CN106840156B - A method of improving mobile phone inertial navigation performance - Google Patents
A method of improving mobile phone inertial navigation performance Download PDFInfo
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- CN106840156B CN106840156B CN201710194760.4A CN201710194760A CN106840156B CN 106840156 B CN106840156 B CN 106840156B CN 201710194760 A CN201710194760 A CN 201710194760A CN 106840156 B CN106840156 B CN 106840156B
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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
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
- G01C25/00—Manufacturing, calibrating, cleaning, or repairing instruments or devices referred to in the other groups of this subclass
- G01C25/005—Manufacturing, calibrating, cleaning, or repairing instruments or devices referred to in the other groups of this subclass initial alignment, calibration or starting-up of inertial devices
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- Radar, Positioning & Navigation (AREA)
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Abstract
The present invention relates to a kind of methods for improving mobile phone inertial navigation performance, comprising the following steps: cloud server calculates this approximate velocity of target vehicle, broadcasts and gives user hand generator terminal；Carry out quality control；Judge whether the distance calculated has reached length of tunnel, if it is progress position locking；Error is calculated using Kalman filter if not user hand generator terminal, and mobile phone inertial navigation is modified, user hand generator terminal exports target vehicle position.The present invention realizes on-line velocity amendment, and the positioning accuracy to promote mobile phone inertial navigation in tunnel is used together with map match；It realizes the tunnel placement under mobile phone non-navigational mode, location error is effectively reduced.
Description
Technical field
The present invention relates to a kind of vehicle positioning system localization method more particularly to a kind of improve mobile phone inertial navigation performance
Method.
Background technique
Mobile phone inertial navigation technology can help mobile phone in the environment that satellite-signal is lost (such as tunnel, underground garage)
Continue to position, promote the effective percentage of mobile phone positioning, which mainly utilizes MEMS sensor built in mobile phone (three-axis gyroscope, three
Axis accelerometer), by way of strap-down inertial with GPS (Global Positioning System, global positioning system
System) positioning progress loose coupling, the seamless connection of mobile phone positioning may be implemented.There are errors for device itself due to sensor, should
Error can constantly accumulate within the time that satellite-signal is lost, make the precision of mobile phone inertial navigation as time increases without
Disconnected diverging, the method for promoting mobile phone inertial navigation positioning accuracy at present mainly have: odometer auxiliary, magnetometer auxiliary, image are auxiliary
It helps.But the calculated car speed of cloud server is not utilized to promote mobile phone inertial navigation positioning accuracy.
Also it is positioned in tunnel under the with good grounds Mobile Telephone Gps mode using Online Map, tunnel placement under navigation mode
Technical principle is mainly the route for passing through map match and having planned, there are also the speed of access tunnel, according to simplest
Dead reckoning carries out two-dimensional position recursion with the course information of map and the velocity information of vehicle access tunnel, thus
Realize tunnel placement.But it needs mobile phone to be under navigation mode, and to have planned route on mobile phone in advance.
Summary of the invention
In view of the above-mentioned problems, the present invention proposes a kind of method for improving mobile phone inertial navigation performance, comprising the following steps:
S1: cloud server obtains the rate pattern of target vehicle process of passing through tunnel and the length in tunnel according to previous data
Degree, and calculate target vehicle this passes through the approximate velocity in the same tunnel, cloud server is long by approximate velocity and tunnel
Degree is broadcast by internet gives user hand generator terminal；
S2: user hand generator terminal receives the approximate velocity and length of tunnel that cloud server is broadcast, and carries out quality control, if
Approximate velocity is unsatisfactory for quality control, then return step S1；
S3: whether the distance for judging that user hand generator terminal inertial navigation calculates has reached length of tunnel, if it is executes step
Rapid S5, if not thening follow the steps S4；
S4: error is calculated using Kalman filter in user hand generator terminal, and is modified to mobile phone inertial navigation, and
Go to step S6；
S5: position locking is carried out, and anchor point is locked in tunnel face, until target vehicle receives GPS signal again；
S6: user hand generator terminal exports target vehicle position.
