CN113335341A - Train positioning system and method based on GNSS and electronic map topological structure - Google Patents
Train positioning system and method based on GNSS and electronic map topological structure Download PDFInfo
- Publication number
- CN113335341A CN113335341A CN202110597668.9A CN202110597668A CN113335341A CN 113335341 A CN113335341 A CN 113335341A CN 202110597668 A CN202110597668 A CN 202110597668A CN 113335341 A CN113335341 A CN 113335341A
- Authority
- CN
- China
- Prior art keywords
- train
- positioning
- module
- data
- electronic map
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
- 238000000034 method Methods 0.000 title claims abstract description 25
- 239000011159 matrix material Substances 0.000 claims description 12
- 238000004364 calculation method Methods 0.000 claims description 7
- 238000001914 filtration Methods 0.000 claims description 7
- 238000012937 correction Methods 0.000 claims description 6
- 238000005259 measurement Methods 0.000 claims description 4
- 239000012634 fragment Substances 0.000 claims description 3
- 238000012216 screening Methods 0.000 claims description 3
- 238000010276 construction Methods 0.000 abstract description 3
- 238000012423 maintenance Methods 0.000 abstract description 3
- 238000005516 engineering process Methods 0.000 description 3
- 238000010586 diagram Methods 0.000 description 2
- 238000006467 substitution reaction Methods 0.000 description 2
- 230000007547 defect Effects 0.000 description 1
- 238000001514 detection method Methods 0.000 description 1
- 238000002620 method output Methods 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 238000012544 monitoring process Methods 0.000 description 1
- 238000012545 processing Methods 0.000 description 1
- 238000011160 research Methods 0.000 description 1
- 238000005070 sampling Methods 0.000 description 1
- 230000007704 transition Effects 0.000 description 1
- 239000002699 waste material Substances 0.000 description 1
Images
Classifications
-
- B—PERFORMING OPERATIONS; TRANSPORTING
- B61—RAILWAYS
- B61L—GUIDING RAILWAY TRAFFIC; ENSURING THE SAFETY OF RAILWAY TRAFFIC
- B61L25/00—Recording or indicating positions or identities of vehicles or trains or setting of track apparatus
- B61L25/02—Indicating or recording positions or identities of vehicles or trains
Landscapes
- Engineering & Computer Science (AREA)
- Mechanical Engineering (AREA)
- Navigation (AREA)
- Position Fixing By Use Of Radio Waves (AREA)
Abstract
The invention relates to a train positioning system and method based on a GNSS and an electronic map topological structure, which comprises a GNSS satellite positioning receiver module, a Kalman filter module, a map matching algorithm module and a vehicle-mounted electronic map module; the GNSS satellite positioning receiver module is connected with the map matching algorithm module through the Kalman filter module, and the map matching algorithm module is connected with the vehicle-mounted electronic map module; the map matching algorithm module accurately matches the train positioning data output by the Kalman filter module to a certain track segment in the electronic map of the vehicle-mounted electronic map module, so that the train is accurately positioned. Compared with the prior art, the method has the advantages of reducing the dependence of a positioning algorithm on ground equipment, reducing the construction cost and the labor maintenance cost of local railways and the like.
Description
Technical Field
The invention relates to a train positioning technology, in particular to a train positioning system and method based on a GNSS and an electronic map topological structure.
Background
The train automatic protection system is key equipment for ensuring the safe operation of a train and realizing overspeed protection, and the train positioning technology is an important basis for realizing the running control and the state monitoring of the train automatic protection system. The research on the precise positioning of the high-speed railway train has important significance for optimizing the railway operation efficiency and improving the railway operation safety coefficient.
The positioning method commonly applied in the railway industry at present is a positioning method based on a wheel diameter speed sensor, a track circuit and an entity transponder, which is adopted in a train control system of a CTCS-2/3 level system. The traditional positioning method realizes train occupation detection by installing a large number of transponders on a railway line and laying a track circuit, thereby greatly increasing the railway construction cost and the maintenance cost.
The method applies a common vehicle-mounted navigation algorithm to a railway system, the vehicle-mounted GNSS/INS integrated navigation system outputs train positioning information in real time, and the positioning information is matched with a preset reference point in a vehicle-mounted electronic map and is subjected to projection calculation to obtain the current mileage of a train. The introduction of the GNSS satellite positioning system greatly reduces the dependence of train positioning algorithm on ground equipment, and improves the precision of real-time train positioning.
