CN109141405B - Vehicle geomagnetic matching positioning method and system in road network environment - Google Patents
Vehicle geomagnetic matching positioning method and system in road network environment Download PDFInfo
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Abstract
The invention provides a vehicle geomagnetic matching positioning method under a road network environment, which can identify a straight road section, a left-turn road section, a right-turn road section and a turn-around road section of an initial driving road when a vehicle is about to pass through an intersection, and identify whether the current driving road section of the vehicle is the straight road section, the left-turn road section, the right-turn road section or the turn-around road section of the initial driving road section after the vehicle passes through the intersection through a maximum correlation coefficient method to obtain the current matching position of the vehicle, thereby realizing the positioning conversion of the vehicle from the initial driving road section to the current driving road section; and then, the running position estimation value and the current matching position are subjected to fusion filtering processing, so that the performance advantage complementation of a geomagnetic matching/dead reckoning system is realized, the positioning result is continuous and reliable, and the autonomous positioning of the long-distance and complex road network environment of the vehicle can be met.
Description
Technical Field
The invention belongs to the technical field of vehicle autonomous positioning, and particularly relates to a vehicle geomagnetic matching positioning method and system in a road network environment.
Background
In the main solution of vehicle positioning, an Inertial Navigation System (INS) and a Dead Reckoning System (DR) are widely used, but both are essentially vehicle trajectory estimation based on variation integral, and therefore, a positioning result cumulative offset is formed due to measurement errors of an Inertial device and an odometer. A Global Navigation Satellite System (GNSS) can provide all-weather and all-time Global positioning, but based on a wireless signal ranging mechanism, Satellite signals in an urban complex road network environment are easily shielded, multipath, radio interference and the like, and a continuous and reliable positioning result cannot be provided. In order to solve the problems, a plurality of novel vehicle positioning and navigation technologies are developed, and technologies such as map matching positioning, RFID road marking positioning, land-based radio network positioning, geomagnetic matching positioning and the like all obtain a series of research results. The geomagnetism matching positioning realizes accurate positioning of the vehicle by means of magnetic field characteristics of the earth and earth surface buildings through characteristic matching. The geomagnetic matching positioning does not need to lay a large number of base stations and information source equipment, has the advantages of low cost, no radiation, no error accumulation along with time and the like, has a better positioning effect, and is a vehicle positioning technology which is developed rapidly at present.
With the development of urban road network construction, the research of the geomagnetic matching and positioning technology based on road network topology has very significant significance. The geomagnetic matching positioning system is used as a vehicle positioning means, and has the characteristics that the positioning error of the geomagnetic matching positioning system does not diverge with the lapse of time, but has weak points: firstly, the vehicle road network is complex, the real-time performance of global matching calculation is poor, and interference road sections are easily introduced; secondly, when the vehicle is positioned at the intersection, the problem of mismatching is easy to occur due to the randomness of the driving direction, so that the vehicle cannot provide a continuous positioning result.
Disclosure of Invention
In order to solve the problems, the invention provides a vehicle geomagnetic matching positioning method and system in a road network environment, which integrate dead reckoning and geomagnetic matching and realize efficient and reliable road network environment vehicle autonomous positioning.
A vehicle geomagnetic matching positioning method in a road network environment comprises the following steps:
s1: acquiring geomagnetic field data of a vehicle driving route, the driving mileage of the vehicle, the driving course of the vehicle and a driving position calculation value of the vehicle in a road network environment in real time;
s2: sampling the geomagnetic field data at equal mileage intervals based on the mileage to obtain an actually measured geomagnetic sequence;
s3: determining an initial driving road section of the vehicle in a preset road network geomagnetic reference library based on the driving position calculation value by adopting a minimum track difference method;
s4: matching and resolving the actually measured geomagnetic sequence and a reference geomagnetic sequence corresponding to the initial driving road section in the road network geomagnetic reference library by adopting a maximum correlation coefficient method to obtain an initial matching position, and realizing vehicle positioning under the initial driving road section;
s5: when the vehicle runs to the intersection, acquiring road sections which are possibly run behind the initial running road section, wherein the road sections comprise a straight road section, a left-turning road section, a right-turning road section and a U-turn road section;
s6: matching and resolving the actually measured geomagnetic sequences with corresponding reference geomagnetic sequences of a straight road section, a left-turn road section, a right-turn road section and a turn-around road section of the initial driving road section in the road network geomagnetic reference library by adopting a maximum correlation coefficient method to correspondingly obtain a straight matching position, a left-turn matching position, a right-turn matching position and a turn-around matching position;
s7: taking the maximum correlation coefficient peak value corresponding to the straight-going matching position, the left-turning matching position, the right-turning matching position and the U-turn matching position as the optimal matching position of the vehicle at the current moment;
s8: repeating the steps S6 and S7 until more than 5 continuous optimal matching positions belong to the same road section, and determining the current driving road section after the vehicle passes through the intersection;
s9: matching and resolving the actually measured geomagnetic sequence and a reference geomagnetic sequence corresponding to the current driving road section in the road network geomagnetic reference library by adopting a maximum correlation coefficient method to obtain a current matching position, and realizing vehicle positioning under the current driving road section;
s10: and performing fusion filtering processing on the driving position estimation value and the current matching position to obtain a fusion result serving as a vehicle driving position, so as to realize vehicle positioning in a road network environment.
