correction point. And taking off a vehicle point and continuing running.
Compared with the prior art, the technical scheme of the invention has the following advantages:
1. the vehicle-mounted inertial navigation system directly reads information through the CAN bus of the vehicle audio interface, thereby avoiding refitting of the vehicle and improving the overall safety of the vehicle.
2. The invention improves the reliability of navigation and positioning by the dynamic compensation of zero offset error of the gyroscope and the compensation of random drift error.
3. The invention does not need to collect vehicle pulse signals, thereby further avoiding the collection error in the process of collecting pulses and converting the pulses into the vehicle speed and avoiding the problem of yaw.
4. The invention has the advantages of simple structure, low cost, convenient installation and the like.
5. The invention further corrects the GPS positioning information and the positioning information of the DR system by utilizing the indirect feedback of the Karl filtering and the digital map matching technology, thereby further improving the accurate reliability of navigation.
Drawings
FIG. 1 is a block diagram of the architecture of one embodiment of the present invention.
Fig. 2 is a CAN bus interface circuit in one embodiment of the invention.
Fig. 3 is a diagram of the steps of the zero offset error dynamic compensation of the present invention.
Fig. 4 is a flow chart of the random drift error compensation data processing of the present invention.
FIG. 5 is a schematic diagram of indirect feedback filtering using Karschner filtering according to the present invention.
Detailed Description
Referring to fig. 1, the vehicle-mounted inertial navigation system of the present invention includes: the main processor MCU is connected with a CAN bus of the vehicle sound interface through a CAN bus controller to read information, and the main processor is connected with the gyroscope through an SPI interface and connected with the GPS and the map through serial ports.
The main processor MCU of the invention selects LPC11C14 of ST company as the main processor to complete the functions of data processing, external module control and the like. The processor is a microcontroller based on ARM Cotex-M0, can be used for embedded applications with high integration level and low power consumption, and ARM Cotex-M0 is a second generation core and provides a simple instruction set to realize deterministic behavior. Operating frequency up to 50mhz the peripherals include up to 32KB of FLASH, 8KB of data storage. The CAN bus controller is connected with the CAN bus through the CAN transceiver. The CAN transceiver uses PCA82C250 to convert the differential voltage and level voltage of the CAN bus, is fully compatible with the ISO/DIS11898 standard, and the CHAN and CANL two wires also prevent electrical transients that may occur in a vehicle environment, and the CAN bus interface circuitry is shown in FIG. 2.
The gyroscope of the present invention is implemented using the chip L3G4200D from ST Italian semiconductor, the L3G4200D is a low power consumption triaxial gyroscope providing three alternative full scales (+ -250/+ -500/+ -2000 dps), the sensing element is designed using a special microfabrication process, IC, SPI interface technology realizes a special circuit design using CMOS, the L3G4200D is packaged using plastic (LGA) and provides excellent temperature stability, and the operating temperature range is extended to (-40 deg.C to +85 deg.C).
Initial conditions of the gyroscope of the invention are given as follows:
two initial states, a vehicle stationary state and a linear motion state, are considered, in which the following initial states need to be given:
1. given an initial position λ0，L0，h0Wherein is the true initial position of the carrier, Δ λ0，ΔL0，Δh0Is the initial position error;
2. given initial velocity VE0，VN0，VU0Wherein for the true initial velocity of the carrier, Δ VE0，ΔVN0，ΔVU0Is the initial velocity error;
3. given an initial attitude angle θ0，ψ0，γ0Wherein is the true initial attitude angle of the carrier, Delta theta0，Δψ0，Δγ0Is the initial attitude angle error;
the above initial error Δ λ0，ΔL0，Δh0，ΔVE0，ΔVN0，ΔVU0，Δθ0，Δψ0，Δγ0Determined by the inertial navigation system initial alignment conditions.