The traditional map matching method comprises a point-to-point map matching algorithm, a point-to-line map matching algorithm and a line-to-line map matching algorithm, wherein the point-to-point map matching algorithm has the advantages of simple algorithm and easiness in implementation, but the matching precision is poor. Although the point-to-line map matching algorithm and the line-to-line map matching algorithm have high matching accuracy, the algorithms are complex and have poor real-time performance.
Therefore, how to combine satellite positioning and an electronic map to realize accurate train positioning becomes a technical problem to be solved.
Disclosure of Invention
The present invention aims to overcome the defects of the prior art and provide a train positioning system and method based on GNSS and electronic map topology.
The purpose of the invention can be realized by the following technical scheme:
according to one aspect of the invention, a train positioning system based on a GNSS and an electronic map topological structure is provided, which comprises a GNSS satellite positioning receiver module, a Kalman filter module, a map matching algorithm module and a vehicle-mounted electronic map module; the GNSS satellite positioning receiver module is connected with the map matching algorithm module through the Kalman filter module, and the map matching algorithm module is connected with the vehicle-mounted electronic map module;
the map matching algorithm module accurately matches the train positioning data output by the Kalman filter module to a certain track segment in the electronic map of the vehicle-mounted electronic map module, so that the train is accurately positioned.
As a preferred technical scheme, the GNSS satellite positioning receiver module is installed at the head position of the train and is used for receiving positioning signals of the GNSS navigation system in real time, resolving the real-time positioning data of the train and outputting the real-time positioning data to the Kalman filter module.
As a preferred technical scheme, the output data of the GNSS satellite positioning receiver module is a series of longitude and latitude information representing the position of a train, and the output data is Rgnss(t)＝(Lon(t),Lat(t)), wherein Lon(t) longitudinal positioning data of train at time t, Lat(t) represents train positioning latitudinal direction positioning data at time t.
As an optimal technical scheme, the Kalman filter module is used for filtering train positioning data output by the GNSS satellite positioning receiver module, eliminating invalid values in the positioning data and outputting the filtered train positioning data and the covariance matrix to the map matching algorithm module.
As a preferred technical solution, the filtering process of the kalman filter module specifically includes:
at the moment of k +1, the Kalman filter receives positioning data Z input by the GNSS satellite positioning receiver modulek+1The Kalman filter module firstly predicts a covariance matrix P of the Kalman filter at the moment of k +1 according to the working state of the GNSS satellite positioning receiver modulek+1/kAnd last moment effective positioning data Xk/kJudging the data validity of the positioning data; if the data is judged to be invalid, the positioning data is rejected; if the data is judged to be valid, the positioning data is brought into a filter to carry out position correction calculation;
under the condition that the input data is effective, the Kalman filter module corrects train positioning data Xk+1/k+1And correcting the covariance matrix Pk+1/k+1And outputting the data to a map matching algorithm module.
As a preferable technical scheme, the vehicle-mounted electronic map module is an electronic map database formed by longitude and latitude information of a large number of reference points measured on a track on which a train runs by a vehicle-mounted high-precision positioning and measuring system.
As a preferred technical scheme, the electronic map database adopts a hierarchical topological structure to establish an index structure of an electronic map, wherein the three-level structure is a station, a track and a track segment respectively.
As a preferred technical solution, the hierarchical topology of the electronic map includes:
the first-level station structure stores the following information: station number, number of rails under the jurisdiction of the station, number of the rails, and longitude and latitude range under the jurisdiction of the station;
a secondary track structure storing the following information: the method comprises the following steps of (1) track numbering, track superior station numbering, track starting point longitude and latitude and mileage, track end point longitude and latitude and mileage, track administered longitude and latitude range and track administered fragment numbering;
a three-level track segment structure storing the following: track segment number, superior track number, superior station number, starting point longitude and latitude and mileage, and ending point longitude and latitude and mileage.
As a preferred technical solution, the matching process of the map matching algorithm module specifically includes:
firstly, calculating a confidence interval error ellipse of the positioning data;
secondly, screening track segments to be matched which meet the conditions;
thirdly, calculating a matching error function with a matching track segment, and selecting the track segment with the minimum error function as a matching result;
and fourthly, converting the two-dimensional positioning data into one-dimensional mileage data to be used as the output of the train positioning system.