Quality control is carried out by following judgment rule:
Vb/ x < Va< VbX < k；
Wherein VaIndicate the approximate velocity that cloud server is broadcast, vbIndicate speed of the target vehicle into tunnel face, x expression
Experience value coefficient, value are that 3~5, k indicates that maximum speed limit, range are 180km/h~200km/h.
Step S4 the following steps are included:
S41: carry out Kalman filter calculating, according to mobile phone inertial navigation calculate position and map match position it
Between alternate position spike, estimate the location error of mobile phone inertial navigation, and opsition dependent error carries out feedback to mobile phone inertial navigation and repairs
Just；
S42: carrying out Kalman filter calculating, and the approximate velocity broadcast using cloud server is pushed away with mobile phone inertial navigation
Difference between the speed of calculation estimates the velocity error of inertial navigation, and feeds back by velocity error to mobile phone inertial navigation
Amendment；
S43: carrying out Kalman filter calculating, is calculated using the GPS position and speed provided and mobile phone inertial navigation
Difference between position and speed, estimation mobile phone go out location error, velocity error, attitude error, the gyro zero bias of inertial navigation
Error, accelerometer bias error carry out feedback modifiers to mobile phone inertial navigation.
Technical solution of the present invention realize the utility model has the advantages that
The present invention obtains vehicle approximate velocity and cloud server by machine learning using cloud server and calculates in advance
Good length of tunnel is issued to mobile phone terminal by internet, realizes on-line velocity amendment, and be used together to mention with map match
Rise positioning accuracy of the mobile phone inertial navigation in tunnel.It realizes the tunnel placement under mobile phone non-navigational mode, position is effectively reduced
Error, can significantly be promoted mobile phone inertial navigation under tunnel, overhead, by high building, the positioning accuracy of underground garage.
Detailed description of the invention
Fig. 1 is a kind of flow chart for the method for improving mobile phone inertial navigation performance of the present invention.
Fig. 2 is a kind of schematic diagram for the method for improving mobile phone inertial navigation performance of the present invention.
Specific embodiment
In the following with reference to the drawings and specific embodiments, the present invention is further explained, and the embodiment of the present invention is only to illustrate this hair
The protection scope that bright technical solution is not intended to limit the present invention.
As shown in Figure 1, the present invention proposes a kind of method for improving mobile phone inertial navigation performance, comprising the following steps:
The following steps are included:
S1: cloud server obtains the rate pattern of target vehicle process of passing through tunnel and the length in tunnel according to previous data
Degree, and calculate target vehicle this passes through the approximate velocity in the same tunnel, cloud server is long by approximate velocity and tunnel
Degree is broadcast by internet gives user hand generator terminal；
S2: user hand generator terminal receives the approximate velocity and length of tunnel that cloud server is broadcast, and carries out quality control, if
Approximate velocity is unsatisfactory for quality control, then return step S1；
S3: whether the distance for judging that user hand generator terminal inertial navigation calculates has reached length of tunnel, if it is executes step
Rapid S5, if not thening follow the steps S4；
S4: error is calculated using Kalman filter in user hand generator terminal, and is modified to mobile phone inertial navigation, and
Go to step S6；
S5: position locking is carried out, and anchor point is locked in tunnel face, until target vehicle receives GPS signal again；
S6: user hand generator terminal exports target vehicle position.
Quality control is carried out by following judgment rule:
Vb/ x < Va< VbX < k；
Wherein vaIndicate the approximate velocity that cloud server is broadcast, vbIndicate speed of the target vehicle into tunnel face, x expression
Experience value coefficient, value are that 3~5, k indicates that maximum speed limit, range are 180km/h~200km/h.