Due to the influence of factors such as temperature, analog-to-digital conversion errors, interference signals and the like, when the MIMU is static, the gyroscope has zero value offset, and if the MIMU is not processed, the matrix offset directly calculated through a navigation algorithm is extremely large, so that the attitude angle, the azimuth angle, the speed and the longitude and latitude are extremely large. Generally, the compensation for the zero offset error is simple, and the zero offset error of the gyroscope in the whole operation process is usually compensated by adopting the average value of a section of stationary data after the gyroscope works stably. However, as the operating time of the gyroscope increases, the ambient temperature changes, and other factors affect, the zero offset of the gyroscope also generates obvious drift, and in order to more accurately remove the zero offset error, the present invention provides a dynamic compensation method, which is shown in fig. 3:
step 1) presetting the updating time T of a zero offset compensation factor;
and 2) judging the stationarity of the current signal. If the current signal is a stationary signal, the average value of the current segment of data can be taken to update the compensation factor, and if the current signal is a non-stationary signal. This update should be skipped.
The invention also discloses a method for compensating the random drift error of the gyroscope, which adopts an HDR algorithm to design a closed-loop network, adds a double low-pass filter to remove the deviation generated by the swinging of the gyroscope, obviously reduces the random drift error of the gyroscope, reduces the noise of the gyroscope and improves the output precision of the gyroscope.
Referring to fig. 4, the present invention adopts HDR algorithm to compensate random drift error, and the gyroscope outputs angular velocity signal, but the output angular velocity signal contains one due to limitation of gyroscope precisionError of the stator, the error including zero-valued offset error0And random drift errord. Random drift errordIt means that the random drift of the gyroscope, the increase of the operating time of the gyroscope, the change of the temperature environment, etc. will make the gyroscope rotate slightly and further make the deviation between the output value and the actual value, and these deviations are called random drift, which is also the main object of HDR estimation and compensation. ω in FIG. 4trueFor true output values, in order to measure accurate ωtrueZero offset error must be removed from the measured data0And random drift errord. As can be seen from FIG. 4, when the angular velocity of rotation of the carrier is ωtrueAt time, the gyroscope actually outputs an angular velocity of ωtrue+0+d. Zero value offset error0Has been described above, so that the zero-value offset error compensated angular velocity is ωtrue+dThen, a double low-pass filter is used to solve the problem of swing during carrier motion, and the angular velocity after passing through the double low-pass filter becomes omega +d. The input is set to an angular velocity of 0, i.e. ωset0. Omega of the last momentiThe value is fed back to the set input in the form of negative feedback by a z-transform, on the one hand, to obtain the error signal E, and on the other hand, by an attenuated signal controller and an integral controller. The error signal E is integrated by an integral controller to obtain a compensation factor I. The obtained compensation factors I and omega +dAdding to obtain the angular velocity omega of the current momenti；
The gyroscope angular velocity compensated by the HDR algorithm is as follows:
ωi＝ω″+d+Iiand ω "is the angular velocity ωtrueAngular velocity values through the dual low pass filter;
and (3) calculating a compensation factor:
Ii＝Ii-1-Aisign(ωi-1)ic，Ii-1is a compensation factor at the previous moment, IiFor compensating for the current timeSign is a sign-taking function, icIs a constant number, AiIn order to be a function of the attenuation,
wherein ω isi-1Angular velocity, θ, at the previous momentωFor a set threshold, p is a set attenuation factor.
In order to accelerate the convergence speed, the small angle input is better identified, so that the error existing in theory is reduced, the accuracy of the algorithm is improved, and the threshold function is improved.
In the algorithm, the selection of the p value is critical, when the p value is selected to be larger, the convergence rate is faster, but the action range of HDR is reduced, and in practical application, only appropriate p and theta are selectedωThe output result is always closer to the real input, and the ideal angular speed output is obtained.