According to another aspect of the present invention, there is provided a train positioning method based on GNSS and electronic map topology, comprising the following steps:
step 101: acquiring current positioning data of the train;
step 102: judging whether the positioning data is valid, if so, executing step 103; otherwise, go to step 109;
step 103: inputting the positioning data into a Kalman filter module for filtering correction;
step 104: establishing a confidence interval to screen candidate track segments;
step 105: judging whether the number of the candidate track segments is greater than 0, if so, executing step 106; otherwise, go to step 109;
step 106: calculating the matching error function values from the positioning points to the candidate track segments one by one;
step 107: selecting the track segment with the minimum function value as a matching result;
step 108: converting the two-dimensional positioning data into one-dimensional mileage data as the output of a train positioning system;
step 109: the current satellite positioning is not available and the next set of data is awaited.
Compared with the prior art, the invention has the following advantages:
1) the invention reduces the dependence of the positioning technology on ground equipment and lightens the construction cost and the manpower maintenance cost of the local railway.
2) The invention utilizes the hierarchical topological structure of the electronic map, effectively avoids the waste of computing resources caused by comparing a large number of reference points one by one in the positioning process, and realizes the real-time performance and the accuracy of the map matching algorithm.
3) The invention is easy to realize, and the subsequent train can realize the positioning algorithm by depending on the satellite positioning receiving equipment and the vehicle-mounted electronic map only by using the high-precision positioning equipment for one-time positioning measurement on the local railway.
Drawings
FIG. 1 is a schematic diagram of a positioning system according to the present invention;
FIG. 2 is a schematic diagram of the track fragment processing of the present invention;
fig. 3 is a flow chart of the operation of the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are some, not all, embodiments of the present invention. All other embodiments, which can be obtained by a person skilled in the art without any inventive step based on the embodiments of the present invention, shall fall within the scope of protection of the present invention.
As shown in fig. 1, the train positioning system based on GNSS and electronic map topology of the present invention includes a GNSS satellite positioning receiver module, a kalman filter module, a map matching algorithm module, and a vehicle-mounted electronic map module; the GNSS satellite positioning receiver module is connected with the map matching algorithm module through the Kalman filter module, and the map matching algorithm module is connected with the vehicle-mounted electronic map module; the map matching algorithm module accurately matches the train positioning data output by the Kalman filter module to a certain track segment in the electronic map of the vehicle-mounted electronic map module, so that the train is accurately positioned.
The GNSS satellite positioning receiver module is an input module of a train positioning algorithm. Receiver mountingAnd the train head position is responsible for receiving positioning signals of the GNSS navigation system in real time, resolving the real-time train positioning data and outputting the real-time train positioning data to the Kalman filter module. The output data of the GNSS satellite positioning receiver module is a series of longitude and latitude information representing the position of the train, and the output data is recorded as Rgnss(t)＝(Lon(t),Lat(t)), wherein Lon(t) longitudinal positioning data of train at time t, Lat(t) represents train positioning latitudinal direction positioning data at time t.
The Kalman filter module is responsible for filtering train positioning data input by the GNSS satellite positioning receiver module, eliminating invalid values in the positioning data and outputting the filtered train positioning data and the covariance matrix to the map matching algorithm module.
The Kalman filter calculation formula is as follows:
Xk+1/k＝Ak+1/kXk/k(1)
Xk+1/k+1＝Xk+1/k+Kk+1(Zk+1-Hk+1Xk+1/k) (3)
Pk+1/k+1＝(I-Kk+1Hk+1)Pk+1/k (4)
at the moment of k +1, the Kalman filter receives positioning data Z input by the GNSS satellite positioning receiver modulek+1The Kalman filter module firstly predicts a covariance matrix P of the Kalman filter at the moment of k +1 according to the working state of the GNSS satellite positioning receiverk+1/kAnd last moment effective positioning data Xk/kAnd judging the data validity of the positioning data. If the data is judged to be invalid, the positioning data is rejected; if the data is judged to be valid, positioning the dataThe substitution filter performs a position correction calculation.
The state variables of the kalman filter are:
the constant coefficient state transition matrix is:
the measurement matrix is:
Hk+1＝[1 1 0 0]T
under the condition that the input data is effective, the Kalman filter module corrects train positioning data Xk+1/k+1And correcting the covariance matrix Pk+1/k+1And outputting the data to a map matching algorithm module.
The electronic map module is an electronic map database formed by longitude and latitude information of a large number of reference points measured on a track where a train runs by a vehicle-mounted high-precision positioning and measuring system. The database adopts a hierarchical topological structure to establish an index structure of an electronic map, and the three-level structure is a station (station), a track (track) and a track segment (piece). The track segments (piece) are the most basic structure of the electronic map, each track segment is about 50-100 m long and consists of a starting point and an end point. Since the sampling is sufficiently dense, the trajectory between the two reference points can be considered to be a straight line. And the electronic map module is responsible for providing data support for the map matching algorithm module.
