CN109849976A - A kind of train positioning system based on GPS, ODO and WKNN combination - Google Patents
A kind of train positioning system based on GPS, ODO and WKNN combination Download PDFInfo
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- CN109849976A CN109849976A CN201711241623.8A CN201711241623A CN109849976A CN 109849976 A CN109849976 A CN 109849976A CN 201711241623 A CN201711241623 A CN 201711241623A CN 109849976 A CN109849976 A CN 109849976A
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- location information
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Abstract
The present invention provides a kind of train positioning system based on GPS, ODO and WKNN combination, including train terminal, LTE communication network and monitoring center, the train terminal includes that ARM embedded system, ODO coding odometer, GPS module and LTE antenna, the GPS module obtain the geographical location information of train in real time；The ODO coding odometer obtains the mileage information of train in real time；The LTE antenna receives base station signal and by base station signal strength；The geographical location information of train, the mileage information of train and base station signal strength are sent monitoring center by the ARM embedded system；The monitoring center estimates train position using WKNN Indoor Position Techniques Based on Location Fingerprint according to base station signal strength, and obtains the location information of train after pre- estimation train position and received train geographical location information, mileage information are sent into Federated Kalman Filter.
Description
Technical field
The present invention relates to a kind of train positioning systems, specifically, relate to it is a kind of based on GPS, ODO and WKNN combination
Train positioning system.
Background technique
In current track traffic, the train locating method based on wheel shaft velocity sensor is more common, by measuring train
The revolving speed of wheel shaft calculates the speed of train, the displacement of train is obtained using time integral, to calculate the position of train.
Odometer wheel shaft method for locating speed measurement has many advantages, such as that measurement is simple, technology maturation, reliable and stable and relative accuracy is higher in short-term,
But to the rail traffic based on wheel track, when the frictional force deficiency between wheel and rail, it may occur that idle running or slipping phenomenon are led
Cause measurement train speed it is larger or even insincere with true train velocity deviation, seriously affect train operation availability and
Safety.
It can not work normally, or even can be made to system since the accidental failure of single positioning system will lead to whole system
At catastrophic consequence, such as based on odometer wheel shaft method for locating speed measurement, exists due to excessive slip and cause train unsceptered
The problem of, and the advantage of a variety of location technologies combination is to provide for system and more accurately may be used by redundancy, complementary information
The information leaned on.
In order to solve the above problems, people are seeking always a kind of ideal technical solution.
Summary of the invention
The purpose of the present invention is in view of the deficiencies of the prior art, combined to provide one kind based on GPS, ODO and WKNN
Train positioning system.
To achieve the goals above, the technical scheme adopted by the invention is that: it is a kind of based on GPS, ODO and WKNN combination
Train positioning system, including train terminal and monitoring center；
The train terminal includes ARM embedded system, ODO coding odometer, GPS module and LTE antenna, the ARM
Embedded system is connect with ODO coding odometer, the GPS module and the LTE antenna respectively；The GPS module is real
When obtain train geographical location information；The ODO coding odometer obtains the mileage information of train in real time；The LTE antenna
It receives base station signal and extracts the signal strength of base station；The ARM embedded system is by the geographical location information of train, train
Mileage information and base station signal strength are sent to monitoring center by LTE antenna in the form of short message after being packaged；
The monitoring center receives the mileage information and base of the train geographical location information of the LTE antenna transmission, train
It stands signal strength, train position is estimated using WKNN Indoor Position Techniques Based on Location Fingerprint according to base station signal strength, and will estimate column in advance
Truck position and received train geographical location information, mileage information obtain the position letter of train after being sent into Federated Kalman Filter
Breath, and train terminal is returned to by the LTE antenna.
Based on above-mentioned, the structure of Federated Kalman Filter is subfilter 1, subfilter 2, subfilter 3 and main filter
Wave device, train geographical location information are sent to senior filter after passing through subfilter 1, and the mileage information of train passes through subfilter
It is sent in senior filter after 2, the train position of WKNN Indoor Position Techniques Based on Location Fingerprint estimation is by being sent to master after subfilter 3
In filter, the optimal estimation location information with output train position after optimum fusion is updated by the time of senior filter.
The present invention has substantive distinguishing features outstanding and significant progress compared with the prior art, and specifically, the present invention will
GPS, ODO and WKNN are combined into a train positioning system, improve the precision of train positioning, optimize the property of positioning system
Can, while it is at low cost.
Detailed description of the invention
Fig. 1 is structural schematic diagram of the invention.
Fig. 2 is the structure chart of Federated Kalman Filter.
Specific embodiment
Below by specific embodiment, technical scheme of the present invention will be described in further detail.