The invention integrates GPS and DR to form a GPS/DR combined navigation system, and makes use of the respective advantages of the GPS/DR combined navigation system through mutual compensation of the system, thereby obtaining the navigation precision and reliability superior to any single navigation system. Meanwhile, the optimal estimated value is calculated by adopting the combined Kalman filtering, in a multi-sensor system, the combined Kalman filtering can realize the optimal integration of multi-sensor information by utilizing an information distribution principle, and the whole system has certain fault-tolerant capability, so that the overall optimal performance can be obtained. The idea of the joint kalman filtering itself originates from solving the fault-tolerant and optimal information integration problem of the integrated navigation system. The integrated navigation system is a multi-sensor system consisting of two mutually independent subsystems of a GPS positioning system and an inertial navigation system, so that the optimal integration and mutual correction of positioning navigation information can be realized by applying the combined Kalman filtering technology to the vehicle-mounted integrated navigation system. However, if the inertial navigation system and the GPS output are directly filtered by the kalman filter, the equations are computationally expensive. However, if an indirect feedback method is adopted, the calculation period is extremely large, and the effective performance of filtering is not influenced. Specifically, the calculated value of the error of the inertial navigation system is used to correct the corresponding navigation parameter in the mechanical arrangement of the inertial navigation system, that is, the error estimation value is fed back to the interior of the inertial navigation system, so as to obtain the optimal estimation of the navigation parameter, see fig. 5.
The invention also discloses a method for further correcting the GPS positioning information and the positioning information of the DR system by utilizing the digital map matching technology, which comprises the following steps:
the map matching function disclosed by the invention is to select a matching track which is most likely to be driven by a vehicle and is positioned on some road sections of a road traffic network by comparing the vehicle driving track determined by the positioning signal with the geometric characteristics of the related driving road sections in the electronic map. This matching process is implemented by a certain matching algorithm.
The map matching algorithm flow of the invention is as follows:
step 1: and selecting a circle with a proper value as a radius and drawing the hidden circle by taking the vehicle point as the center of the circle, judging whether the circle is intersected with the objects in the road layer, and calculating that a plurality of objects in the road layer are intersected with the circle if the circle is intersected with the objects in the road layer. If more than one object is found, the circle radius is appropriately reduced, and if the road layer object which does not meet the condition is not found, the circle radius is appropriately increased until only one object which meets the condition is found, and the road field of the object is obtained. If the radius of the circle is larger than a certain threshold, the vehicle is considered to enter a certain area, such as a large square or a parking lot, and the center of the circle is used as a correction point to directly transfer to step 4.
Step 2: and judging whether the name of the road object in the current cycle is the same as that of the road object in the previous cycle, if so, indicating that the two points are on the same road, and turning to step 3. If the difference is not the same, the vehicle is likely to turn, but the vehicle is not judged to turn left or turn right, so the point is not processed, the point is skipped, and the road object closest to the vehicle point is recorded for the next cycle comparison. Take the next point and return to step 1.
Step 3: and reading all inflection points on the road object, calculating a foot from a vehicle point to a line segment formed by connecting two adjacent inflection points and the distance between the vehicle point and the foot, and taking the foot as a correction point if the foot is between the two adjacent inflection points and the distance is the minimum.
Step 4: and drawing a mark on the obtained correction point. And taking off a vehicle point and continuing running.
The vehicle-mounted inertial navigation system in the calculation scheme has quite high navigation precision and navigation reliability.
It will be appreciated by those skilled in the art that while the present invention has been disclosed in terms of preferred embodiments, it can be embodied in other specific forms without departing from the spirit or essential characteristics thereof. The above-described embodiments are to be considered in all respects only as illustrative and not restrictive. The scope of the invention is, therefore, indicated by the appended claims rather than by the foregoing description. All changes which come within the meaning and range of equivalency of the claims are to be embraced within their scope.
Claims (7)
1. The utility model provides a vehicle-mounted inertial navigation system, includes main processing unit MCU, gyroscope, GPS and map, its characterized in that: the main processor MCU is connected with a CAN bus of the vehicle sound interface through a CAN bus controller to read information, and is connected with the gyroscope through an SPI interface and is connected with the GPS and the map through a serial port.