Further, the method for acquiring the estimated value of the driving position of the vehicle in the road network environment specifically comprises the following steps:
obtaining a starting position (e) of the vehicle0,n0) (ii) a Wherein e is0Is the initial east position, n0Is the initial north position;
according to the starting position (e)0,n0) Obtaining the estimated value (e) of the driving position at the k-th timek,nk) Specifically, the method comprises the following steps:
wherein e iskEast position at time k, nkNorth orientation at time k, diIs the mileage increment at the ith time, thetaiI is the heading angle at time i, i is 0,1,2, …, k-1, θkIs the heading angle, θ, at time kg,kMagnetic heading, θ, at time kbIs the declination.
Further, the determining an initial driving road section of the vehicle in a preset road network geomagnetic reference library by using a minimum track difference method specifically includes:
acquiring a track difference between the driving position calculation value at each moment and each road section in the road network geomagnetic reference library, wherein the road section corresponding to the minimum value of the track difference at each moment is a road section to be selected for driving; if the corresponding road sections to be selected at more than 5 continuous moments are the same road section loptThen road section loptAs an initial travel segment of the vehicle.
Further, the calculation method of the track difference comprises the following steps:
wherein, Delta trjlCalculating a value x for the driving position at the k-th timeDR,kTrack difference from the first road section, xDR,k＝(ek,nk) Estimate of the driving position at the k-th time, xmap,nThe position of the nth sampling point theta of the first road section in the geomagnetic reference library of the road networkkIs the heading angle, θ, at time kmap,nThe N-th heading angle of the first road section in the road network geomagnetic reference library is 1,2, …, Nl，NlThe total number of sampling points of the first road segment is 1,2, …, and L is the total number of road segments in the road network geomagnetic reference library.
Further, the running position estimate and the current matching position are subjected to fusion filtering, and an obtained fusion result as a vehicle running position specifically includes:
with east position error deltaekNorth position error δ nkMileage increment error δ dkAnd heading error delta thetakAs state vector X at time kkSpecifically, the method comprises the following steps:
Xk＝[δek,δnk,δdk,δθk]T
taking the difference value between the estimated value of the driving position and the matching position as an observation vector ZkSpecifically, the method comprises the following steps:
Zk＝[Δek,Δnk]T＝[eg,k-ek,ng,k-nk]
wherein (e)g,k,ng,k) Is the matching position at the k-th time, (e)k,nk) Is a driving position estimate at the k-th time;
obtaining a state equation according to the dead reckoning principle:
wherein, wnoise,eSystematic noise, w, for east positionnoise,nSystem noise, w, for north positionnoise,DSystem noise, w, in mileage incrementsnoise,θSystem noise that is a heading angle; delta ek+1、δnk+1、δdk+1And delta thetak+1East position error at time k +1, respectivelyNorth position error, mileage increment error and course error;
obtaining a state transition matrix phi from a state equationk：
Wherein d iskThe total driving range at the kth moment;
observation matrix HkComprises the following steps:
system noise matrix QkComprises the following steps:
wherein, deltae＝δnBeing position noise, δDAs mileage noise, δθThe noise is course noise;
the observed noise matrix R is:
wherein, we＝wnMatching the position error root mean square value;
fusing the results
As a vehicle travel position output.