As shown in Figure 1, a kind of train positioning system based on GPS, ODO and WKNN combination, including train terminal and monitoring
Center,
The train terminal includes ARM embedded system, ODO coding odometer, GPS module and LTE antenna, the GPS
Module obtains the geographical location information of train in real time；The ODO coding odometer obtains the mileage information of train in real time；It is described
LTE antenna receives base station signal and extracts the signal strength of base station；
The ARM embedded system beats the geographical location information of train, the mileage information of train and base station signal strength
Monitoring center is sent to by LTE antenna in the form of short message after packet；
The monitoring center receives the mileage information and base of the train geographical location information of the LTE antenna transmission, train
It stands signal strength, train position is estimated using WKNN Indoor Position Techniques Based on Location Fingerprint according to base station signal strength, and will estimate column in advance
Truck position and received train geographical location information, mileage information obtain the position letter of train after being sent into Federated Kalman Filter
Breath, and train terminal is returned to by the LTE antenna.
As shown in Fig. 2, the structure of Federated Kalman Filter is subfilter 1, subfilter 2, subfilter 3 and main filter
Wave device, train geographical location information are sent to senior filter after passing through subfilter 1, and the mileage information of train passes through subfilter
It is sent to after 2 after the train position that WKNN Indoor Position Techniques Based on Location Fingerprint is estimated in senior filter passes through subfilter 3 and is sent to master
In filter,Main system only does time update；It is updated and output train after optimum fusion by the time of senior filter
The optimal estimation location information of position.
Specifically, in GPS/ODO/WKNN bullet train integrated navigation system, using " current " statistics of motor-driven carrier
Model, wherein the state variable of system are as follows: X=[e, ve,ae,n,vn,an,εe,εn], it is train east orientation and north orientation position respectively
Coordinate components, speed air quantity, component of acceleration and error component, work as X1=X2=X3When=X, state equation is obtained:
X (k)=Φ (k, k-1) X (k-1)+U (k)+W (k)
Φ (k, k-1)=diag { Φe(k,k-1),Φn(k,k-1),Φεe(k,k-1),Φεn(k,k-1)}
Uk=[Ue,Un,Uεe,Uεn]T
Uεe=Uεn=0
Qk=E [WkWk T]=diag [2 λaeσae 2Qe,2λanσan 2Qn,2λεeσεe 2,2λεnσεn 2]
If sampling interval duration is very short, uniformly accelerated motion can be regarded in the same sampling period as, then have λae=λan=λεe=
λεn=0, then state-transition matrix is converted are as follows:
Φεe(k, k-1)=Φεn(k, k-1)=1
Train acceleration is " current " acceleration mean value, the one-step prediction of acceleration can be regarded as the equal of " current " acceleration
Value,
State equation simplifies are as follows:
X (k)=Φ (k, k-1) X (k-1)+W (k)
Φ (k, k-1)=diag { Φe(T),Φn(T),Φεe(T),Φεn(T)}
Φεe(T)=Φεn(T)=1
The measurement equation of local filter 1 are as follows:
Z1(k)=H1(k)X1(k)+W1(k)；
Observed quantity, observing matrix and observation noise are respectively as follows:
We(k)、Wn(k) be east orientation and north orientation position that GPS receiver arrives measurement noise, the respectively white Gaussian of zero-mean
Noise；The observation noise covariance matrix of local filter 1 is
The measurement equation of local filter 2 are as follows:
Z2(k)=H2(k)X2(k)+W2(k)；
Observed quantity, observing matrix and observation noise are respectively as follows:
WodoIt (k) is ODO odometer observation noise；The observation noise covariance matrix of local filter 1 is
The measurement equation of local filter 3 are as follows:
Z3(k)=H3(k)X3(k)+V3(k)；
Observed quantity, observing matrix and observation noise are respectively as follows:
vx(k)、vy(k) be WKNN location fingerprint positioning east orientation and north orientation measurement noise；std(error_wknnx),std
(error_wknny) be respectively east orientation and north orientation position error standard deviation；The observation noise covariance matrix of local filter 3
For R3=diag { (error_wknnx)2,(error_wknny)2}。
In self-adaptive GPS/ODO/WKNN adaptive federated filtering device, senior filter carries out three subfilter outputs
Information is merged and is reset；State estimation, evaluated error covariance matrix and the process noise covariance battle array of subfilter i be Xi, Pi,
Qi (i=1,2,3)；State estimation, evaluated error covariance matrix and the process noise covariance battle array of the senior filter of overall situation fusion
For Xg, Pg, Qg, the optimal State Estimation of system are as follows:
As can be seen from the above formula that the filtering of GPS/ODO/WKNN integrated navigation federal style is in fact in data fusion process
GPS/ODO integrated navigation merges with WKNN location information, and GPS location precision PDOP determines β1(k) size, β2(k),β3
(k) by comparing the coefficient for dynamically distributing ODO and WKNN subsystem to the error covariance of estimation, adaptive algorithm are as follows:
β3(k)=1- β1(k)-β2(k)
Finally it should be noted that: the above embodiments are merely illustrative of the technical scheme of the present invention and are not intended to be limiting thereof；To the greatest extent
The present invention is described in detail with reference to preferred embodiments for pipe, it should be understood by those ordinary skilled in the art that: still
It can modify to a specific embodiment of the invention or some technical features can be equivalently replaced；Without departing from this hair
The spirit of bright technical solution should all cover within the scope of the technical scheme claimed by the invention.