2. The vehicle-mounted inertial navigation system according to claim 1, characterized in that the main processor MCU selects LPC11C14 from ST as the main processor, the gyroscope uses L3G4200D chip from ST semiconductor corporation, and the CAN transceiver uses PCA82C 250.
3. The in-vehicle inertial navigation system of claim 1 or 2, the gyroscope being given the following initial states in the vehicle stationary and linear motion states:
a) given an initial position λ0，L0，h0Wherein is the true initial position of the carrier, Δ λ0，ΔL0，Δh0Is the initial position error;
b) given initial velocity VE0，VN0，VU0Wherein for the true initial velocity of the carrier, Δ VE0，ΔVN0，ΔVU0Is the initial velocity error;
c) given an initial attitude angle θ0，ψ0，γ0Wherein is the real initial attitude angle of the carrier,Δθ0，Δψ0，Δγ0is the initial attitude angle error;
the above initial error Δ λ0，ΔL0，Δh0，ΔVE0，ΔVN0，ΔVU0，Δθ0，Δψ0，Δγ0The initial data calculation formula is determined by the initial alignment condition of the inertial navigation system as follows:
wherein,x, Y, g is the acceleration of gravity; when the vehicle is in the initial state of linear motion, the acceleration of the vehicle in the X axial direction is the component of gravity in the axial direction, and the formulaCan calculate gamma0Electronic compass according to gamma0Theta can be calculated by the sum of longitude and latitude0，ψ0。
4. The vehicle-mounted inertial navigation system according to claim 1 or 2, characterized in that a zero-value offset error of the gyroscope is compensated by a dynamic compensation method, and step 1) is to preset an update time T of a zero-value offset compensation factor; and 2) judging the stationarity of the current signal, if the current signal is a stationary signal, taking the average value of a current segment of data to update the compensation factor, and if the current signal is a non-stationary signal, skipping the updating.
5. The vehicle-mounted inertial navigation system according to claim 1 or 2, wherein the HDR algorithm is adopted to perform random drift error compensation, and the angular velocity of the gyroscope compensated by the HDR algorithm is:
ωi＝ω”+d+Iiand ω "is the angular velocity ωtrueAngular velocity value, omega, through a double low-pass filtertrueIs the true output value;
and (3) calculating a compensation factor:
Ii＝Ii-1-Aisign(ωi-1)ic，Ii-1is a compensation factor at the previous moment, IiFor the compensation factor at the current time, sign is the sign-taking function, icIs a constant number, AiIn order to be a function of the attenuation,
wherein ω isi-1Angular velocity, θ, at the previous momentωFor a set threshold, p is a set attenuation factor.
6. The vehicle-mounted inertial navigation system of claim 1 or 2, wherein the outputs of the inertial navigation system and the GPS positioning system are also fed back indirectly using a kalman filter to obtain an optimal estimate of the navigation parameters.
7. The vehicle-mounted inertial navigation system according to claim 1 or 2, further comprising a map matching technique, wherein the map matching algorithm flow is as follows:
step 1: if the radius of the circle is larger than a certain threshold, the vehicle is considered to enter a certain area at the moment, such as a relatively large square or a parking lot, and the center of the circle is taken as a correction point, and step4 is directly transferred;
step 2: judging whether the name of the road object in the current cycle is the same as that of the road object in the previous cycle, if so, indicating that two points are on the same road, turning to step3, if not, judging whether the vehicle turns to the left or to the right, so adopting a method of not processing the point, skipping the point, but still recording the road object closest to the vehicle point for next cycle comparison, taking the next point, and returning to step 1;
step 3: reading all inflection points on the road object, calculating a foot from a vehicle point to a line segment formed by connecting two adjacent inflection points and the distance between the vehicle point and the foot, and taking the foot as a correction point if the foot is between the two adjacent inflection points and the distance is the minimum;
step 4: and drawing a mark on the obtained correction point, taking down a vehicle point, and continuing to operate.
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