A vehicle geomagnetic matching positioning system in a road network environment comprises a magnetic sensor, a speedometer, an electronic compass, a dead reckoning module, a road network geomagnetic matching resolving module and a data fusion filtering module;
the magnetic sensor is used for acquiring geomagnetic field data on a vehicle running route in real time; the odometer is used for measuring the mileage driven by the vehicle; the electronic compass is used for measuring the running course of the vehicle; the dead reckoning module is used for obtaining a real-time driving position estimation value of the vehicle in a road network environment according to the mileage and the course;
the road network geomagnetic matching calculation module comprises an actual measurement geomagnetic sequence acquisition unit, an initial road section acquisition unit and a matching calculation unit; the measured geomagnetic sequence acquisition unit is used for sampling the geomagnetic field data at equal mileage intervals based on the mileage to obtain a measured geomagnetic sequence; the initial road section obtaining unit is used for determining an initial driving road section of the vehicle in a preset road network geomagnetic reference library based on the driving position calculation value by adopting a minimum track difference method; the matching and resolving unit is used for matching and resolving the actually measured geomagnetic sequence and a reference geomagnetic sequence corresponding to an initial driving road section in a road network geomagnetic reference library by adopting a maximum correlation coefficient method to obtain an initial matching position to realize vehicle positioning under the initial driving road section, then determining a current driving road section of a vehicle from road sections possibly driven behind the initial driving road section including a straight road section, a left-turning road section, a right-turning road section and a turning road section according to the maximum criterion of a correlation coefficient peak value when the vehicle drives to an intersection, and finally matching and resolving the actually measured geomagnetic sequence and the reference geomagnetic sequence corresponding to the current driving road section in the road network geomagnetic reference library to obtain the current matching position to realize vehicle positioning under the current driving road section;
and the data fusion filtering module is used for performing fusion filtering processing on the driving position calculation value and the current matching position, and an obtained fusion result is used as a vehicle driving position to realize vehicle positioning in a road network environment.
Further, the specific method for obtaining the real-time driving position estimation value of the vehicle in the road network environment by the dead reckoning module according to the mileage and the heading comprises the following steps:
obtaining a starting position (e) of the vehicle0,n0) Wherein e is0Is the initial east position, n0Is the initial north position;
according to the starting position(e0,n0) Obtaining the estimated value (e) of the driving position at the k-th timek,nk) Specifically, the method comprises the following steps:
wherein e iskEast position at time k, nkNorth orientation at time k, diIs the mileage increment at the ith time, thetaiI is the heading angle at time i, i is 0,1,2, …, k-1, θkIs the heading angle, θ, at time kg,kMagnetic heading, θ, at time kbIs the declination.
Further, the initial road section obtaining unit is configured to determine, by using a minimum track difference method, an initial driving road section of the vehicle in a preset road network geomagnetic reference library, specifically:
acquiring a track difference between the driving position calculation value at each moment and each road section in the road network geomagnetic reference library, wherein the road section corresponding to the minimum value of the track difference at each moment is a road section to be selected for driving; if the corresponding road sections to be selected at more than 5 continuous moments are the same road section loptThen road section loptAs an initial travel segment of the vehicle.
Further, the calculation method of the track difference comprises the following steps:
wherein, Delta trjlCalculating a value x for the driving position at the k-th timeDR,kTrack difference from the first road section, xDR,k＝(ek,nk) Estimate of the driving position at the k-th time, xmap,nThe position of the nth sampling point theta of the first road section in the geomagnetic reference library of the road networkkIs the heading angle, θ, at time kmap,nThe N-th heading angle of the first road section in the road network geomagnetic reference library is 1,2l，NlThe total number of sampling points of the first road section is 1,2, …, and L is the geomagnetic reference of the road networkTotal number of links in the library.
Furthermore, the data fusion filtering module is also used for obtaining a mileage increment error estimation value and a course angle error estimation value and feeding back the mileage increment error estimation value and the course angle error estimation value to the dead reckoning module, so that the dead reckoning module corrects the mileage and the course according to the mileage increment error estimation value and the course angle error estimation value.
Has the advantages that:
1. the invention provides a vehicle geomagnetic matching positioning method under a road network environment, which can identify a straight road section, a left-turn road section, a right-turn road section and a turn-around road section of an initial driving road when a vehicle is about to pass through an intersection, and identify whether the current driving road section of the vehicle is the straight road section, the left-turn road section, the right-turn road section or the turn-around road section of the initial driving road section after the vehicle passes through the intersection through a maximum correlation coefficient method to obtain the current matching position of the vehicle, thereby realizing the positioning conversion of the vehicle from the initial driving road section to the current driving road section; and then, the running position estimation value and the current matching position are subjected to fusion filtering processing, so that the performance advantage complementation of a geomagnetic matching/dead reckoning system is realized, the positioning result is continuous and reliable, and the autonomous positioning of the long-distance and complex road network environment of the vehicle can be met.