The hierarchical topology structure of the electronic map comprises: the first-level station structure stores the following information: station number, number of tracks and track number under the jurisdiction of the station, and longitude and latitude range under the jurisdiction of the station (namely, the maximum value and the minimum value of the longitude and latitude in all track segments). A secondary track structure storing the following information: the track number, the track superior station number, the track starting point longitude and latitude and mileage, the track end point longitude and latitude and mileage, the track administered longitude and latitude range (namely the maximum value and the minimum value of the longitude and latitude in all track segments), and the track administered all track segments number. A three-level track segment structure storing the following: track segment number, superior track number, superior station number, starting point longitude and latitude and mileage, and ending point longitude and latitude and mileage, as shown in table 1.
TABLE 1
And the map matching algorithm module is responsible for accurately matching the train positioning data output by the Kalman filter module to a certain track segment in the electronic map. The matching process can be divided into four steps: firstly, calculating a confidence interval error ellipse of the positioning data; secondly, screening track segments to be matched which meet the conditions; thirdly, calculating a matching error function with a matching track segment, and selecting the track segment with the minimum error function as a matching result; and fourthly, converting the two-dimensional positioning data into one-dimensional mileage data to be used as the output of a train positioning algorithm.
1) And positioning a data confidence interval error ellipse, which is hereinafter referred to as an error ellipse.
The data of the train satellite positioning is affected by a plurality of errors, including satellite orbit errors, satellite clock errors, relativistic effects and the like related to the satellite, ionospheric delay, tropospheric delay, shielding of satellite signals, multipath effects and the like suffered by the satellite signals in the atmospheric layer propagation process, and further including receiver clock errors, receiver hardware delay, measurement noise and the like related to the receiver. On a two-dimensional plane, the positioning error appears as an infinite number of error ellipses of equal probability density. The size of the ellipse depends on the covariance matrix of the positioning data.
And (3) taking the corrected satellite positioning data output by the Kalman filter module as the circle center, selecting coordinate axes along the longitude and latitude directions, and constructing a coordinate system, wherein the relevant parameters of the error ellipse are as follows:
in the above formula, a represents a semimajor axis of the error ellipse, b represents a semiminor axis of the error ellipse, and α represents a deflection angle of the error ellipse with respect to the longitudinal direction; sigmalonIndicating the standard deviation, σ, of the longitudinal direction of the positioning datalatStandard deviation, σ, representing the latitudinal direction of the positioning datalonlatRepresenting the covariance of the positioning data. s represents the confidence level of the error ellipse, where the confidence level is chosen to be 95%, and s is 5.991.
2) Set of track segments to be matched
And determining the station where the train is probably located at present by comparing the current positioning data of the train with the jurisdictional longitude and latitude ranges of all stations in the electronic map. And determining the track where the train is possibly located at present by comparing the jurisdiction longitude and latitude ranges of all tracks under jurisdiction of the station where the train is possibly located. Under the condition that the error ellipse is reasonably selected, the number of stations and tracks where trains can be located is not more than 2.
And comparing all track segments under the track where the train is possibly located, if the starting point or the end point of the track segment enters the range of the error ellipse, marking the track segment as a track segment to be matched, and a set formed by all the track segments meeting the conditions is called as a track segment set to be matched. And if no track segment enters the error ellipse range at the current moment, the map matching is considered to be failed, and the map matching algorithm is exited. If no orbit segment enters the error ellipse range continuously in a period of time, resetting the Kalman filter and adjusting the selection of the error ellipse.
3) Point-to-line map matching error function
After obtaining the set of candidate track segments, the distance deviation and direction deviation of each track segment are calculated. The distance deviation refers to the vertical distance from the positioning data to a line segment formed by connecting the starting point and the end point of the track segment, and the direction deviation refers to the included angle between the speed component output by the Kalman filter module and the track segment vector. And multiplying the distance deviation and the direction deviation by respective weights to obtain an error function value of map matching, wherein the track segment with the lowest error function value is used as a result of map matching of the train. The error function is as follows:
E＝Ed×Eφ＝λdDline×Tλφcosφ
in the formula, EdDenotes the distance deviation, EφDenotes the directional deviation, λ denotes the weight, and T is an auxiliary parameter.