As shown in Fig. 2, step S4 the following steps are included:
S41: carrying out Kalman filter 1 and calculate, the position of the position and map match that are calculated according to mobile phone inertial navigation
Between alternate position spike, estimate the location error of mobile phone inertial navigation, and opsition dependent error feeds back mobile phone inertial navigation
Amendment improves the position precision of mobile phone inertial navigation；
S42: carrying out Kalman filter 2 and calculate, the approximate velocity and mobile phone inertial navigation broadcast using cloud server
Difference between the speed of reckoning estimates the velocity error of mobile phone inertial navigation, and by velocity error to mobile phone inertial navigation into
Row feedback modifiers improve the velocity accuracy of mobile phone inertial navigation；
S43: carrying out the calculating of main card Thalmann filter, is calculated using the GPS position and speed provided and mobile phone inertial navigation
Position and speed between difference, estimate the location error of inertial navigation, velocity error, attitude error, gyro zero bias and miss
Difference, accelerometer bias error carry out feedback modifiers to mobile phone inertial navigation, improve the position and speed essence of mobile phone inertial navigation
Degree.
The input of Kalman filter 1 is the alternate position spike of inertial navigation and map match, and output is inertial navigation system
Parameter error (parameter includes position, velocity error, attitude error, gyro zero offset error, accelerometer bias error)；
The input of Kalman filter 2 is the speed difference of the speed that cloud server is broadcast and inertial navigation speed, output
It is the parameter error of inertial navigation system (parameter includes position, speed, posture, gyro zero bias, accelerometer bias)；
The input of main card Thalmann filter is the location error and velocity error of GPS and inertial navigation, and output is that inertia is led
The parameter error of boat system (parameter includes position, speed, posture, gyro zero bias, accelerometer bias).
Following approximate velocity update equation, which is realized, calculates error using Kalman filter:
Zk=HkXk+ek
Wherein,ekIndicate random measurement
Noise, Xk=(δ rnδvnεnδbgyroδbacc)3×15, at the subscript k expression k moment, subscript b indicates carrier coordinate system, n expression navigation seat
Mark system, subscript x, y, z indicate three axial directions of carrier coordinate system x, y, z,Indicate carrier coordinate system X-axis velocity error,Table
Show carrier coordinate system Y-axis velocity error,Indicate carrier coordinate system Z axis velocity error,Indicate that navigational coordinate system is sat to carrier
Mark the direction cosine matrix of system, vnThe multiplication cross antisymmetric matrix of × expression navigational coordinate system speed, δ rnIndicate navigational coordinate system position
Set error, δ vnIndicate navigational coordinate system velocity error, εnIndicate that navigation is attitude error, δ bgyroIndicate gyroscope zero offset error,
δbaccIndicate accelerometer bias error.
If the limitation of only on-line velocity amendment and length of tunnel, the performance of mobile phone inertial navigation can only reduce longitudinal position
Error is set, and normal direction location error still has, therefore on-line velocity amendment needs to be used together ability with map match really
Improve the stationkeeping ability of mobile phone inertial navigation.
The speed that the speed and length of tunnel and inertial navigation issued using cloud server is calculated carries out Kalman filtering
Fusion can be estimated to obtain velocity error, carry out feedback modifiers to inertial navigation speed, improve forward speed precision, and then improve
Lengthwise position precision, meanwhile, the position of inertial navigation is modified using Online Map matched result, normal direction can be improved
Position precision, therefore the two combination can significantly promote performance of the mobile phone inertial navigation in tunnel.