2. The invention provides a vehicle geomagnetic matching positioning system under a road network environment, wherein on the basis of geomagnetic matching, a matching resolving unit can obtain a matching position of a vehicle in an intersection with a straight road section, a left-turn road section, a right-turn road section and a U-turn road section by a maximum correlation coefficient method, and then fusion filtering processing is carried out on a driving position calculation value and the matching position, so that performance advantage complementation of a geomagnetic matching/dead reckoning system is realized, a positioning result is continuous and reliable, and autonomous positioning of a vehicle distance and a complex road network environment can be met.
Drawings
FIG. 1 is a schematic diagram of a matching solution based on a road segment l according to the present invention;
fig. 2 is a schematic diagram of a road network where the first road section provided by the present invention is located;
fig. 3 is a schematic block diagram of a vehicle geomagnetic matching positioning system in a road network environment according to the present invention.
Detailed Description
In order to make the technical solutions better understood by those skilled in the art, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application.
Example one
The embodiment provides a vehicle geomagnetic matching positioning method in a road network environment, which includes the following steps:
s1: and acquiring geomagnetic field data of a vehicle driving route, the driving mileage of the vehicle, the driving course of the vehicle and the driving position estimation value of the vehicle in the road network environment in real time.
It should be noted that dead reckoning is a basic way to locate a vehicle, and its principle is to use sensors of course and mileage to estimate the position of the vehicle. The following describes a method for acquiring an estimated value of a driving position of a vehicle in a road network environment, specifically:
obtaining a starting position (e) of the vehicle0,n0) (ii) a Wherein e is0Is the initial east position, n0Is the initial north position.
According to the starting position (e)0,n0) Obtaining the estimated value (e) of the driving position at the k-th timek,nk) Specifically, the method comprises the following steps:
wherein e iskEast position at time k, nkNorth orientation at time k, diIs the mileage increment at the ith time, thetaiI is the heading angle at time i, i is 0,1,2, …, k-1, θkIs the heading angle, θ, at time kg,kIs the heading of time k, θbIs the declination.
S2: and carrying out equal-mileage interval sampling on the geomagnetic field data based on the mileage to obtain an actually measured geomagnetic sequence.
In order to achieve the unification of the spatial scale between the measured geomagnetic sequence and the reference geomagnetic sequence in the road network geomagnetic reference library, it is necessary to convert the geomagnetic data measured by the magnetic sensor from the time sequence to the spatial sequence by using the mileage information. Performing linear interpolation processing on the geomagnetic field data sequence (m, t) and the mileage information sequence (D, t), increasing the sampling frequency and realizing alignment of the measurement moments to obtain a sequence (m, D); re-extracting according to the preset mileage interval delta d to form a geomagnetic sequence [ mf,(f-1)Δd]And F is 1,2, …, where F denotes the F-th mileage sampling point, and F is the total number of mileage sampling points after re-extraction, that is, the calculation of the measured geomagnetic sequence is completed.
In the formula, the mileage interval Δ d is a mileage scale of the actually measured geomagnetic sequence.
It should be noted that, in this embodiment, the geomagnetic field data is used to establish the reference library, so that the geomagnetic reference library has high spatial resolution, and the positioning accuracy is significantly improved. Meanwhile, the spatial scale matching processing of the reference geomagnetic sequence of the road network geomagnetic reference library and the actually measured geomagnetic data is completed by adopting the mileage information, the processing process is simple and convenient to calculate, and the engineering implementation is easy.
S3: and determining an initial driving road section of the vehicle in a preset road network geomagnetic reference library based on the driving position estimation value by adopting a minimum track difference method.
In the road network environment, the number of links is large, and it is necessary to use the travel position estimate (e)k,nk) And heading thetakThe search range is narrowed, and an initial road section of the matching calculation process is determined. The method for acquiring the initial driving road section is described as follows:
acquiring a track difference between the driving position calculation value at each moment and each road section in the road network geomagnetic reference library, wherein the road section corresponding to the minimum value of the track difference at each moment is a road section to be selected for driving; if the initial road sections to be selected corresponding to more than 5 continuous moments are the same road section loptThen road section loptAs an initial travel segment of the vehicle.