Calculating distance deviation:
a coordinate system is established by taking the starting point of the track segment to be processed as the origin and the longitude and latitude directions as coordinate axes, and each point and line segment are represented in a vector mode, as shown in FIG. 2.
In the figure, point A represents the origin of coordinates, which is also the starting point of the track segment, and the latitude and longitude information of the point A is (Lon)A,LatA) The B point represents the end point of the track segment, and the longitude and latitude information of the B point is (Lon)B,LatB) The C point represents a satellite positioning point to be matched, and the longitude and latitude information of the C point is (Lon)C,LatC) Vector of motion
(Vector)
Vector from point C
Projecting to obtain intersection D, and calculating vector by using point multiplication and cross multiplication of vector
Sum vector
Length of (d):
wherein
Representing a vector
In that
Length of upper projection, if
Length exceeds
Indicating that point C projected outside segment AB, the matching of this track segment failed. If the C point is projected between the AB line segments
Indicating the distance deviation of the track segment.
Calculation of directional deviation
And (3) taking the velocity component in the output state variable of the Kalman filter module according to the direction of the track segment, namely the vector direction of the track segment, and calculating an included angle between the velocity component and the track segment direction:
when the train running speed is low, the influence of the satellite signal receiver, the train body shake and the like is caused, and the course angle calculated by the satellite positioning data has large deviation and jump, so that an auxiliary parameter T is set:
wherein V is the speed of train operation, VlowThe value of the low speed threshold of the train is determined by the performance of the satellite signal receiver.
4) Train positioning method output based on GNSS navigation system and electronic map topological structure
And selecting the orbit segment with the minimum matching error function value from the candidate orbit segments as a map matching result to perform point-to-line map matching calculation, wherein the process is to calculate the mileage of the one-dimensional orbit line where the D point projected from the satellite positioning point C to the orbit segment AB is located, and the mileage is used as an output result of a positioning algorithm.
The mileage of the track segment starting point A and the track segment end point B in the one-dimensional track line can be obtained in an electronic map database and respectively recorded as LAAnd LB. According to the geometric proportion relation, the following relation can be obtained:
LDand (4) the mileage of the matching point of the satellite positioning data on the orbit segment AB is calculated, and the train positioning process is finished.
As shown in fig. 3, the train positioning method based on GNSS and electronic map topology of the present invention includes the following steps:
step 101: acquiring current positioning data of the train;
step 102: judging whether the positioning data is valid, if so, executing step 103; otherwise, go to step 109;
step 103: inputting the positioning data into a Kalman filter module for filtering correction;
step 104: establishing a confidence interval to screen candidate track segments;
step 105: judging whether the number of the candidate track segments is greater than 0, if so, executing step 106; otherwise, go to step 109;
step 106: calculating the matching error function values from the positioning points to the candidate track segments one by one;
step 107: selecting the track segment with the minimum function value as a matching result;
step 108: converting the two-dimensional positioning data into one-dimensional mileage data as the output of a train positioning system;
step 109: the current satellite positioning is not available and the next set of data is awaited.
While the invention has been described with reference to specific embodiments, the invention is not limited thereto, and various equivalent modifications and substitutions can be easily made by those skilled in the art within the technical scope of the invention. Therefore, the protection scope of the present invention shall be subject to the protection scope of the claims.
Claims (10)
1. A train positioning system based on a GNSS and an electronic map topological structure is characterized by comprising a GNSS satellite positioning receiver module, a Kalman filter module, a map matching algorithm module and a vehicle-mounted electronic map module; the GNSS satellite positioning receiver module is connected with the map matching algorithm module through the Kalman filter module, and the map matching algorithm module is connected with the vehicle-mounted electronic map module;
the map matching algorithm module accurately matches the train positioning data output by the Kalman filter module to a certain track segment in the electronic map of the vehicle-mounted electronic map module, so that the train is accurately positioned.
2. The train positioning system based on the GNSS and the electronic map topological structure as claimed in claim 1, wherein the GNSS satellite positioning receiver module is installed at a head position of the train for receiving positioning signals of the GNSS navigation system in real time, resolving real-time train positioning data and outputting the same to the Kalman filter module.
3. Train positioning system based on GNSS and electronic map topologies, according to claim 1 or 2, characterized in thatCharacterized in that the output data of the GNSS satellite positioning receiver module is a series of longitude and latitude information representing the position of the train, and the output data is recorded as Rgnss(t)＝(Lon(t),Lat(t)), wherein Lon(t) longitudinal positioning data of train at time t, Lat(t) represents train positioning latitudinal direction positioning data at time t.