Claims (2)
1. a kind of method for improving mobile phone inertial navigation performance, it is characterised in that the following steps are included:
S1: cloud server obtains the rate pattern and length of tunnel of target vehicle process of passing through tunnel according to previous data, and counts
Calculating target vehicle, this passes through the approximate velocity in the same tunnel, and the cloud server is by the approximate velocity and the tunnel
Road length is broadcast by internet and gives user hand generator terminal；
S2: the user hand generator terminal receives the approximate velocity and the length of tunnel that the cloud server is broadcast, and carries out
Quality control, if the approximate velocity is unsatisfactory for the quality control, return step S1；
S3: whether the distance for judging that the user hand generator terminal inertial navigation calculates has reached the length of tunnel, if it is holds
Row step S5, if not thening follow the steps S4；
S4: error is calculated using Kalman filter in the user hand generator terminal, is modified to mobile phone inertial navigation, and jump
Go to step S6；
S5: position locking is carried out, and anchor point is locked in the tunnel face, until the target vehicle receives GPS again
Signal；
S6: the user hand generator terminal exports the target vehicle position；
The quality control is carried out by following judgment rule:
vb/ X < va< vbX < k；
Wherein vaIndicate the approximate velocity that the cloud server is broadcast, vbIndicate the target vehicle into tunnel face speed
Degree, x indicate experience value coefficient, and value is that 3~5, k indicates that maximum speed limit, range are 180km/h~200km/h.
2. the method according to claim 1 for improving mobile phone inertial navigation performance, it is characterised in that the step S4 includes
Following steps:
S41: carrying out Kalman filter calculating, the position of the position and map match that are calculated according to the user mobile phone inertial navigation
Alternate position spike between setting estimates the location error of the mobile phone inertial navigation, and used to the mobile phone by the location error
Property navigation carry out feedback modifiers；
S42: carrying out Kalman filter calculating, and the approximate velocity broadcast using the cloud server and the mobile phone are used
Property the speed that calculates of navigation between difference estimate the velocity error of the mobile phone inertial navigation, and press the velocity error pair
The mobile phone inertial navigation carries out feedback modifiers；
S43: carrying out Kalman filter calculating, is calculated using the GPS position and speed provided and the mobile phone inertial navigation
Difference between position and speed estimates the location error, velocity error, attitude error, gyro of the mobile phone inertial navigation
Zero offset error, accelerometer bias error carry out feedback modifiers to the mobile phone inertial navigation.
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| CN107943859B (en) * | 2017-11-07 | 2021-07-30 | 千寻位置网络有限公司 | System and method for collecting, processing and feeding back mass sensor data |
| CN108121003A (en) * | 2017-12-26 | 2018-06-05 | 湖南迈克森伟电子科技有限公司 | Integrated navigation precise positioning system |
| CN113554890A (en) * | 2021-06-30 | 2021-10-26 | 东风汽车集团股份有限公司 | Navigation enhancement system and method based on 5G communication under tunnel working condition |
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| CN102928816A (en) * | 2012-11-07 | 2013-02-13 | 东南大学 | High-reliably integrated positioning method for vehicles in tunnel environment |
| CN104020441A (en) * | 2014-06-17 | 2014-09-03 | 东南大学 | Two-dimensional vehicle positioning method in tunnel environment and based on radio frequency identification |
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| JP5372802B2 (en) * | 2010-02-24 | 2013-12-18 | クラリオン株式会社 | Navigation device with tunnel position estimation function |
| CN103033184B (en) * | 2011-09-30 | 2014-10-15 | 迈实电子(上海)有限公司 | Error correction method, device and system for inertial navigation system |
| CN103499350B (en) * | 2013-09-28 | 2016-01-27 | 长安大学 | Vehicle high-precision localization method and the device of multi-source information is merged under GPS blind area |
| CN106143367A (en) * | 2015-04-27 | 2016-11-23 | 戴姆勒大中华区投资有限公司 | A kind of tunnel passes through aid system |
| US10304331B2 (en) * | 2015-06-25 | 2019-05-28 | Here Global B.V. | Method and apparatus for determining an estimated traffic congestion status of a tunnel based on probe data |
| CN105628024B (en) * | 2015-12-29 | 2018-09-04 | 中国电子科技集团公司第二十六研究所 | Single positioning navigator based on Multi-sensor Fusion and positioning navigation method |
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| CN102928816A (en) * | 2012-11-07 | 2013-02-13 | 东南大学 | High-reliably integrated positioning method for vehicles in tunnel environment |
| CN104020441A (en) * | 2014-06-17 | 2014-09-03 | 东南大学 | Two-dimensional vehicle positioning method in tunnel environment and based on radio frequency identification |
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