Further, the calculation method of the track difference comprises the following steps:
wherein, Delta trjlCalculating a value x for the driving position at the k-th timeDR,kTrack difference from the first road section, xDR,k＝(ek,nk) Estimate of the driving position at the k-th time, xmap,nThe position of the nth sampling point theta of the first road section in the geomagnetic reference library of the road networkkIs the heading angle, θ, at time kmap,nThe N-th heading angle of the first road section in the road network geomagnetic reference library is 1,2l，NlThe total number of sampling points of the first road segment is 1,2, …, and L is the total number of road segments in the road network geomagnetic reference library.
S4: and matching and resolving the actually measured geomagnetic sequence and a reference geomagnetic sequence of the initial driving road section in the road network geomagnetic reference library by adopting a maximum correlation coefficient method to obtain an initial matching position, so as to realize vehicle positioning in the initial driving road section.
Referring to fig. 2, the figure is a schematic diagram of a matching solution based on a road segment l provided in the present embodiment. Taking w as a window interval of matching calculation, wherein the physical meaning is that sliding matching is carried out on an actually measured geomagnetic sequence with the distance of w · Δ d and a reference geomagnetic sequence in a road network geomagnetic reference library.
In FIG. 2, mjIn order to actually measure the geomagnetic sequence,
for the reference geomagnetic sequence of the first road segment in the geomagnetic reference library of the road network,
n is the corresponding space geographic coordinate of the first road section, 1,2l. Using the newly acquired w actually-measured geomagnetic sequences to carry out matching calculationThe method is an improved zero-mean correlation coefficient method.
The above formula reflects the actually measured geomagnetic sequence mjWith reference geomagnetic sequence
The degree of correlation between N ∈ [ w, N ] in the intervall]Inner, rnIn order to be the correlation coefficient,
is the average value of the geomagnetic reference database data of the road network,
is the average value of the measured geomagnetic data, N represents the mileage sampling point of the first road section, NlK is the total number of sampling points of the ith road section, k represents the kth measured geomagnetic data point,
for the n-k road network geomagnetic reference database data,
and measuring geomagnetic data for the w-k. Peak value of correlation coefficient rmaxCorresponding geomagnetic reference library sequence position xopt＝(eg,ng) I.e. the matching position when rmaxGreater than a set threshold rtWhen, consider matching position xoptIs effective. Otherwise, the matching position is abandoned, and the initial matching position of the vehicle is not output. Wherein r istAnd setting for a preset correlation coefficient threshold according to actual conditions. The zero-averaging processing in the formula is intended to eliminate the influence of the zero-offset mismatch of the magnetic sensor.
S5: when the vehicle runs to the intersection, the road sections which are possibly run behind the initial running road section are obtained, wherein the road sections comprise a straight road section, a left-turning road section, a right-turning road section and a turning road section.
In the road network environment, if continuous matching and positioning between road segments are to be realized, a road segment splicing function is required. Referring to fig. 2, the figure is a schematic diagram of a road network where the first road segment is located according to this embodiment. When the vehicle is driven to the intersection and is about to drive into a new road section, all possible spliced road sections of the initial driving road section are a straight road section, a left-turning road section, a right-turning road section and a U-turn road section.
S6: and respectively matching and resolving the actually measured geomagnetic sequences with the corresponding reference geomagnetic sequences of the straight road section, the left-turn road section, the right-turn road section and the turn-around road section of the initial driving road section in the road network geomagnetic reference library by adopting a maximum correlation coefficient method to correspondingly obtain a straight matching position, a left-turn matching position, a right-turn matching position and a turn-around matching position.
That is, for all splicing conditions (straight running, left turning, right turning and turning around) of the initial running road section, matching calculation is respectively carried out to obtain 4 groups of correlation coefficient peak values
And matching position
p is 1,2,3,4 respectively corresponding to the combination of the current road segment and the straight, left-turning, right-turning and u-turning road segments.
S7: and taking the maximum correlation coefficient peak value in the straight-going matching position, the left-turning matching position, the right-turning matching position and the U-turn matching position as the optimal matching position of the vehicle at the current moment.