4. The train positioning system based on the GNSS and the electronic map topology according to claim 1, wherein the kalman filter module is configured to filter the train positioning data outputted from the GNSS satellite positioning receiver module, remove invalid values in the positioning data, and output the filtered train positioning data and the covariance matrix to the map matching algorithm module.
5. The train positioning system based on the GNSS and the electronic map topology according to claim 1 or 4, wherein the filtering process of the kalman filter module is as follows:
at the moment of k +1, the Kalman filter receives positioning data Z input by the GNSS satellite positioning receiver modulek+1The Kalman filter module firstly predicts a covariance matrix P of the Kalman filter at the moment of k +1 according to the working state of the GNSS satellite positioning receiver modulek+1/kAnd last moment effective positioning data Xk/kJudging the data validity of the positioning data; if the data is judged to be invalid, the positioning data is rejected; if the data is judged to be valid, the positioning data is brought into a filter to carry out position correction calculation;
under the condition that the input data is effective, the Kalman filter module corrects train positioning data Xk+1/k+1And correcting the covariance matrix Pk+1/k+1And outputting the data to a map matching algorithm module.
6. The train positioning system based on the GNSS and the electronic map topological structure as claimed in claim 1, wherein the vehicle-mounted electronic map module is an electronic map database formed by longitude and latitude information of a plurality of reference points measured on a track on which a train runs by a vehicle-mounted high-precision positioning measurement system.
7. The GNSS and electronic map topology based train positioning system according to claim 6, wherein the electronic map database adopts a hierarchical topology structure to build an index structure of the electronic map, wherein the three-level structure is a station, a track and a track segment respectively.
8. The GNSS and electronic map topology based train positioning system of claim 7, wherein said hierarchical topology of electronic map comprises:
the first-level station structure stores the following information: station number, number of rails under the jurisdiction of the station, number of the rails, and longitude and latitude range under the jurisdiction of the station;
a secondary track structure storing the following information: the method comprises the following steps of (1) track numbering, track superior station numbering, track starting point longitude and latitude and mileage, track end point longitude and latitude and mileage, track administered longitude and latitude range and track administered fragment numbering;
a three-level track segment structure storing the following: track segment number, superior track number, superior station number, starting point longitude and latitude and mileage, and ending point longitude and latitude and mileage.
9. The train positioning system based on the GNSS and the electronic map topology according to claim 1, wherein the matching process of the map matching algorithm module is specifically:
firstly, calculating a confidence interval error ellipse of the positioning data;
secondly, screening track segments to be matched which meet the conditions;
thirdly, calculating a matching error function with a matching track segment, and selecting the track segment with the minimum error function as a matching result;
and fourthly, converting the two-dimensional positioning data into one-dimensional mileage data to be used as the output of the train positioning system.
10. A train positioning method based on a GNSS and an electronic map topological structure is characterized by comprising the following steps:
step 101: acquiring current positioning data of the train;
step 102: judging whether the positioning data is valid, if so, executing step 103; otherwise, go to step 109;
step 103: inputting the positioning data into a Kalman filter module for filtering correction;
step 104: establishing a confidence interval to screen candidate track segments;
step 105: judging whether the number of the candidate track segments is greater than 0, if so, executing step 106; otherwise, go to step 109;
step 106: calculating the matching error function values from the positioning points to the candidate track segments one by one;
step 107: selecting the track segment with the minimum function value as a matching result;
step 108: converting the two-dimensional positioning data into one-dimensional mileage data as the output of a train positioning system;