Claims (2)
1. a kind of train positioning system based on GPS, ODO and WKNN combination, it is characterised in that: including in train terminal and monitoring
The heart, the train terminal include ARM embedded system, ODO coding odometer, GPS module and LTE antenna, the ARM embedded
System is connect with ODO coding odometer, the GPS module and the LTE antenna respectively；The GPS module obtains in real time
The geographical location information of train；The ODO coding odometer obtains the mileage information of train in real time；The LTE antenna receives base
It stands and signal and extracts the signal strength of base station；The ARM embedded system believes the mileage of the geographical location information of train, train
Breath and base station signal strength are sent to monitoring center by LTE antenna in the form of short message after being packaged；
The monitoring center receives the train geographical location information of the LTE antenna transmission, the mileage information of train and base station letter
Number intensity estimates train position using WKNN Indoor Position Techniques Based on Location Fingerprint according to base station signal strength, and will estimate train position in advance
It sets and obtains the location information of train after being sent into Federated Kalman Filter with received train geographical location information, mileage information,
And train terminal is returned to by the LTE antenna.
2. a kind of train positioning system based on GPS, ODO and WKNN combination according to claim 1, it is characterised in that:
The structure of Federated Kalman Filter is subfilter 1, subfilter 2, subfilter 3 and senior filter, train geographical location
Information is sent to senior filter after passing through subfilter 1, and the mileage information of train is by being sent to senior filter after subfilter 2
In, the train position of WKNN Indoor Position Techniques Based on Location Fingerprint estimation after subfilter 3 by being sent in senior filter, by main filter
The time of wave device updates the optimal estimation location information with output train position after optimum fusion.
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| CN201711241623.8A CN109849976A (en) | 2017-11-30 | 2017-11-30 | A kind of train positioning system based on GPS, ODO and WKNN combination |
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Cited By (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110758472A (en) * | 2019-10-08 | 2020-02-07 | 北京市地铁运营有限公司地铁运营技术研发中心 | Train positioning method, device, system and storage medium |
| CN111486840A (en) * | 2020-06-28 | 2020-08-04 | 北京云迹科技有限公司 | Robot positioning method and device, robot and readable storage medium |
| CN113184020A (en) * | 2021-04-23 | 2021-07-30 | 卡斯柯信号有限公司 | Early warning monitoring display method for railway driving safety and construction safety protection |
| CN113259840A (en) * | 2021-05-15 | 2021-08-13 | 西南交通大学 | Train positioning system based on LTE performance parameters |
| CN117233818A (en) * | 2023-11-16 | 2023-12-15 | 中国铁路设计集团有限公司 | Method for enhancing stability of tamping car mileage positioning technology based on Beidou/GNSS |
-
2017
- 2017-11-30 CN CN201711241623.8A patent/CN109849976A/en not_active Withdrawn
Cited By (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110758472A (en) * | 2019-10-08 | 2020-02-07 | 北京市地铁运营有限公司地铁运营技术研发中心 | Train positioning method, device, system and storage medium |
| CN111486840A (en) * | 2020-06-28 | 2020-08-04 | 北京云迹科技有限公司 | Robot positioning method and device, robot and readable storage medium |
| CN113184020A (en) * | 2021-04-23 | 2021-07-30 | 卡斯柯信号有限公司 | Early warning monitoring display method for railway driving safety and construction safety protection |
| CN113184020B (en) * | 2021-04-23 | 2022-07-15 | 卡斯柯信号有限公司 | Early warning monitoring display method for railway driving safety and construction safety protection |
| CN113259840A (en) * | 2021-05-15 | 2021-08-13 | 西南交通大学 | Train positioning system based on LTE performance parameters |
| CN117233818A (en) * | 2023-11-16 | 2023-12-15 | 中国铁路设计集团有限公司 | Method for enhancing stability of tamping car mileage positioning technology based on Beidou/GNSS |
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