S8: and repeating the steps S6 and S7 until more than 5 continuous optimal matching positions belong to the same road section, and determining the current driving road section after the vehicle passes through the intersection.
S9: and matching and resolving the actually measured geomagnetic sequence and a reference geomagnetic sequence corresponding to the current driving road section in the road network geomagnetic reference library by adopting a maximum correlation coefficient method to obtain a current matching position, and realizing vehicle positioning under the current driving road section.
S10: and performing fusion filtering processing on the driving position estimation value and the current matching position to obtain a fusion result serving as a vehicle driving position, so as to realize vehicle positioning in a road network environment.
A specific implementation of the fusion filtering process is described below.
With east position error deltaekNorth position error δ nkMileage increment error δ dkAnd heading error delta thetakAs state vector X at time kkSpecifically, the method comprises the following steps:
Xk＝[δek,δnk,δdk,δθk]T (5)
taking the difference value between the estimated value of the driving position and the matching position as an observation vector ZkSpecifically, the method comprises the following steps:
Zk＝[Δek,Δnk]T＝[eg,k-ek,ng,k-nk] (6)
wherein (e)g,k,ng,k) Is the matching position at the k-th time, (e)k,nk) Is a travel position estimated value at the k-th time;
obtaining a state equation according to the dead reckoning principle:
wherein, wnoise,eSystematic noise, w, for east positionnoise,nSystem noise, w, for north positionnoise,DSystem noise, w, in mileage incrementsnoise,θSystem noise that is a heading angle; delta ek+1、δnk+1、δdk+1And delta thetak+1East position error, north position error, mileage increment error and course error at the moment of k +1 respectively; thetakThe course angle at the kth moment;
obtaining a state transition matrix phi from a state equationk：
Wherein the content of the first and second substances,
the total driving range at the kth moment;
observation matrix is Hk：
System noise matrix of Qk：
Wherein, deltae＝δnBeing position noise, δDAs mileage noise, δθThe noise is course noise;
the observed noise matrix R is:
wherein, we＝wnMatching the position error root mean square value;
fusing the results
As a vehicle travel position output.
It should be noted that, in the process of the fusion filtering process, a mileage increment error estimation value and a course angle error estimation value are also obtained, and the mileage increment error estimation value and the course angle error estimation value can be used for correcting the mileage and the course.
Example two
Based on the above embodiment, this embodiment also provides a vehicle geomagnetism matching positioning system under the road network environment. Referring to fig. 3, the schematic block diagram of a vehicle geomagnetic matching positioning system in a road network environment according to this embodiment is shown. A vehicle geomagnetic matching positioning system in a road network environment comprises a magnetic sensor, a speedometer, an electronic compass, a dead reckoning module, a road network geomagnetic matching resolving module and a data fusion filtering module;
the magnetic sensor is used for acquiring geomagnetic field data on a vehicle running route in real time; the odometer is used for measuring the mileage driven by the vehicle; the electronic compass is used for measuring the running course of the vehicle; and the dead reckoning module is used for obtaining a real-time driving position estimation value of the vehicle in the road network environment according to the mileage and the course.
The road network geomagnetic matching calculation module comprises an actual measurement geomagnetic sequence acquisition unit, an initial road section acquisition unit and a matching calculation unit; the measured geomagnetic sequence acquisition unit is used for sampling the geomagnetic field data at equal mileage intervals based on the mileage to obtain a measured geomagnetic sequence; the initial road section obtaining unit is used for determining an initial driving road section of the vehicle in a preset road network geomagnetic reference library based on the driving position calculation value by adopting a minimum track difference method; the matching and resolving unit is used for matching and resolving the actually measured geomagnetic sequence and a reference geomagnetic sequence corresponding to the initial driving road section in a road network geomagnetic reference library by adopting a maximum correlation coefficient method to obtain an initial matching position to realize vehicle positioning under the initial driving road section, then determining a current driving road section of a vehicle from road sections possibly driven behind the initial driving road section including a straight road section, a left-turning road section, a right-turning road section and a turning road section according to the maximum criterion of a correlation coefficient peak value when the vehicle drives to an intersection, and finally matching and resolving the actually measured geomagnetic sequence and the reference geomagnetic sequence corresponding to the current driving road section in the road network geomagnetic reference library to obtain the current matching position to realize vehicle positioning under the current driving road section;
and the data fusion filtering module is used for performing fusion filtering processing on the driving position calculation value and the current matching position, and an obtained fusion result is used as a vehicle driving position to realize vehicle positioning in a road network environment.