step 109: the current satellite positioning is not available and the next set of data is awaited.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202110597668.9A CN113335341A (en) | 2021-05-31 | 2021-05-31 | Train positioning system and method based on GNSS and electronic map topological structure |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202110597668.9A CN113335341A (en) | 2021-05-31 | 2021-05-31 | Train positioning system and method based on GNSS and electronic map topological structure |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN113335341A true CN113335341A (en) | 2021-09-03 |
Family
ID=77472626
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202110597668.9A Pending CN113335341A (en) | 2021-05-31 | 2021-05-31 | Train positioning system and method based on GNSS and electronic map topological structure |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN113335341A (en) |
Cited By (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114044027A (en) * | 2021-12-24 | 2022-02-15 | 卡斯柯信号有限公司 | Method for realizing train positioning on two-dimensional electronic map |
| CN114312928A (en) * | 2021-12-29 | 2022-04-12 | 卡斯柯信号有限公司 | Virtual responder triggering method |
| CN114440892A (en) * | 2022-01-27 | 2022-05-06 | 中国人民解放军军事科学院国防科技创新研究院 | Self-positioning method based on topological map and odometer |
| CN115014339A (en) * | 2022-05-31 | 2022-09-06 | 苏州精卫信息科技有限公司 | Road matching method, device and equipment of railway train and readable storage medium |
| CN115951379A (en) * | 2023-03-14 | 2023-04-11 | 北京精英智通科技股份有限公司 | Centimeter-level positioning and deviation rectifying method based on GNSS system |
| CN117565937A (en) * | 2024-01-17 | 2024-02-20 | 湖南承希科技有限公司 | Method for realizing dynamic positioning of rail train based on WLAN technology |
| CN117572474A (en) * | 2024-01-12 | 2024-02-20 | 深圳市飞音科技有限公司 | Tramcar accurate positioning method based on GNSS technology |
Citations (11)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101357644A (en) * | 2008-09-08 | 2009-02-04 | 北京交通大学 | Locomotive wheel diameter automatic calibration system and method based on satellite positioning |
| GB201007659D0 (en) * | 2010-05-07 | 2010-06-23 | Westinghouse Brake & Signal | Train location system |
| CN104071186A (en) * | 2013-03-27 | 2014-10-01 | 高鹏 | Train positioning system |
| CN106469505A (en) * | 2015-08-20 | 2017-03-01 | 方正国际软件(北京)有限公司 | A kind of floating wheel paths method for correcting error and device |
| CN108196289A (en) * | 2017-12-25 | 2018-06-22 | 北京交通大学 | A kind of train combined positioning method under satellite-signal confined condition |
| CN109085631A (en) * | 2018-08-01 | 2018-12-25 | 北京交通大学 | Trouble area train track based on satellite positioning weights recognition methods |
| CN110221328A (en) * | 2019-07-23 | 2019-09-10 | 广州小鹏汽车科技有限公司 | A kind of Combinated navigation method and device |
| CN110632627A (en) * | 2019-10-31 | 2019-12-31 | 卡斯柯信号有限公司 | Beidou differential positioning method for ITCS signal system |
| CN111024072A (en) * | 2019-12-27 | 2020-04-17 | 浙江大学 | Satellite map aided navigation positioning method based on deep learning |
| CN112429041A (en) * | 2020-11-06 | 2021-03-02 | 北京全路通信信号研究设计院集团有限公司 | Method and device for judging train running direction based on satellite positioning |
| CN112485818A (en) * | 2020-11-12 | 2021-03-12 | 卡斯柯信号有限公司 | Train control vehicle-mounted positioning method and system and vehicle-mounted terminal |
-
2021
- 2021-05-31 CN CN202110597668.9A patent/CN113335341A/en active Pending
Patent Citations (11)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101357644A (en) * | 2008-09-08 | 2009-02-04 | 北京交通大学 | Locomotive wheel diameter automatic calibration system and method based on satellite positioning |
| GB201007659D0 (en) * | 2010-05-07 | 2010-06-23 | Westinghouse Brake & Signal | Train location system |
| CN104071186A (en) * | 2013-03-27 | 2014-10-01 | 高鹏 | Train positioning system |
| CN106469505A (en) * | 2015-08-20 | 2017-03-01 | 方正国际软件(北京)有限公司 | A kind of floating wheel paths method for correcting error and device |
| CN108196289A (en) * | 2017-12-25 | 2018-06-22 | 北京交通大学 | A kind of train combined positioning method under satellite-signal confined condition |
| CN109085631A (en) * | 2018-08-01 | 2018-12-25 | 北京交通大学 | Trouble area train track based on satellite positioning weights recognition methods |
| CN110221328A (en) * | 2019-07-23 | 2019-09-10 | 广州小鹏汽车科技有限公司 | A kind of Combinated navigation method and device |
| CN110632627A (en) * | 2019-10-31 | 2019-12-31 | 卡斯柯信号有限公司 | Beidou differential positioning method for ITCS signal system |
| CN111024072A (en) * | 2019-12-27 | 2020-04-17 | 浙江大学 | Satellite map aided navigation positioning method based on deep learning |
| CN112429041A (en) * | 2020-11-06 | 2021-03-02 | 北京全路通信信号研究设计院集团有限公司 | Method and device for judging train running direction based on satellite positioning |