It should be noted that the geomagnetic field of any point in the earth's near-earth space has uniqueness, and theoretically corresponds to the geographic coordinate of the point uniquely, and global positioning can be realized as long as the geomagnetic field data of each point is accurately determined. And (3) forming a road network geomagnetic reference library by using geomagnetic field data of a vehicle driving route as a characteristic value and matching the characteristic value with the geographic coordinates of the position where the vehicle is located.
Further, the method for acquiring the estimated value of the driving position specifically includes:
obtaining a starting position (e) of the vehicle0,n0) (ii) a Wherein e is0Is the initial east position, n0Is the initial north position.
According to the starting position (e)0,n0) Obtaining the estimated value (e) of the driving position at the k-th timek,nk) Specifically, the method comprises the following steps:
wherein e iskEast position at time k, nkNorth orientation at time k, diIs the mileage increment at the ith time, thetaiI is the heading angle at time i, i is 0,1,2, …, k-1, θkIs the heading angle, θ, at time kg,kMagnetic heading, θ, at time kbIs the declination.
Further, the method for determining the initial driving section of the vehicle specifically comprises the following steps:
acquiring a track difference between the driving position calculation value at each moment and each road section in the road network geomagnetic reference library, wherein the road section corresponding to the minimum value of the track difference at each moment is a road section to be selected for driving; if the initial road sections to be selected corresponding to more than 5 continuous moments are the same road section loptThen road section loptAs an initial travel segment of the vehicle.
Further, the calculation method of the track difference comprises the following steps:
wherein, Delta trjlCalculating a value x for the driving position at the k-th timeDR,kTrack difference from the first road section, xDR,k＝(ek,nk) Estimate of the driving position at the k-th time, xmap,nThe position of the nth sampling point theta of the first road section in the geomagnetic reference library of the road networkkIs the heading angle, θ, at time kmap,nThe N-th heading angle of the first road section in the road network geomagnetic reference library is 1,2l，NlThe total number of sampling points of the first road segment is 1,2, …, and L is the total number of road segments in the road network geomagnetic reference library.
In addition, in the dead reckoning process, mileage and course measurement errors at different moments are gradually accumulated, so that the positioning error is dispersed. Therefore, the dead reckoning alone cannot perform long-time and long-distance positioning, and needs other navigation methods to correct accumulated errors. Therefore, further, the data fusion filtering module is further configured to obtain a mileage increment error estimation value and a course angle error estimation value, and feed back the mileage increment error estimation value and the course angle error estimation value to the dead reckoning module, so that the dead reckoning module corrects the mileage and the course according to the mileage increment error estimation value and the course angle error estimation value.
The present invention may be embodied in other specific forms without departing from the spirit or essential attributes thereof, and it will be understood by those skilled in the art that various changes and modifications may be made herein without departing from the spirit and scope of the invention as defined in the appended claims.
Claims (9)
1. A vehicle geomagnetic matching positioning method in a road network environment is characterized by comprising the following steps:
s1: acquiring geomagnetic field data of a vehicle driving route, the driving mileage of the vehicle, the driving course of the vehicle and a driving position calculation value of the vehicle in a road network environment in real time;
s2: sampling the geomagnetic field data at equal mileage intervals based on the mileage to obtain an actually measured geomagnetic sequence;
s3: determining an initial driving road section of the vehicle in a preset road network geomagnetic reference library by adopting a minimum track difference method based on the driving position calculation value, wherein the initial driving road section is specifically as follows:
acquiring a track difference between the driving position calculation value at each moment and each road section in the road network geomagnetic reference library, wherein the road section corresponding to the minimum value of the track difference at each moment is a road section to be selected for driving; if the corresponding road sections to be selected at more than 5 continuous moments are the same road section loptThen road section loptAs an initial travel segment of the vehicle;
s4: matching and resolving the actually measured geomagnetic sequence and a reference geomagnetic sequence corresponding to the initial driving road section in the road network geomagnetic reference library by adopting a maximum correlation coefficient method to obtain an initial matching position, and realizing vehicle positioning under the initial driving road section;
s5: when the vehicle runs to the intersection, acquiring road sections which are possibly run behind the initial running road section, wherein the road sections comprise a straight road section, a left-turning road section, a right-turning road section and a U-turn road section;
s6: matching and resolving the actually measured geomagnetic sequences with corresponding reference geomagnetic sequences of a straight road section, a left-turn road section, a right-turn road section and a turn-around road section of the initial driving road section in the road network geomagnetic reference library by adopting a maximum correlation coefficient method to correspondingly obtain a straight matching position, a left-turn matching position, a right-turn matching position and a turn-around matching position;
s7: taking the maximum correlation coefficient peak value corresponding to the straight-going matching position, the left-turning matching position, the right-turning matching position and the U-turn matching position as the optimal matching position of the vehicle at the current moment;
s8: repeating the steps S6 and S7 until more than 5 continuous optimal matching positions belong to the same road section, and determining the current driving road section after the vehicle passes through the intersection;
s9: matching and resolving the actually measured geomagnetic sequence and a reference geomagnetic sequence corresponding to the current driving road section in the road network geomagnetic reference library by adopting a maximum correlation coefficient method to obtain a current matching position, and realizing vehicle positioning under the current driving road section;
s10: and performing fusion filtering processing on the driving position estimation value and the current matching position to obtain a fusion result serving as a vehicle driving position, so as to realize vehicle positioning in a road network environment.