| CN112485818A (en) * | 2020-11-12 | 2021-03-12 | 卡斯柯信号有限公司 | Train control vehicle-mounted positioning method and system and vehicle-mounted terminal |
Cited By (12)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114044027A (en) * | 2021-12-24 | 2022-02-15 | 卡斯柯信号有限公司 | Method for realizing train positioning on two-dimensional electronic map |
| CN114044027B (en) * | 2021-12-24 | 2024-03-26 | 卡斯柯信号有限公司 | Method for realizing train positioning on two-dimensional electronic map |
| CN114312928A (en) * | 2021-12-29 | 2022-04-12 | 卡斯柯信号有限公司 | Virtual responder triggering method |
| CN114312928B (en) * | 2021-12-29 | 2024-03-12 | 卡斯柯信号有限公司 | Virtual transponder triggering method |
| CN114440892A (en) * | 2022-01-27 | 2022-05-06 | 中国人民解放军军事科学院国防科技创新研究院 | Self-positioning method based on topological map and odometer |
| CN114440892B (en) * | 2022-01-27 | 2023-11-03 | 中国人民解放军军事科学院国防科技创新研究院 | Self-positioning method based on topological map and odometer |
| CN115014339A (en) * | 2022-05-31 | 2022-09-06 | 苏州精卫信息科技有限公司 | Road matching method, device and equipment of railway train and readable storage medium |
| CN115951379A (en) * | 2023-03-14 | 2023-04-11 | 北京精英智通科技股份有限公司 | Centimeter-level positioning and deviation rectifying method based on GNSS system |
| CN117572474A (en) * | 2024-01-12 | 2024-02-20 | 深圳市飞音科技有限公司 | Tramcar accurate positioning method based on GNSS technology |
| CN117572474B (en) * | 2024-01-12 | 2024-03-19 | 深圳市飞音科技有限公司 | Tramcar accurate positioning method based on GNSS technology |
| CN117565937A (en) * | 2024-01-17 | 2024-02-20 | 湖南承希科技有限公司 | Method for realizing dynamic positioning of rail train based on WLAN technology |
| CN117565937B (en) * | 2024-01-17 | 2024-04-09 | 湖南承希科技有限公司 | Method for realizing dynamic positioning of rail train based on WLAN technology |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN113335341A (en) | Train positioning system and method based on GNSS and electronic map topological structure | |
| CN107976697B (en) | Train safety positioning method and system based on Beidou/GPS combination | |
| CN104197945B (en) | Global voting map matching method based on low-sampling-rate floating vehicle data | |
| CN106969764B (en) | Road matching method and device and vehicle-mounted map acquisition system | |
| CN108061889B (en) | AIS and radar angle system deviation correlation method | |
| CN110203253B (en) | Method for realizing non-fixed virtual responder | |
| CN1164891A (en) | Movement detector | |
| CN109738902B (en) | High-precision autonomous acoustic navigation method for underwater high-speed target based on synchronous beacon mode | |
| CN110441760B (en) | Wide-range seabed topographic map expansion composition method based on prior topographic map | |
| CN112346104A (en) | Unmanned aerial vehicle information fusion positioning method | |
| CN113866810A (en) | Method, system, electronic equipment and storage medium for train positioning and navigation | |
| CN103047982A (en) | Adaptive target tracking method based on angle information | |
| CN113581260B (en) | Train track occupation judging method based on GNSS | |
| CN111060112A (en) | Vehicle track map matching method and system based on direction angle | |
| CN115009329A (en) | Train initial positioning calculation method and positioning system based on Beidou satellite | |
| CN110927765B (en) | Laser radar and satellite navigation fused target online positioning method | |
| CN118470389A (en) | Railway track mileage calibration method, device, equipment and computer storage medium | |
| CN117130014B (en) | Method and system for establishing single difference model between ionosphere stars in high-precision area | |
| CN113298113B (en) | Rail-following environment classification method based on train-mounted satellite positioning observation data | |
| CN116736327B (en) | Positioning data optimization method, device, electronic equipment and readable storage medium | |
| CN112130137B (en) | Method, device and storage medium for determining lane-level track | |
| CN110647877B (en) | Three-dimensional traffic facility positioning and deviation rectifying method and device based on neural network | |
| CN110081890B (en) | Dynamic k nearest neighbor map matching method combined with deep network | |
| CN112130166A (en) | AGV positioning method and device based on reflector network | |
| CN110108287A (en) | A kind of unmanned vehicle high-precision map-matching method and system based on street lamp auxiliary |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| RJ01 | Rejection of invention patent application after publication | ||
| RJ01 | Rejection of invention patent application after publication |
Application publication date: 20210903 |