2. The method according to claim 1, wherein the method for obtaining the estimated value of the driving position of the vehicle in the road network environment comprises:
obtaining a starting position (e) of the vehicle0,n0) (ii) a Wherein e is0Is the initial east position, n0Is the initial north position;
according to the starting position (e)0,n0) Obtaining the estimated value (e) of the driving position at the k-th timek,nk) Specifically, the method comprises the following steps:
wherein e iskEast position at time k, nkNorth orientation at time k, diIs the mileage increment at the ith time, thetaiI is the heading angle at time i, i is 0,1,2, …, k-1, θkIs the heading angle, θ, at time kg,kMagnetic heading, θ, at time kbIs the declination.
3. The geomagnetic matching and positioning method for vehicles in road network environment according to claim 1, wherein the calculation method of the track difference comprises:
wherein, Delta trjlCalculating a value x for the driving position at the k-th timeDR,kTrack difference from the first road section, xDR,k＝(ek,nk) For driving position push at the k-th momentCalculation of value, xmap,nThe position of the nth sampling point theta of the first road section in the geomagnetic reference library of the road networkkIs the heading angle, θ, at time kmap,nThe N-th heading angle of the first road section in the road network geomagnetic reference library is 1,2, …, Nl，NlThe total number of sampling points of the first road segment is 1,2, …, and L is the total number of road segments in the road network geomagnetic reference library.
4. The geomagnetic matching and positioning method for vehicles in road network environment according to claim 1, wherein the estimated driving position value and the current matching position are subjected to fusion filtering, and the obtained fusion result as the driving position of the vehicle is specifically:
with east position error deltaekNorth position error δ nkMileage increment error δ dkAnd heading error delta thetakAs state vector X at time kkSpecifically, the method comprises the following steps:
Xk＝[δek,δnk,δdk,δθk]T
taking the difference value between the estimated value of the driving position and the matching position as an observation vector ZkSpecifically, the method comprises the following steps:
Zk＝[Δek,Δnk]T＝[eg,k-ek,ng,k-nk]
wherein (e)g,k,ng,k) Is the matching position at the k-th time, (e)k,nk) Is a driving position estimate at the k-th time;
obtaining a state equation according to the dead reckoning principle:
wherein, wnoise,eSystematic noise, w, for east positionnoise,nSystem noise, w, for north positionnoise,DSystem noise, w, in mileage incrementsnoise,θSystem noise that is a heading angle; delta ek+1、δnk+1、δdk+1And delta thetak+1East position error, north position error, mileage increment error and course error at the moment of k +1 respectively;
obtaining a state transition matrix phi from a state equationk：
Wherein d iskThe total driving range at the kth moment;
observation matrix HkComprises the following steps:
system noise matrix QkComprises the following steps:
wherein, deltae＝δnBeing position noise, δDAs mileage noise, δθThe noise is course noise;
the observed noise matrix R is:
wherein, we＝wnMatching the position error root mean square value;
fusing the results
As a vehicle travel position output.
5. A vehicle geomagnetic matching positioning system in a road network environment is characterized by comprising a magnetic sensor, a milemeter, an electronic compass, a dead reckoning module, a road network geomagnetic matching resolving module and a data fusion filtering module;
the magnetic sensor is used for acquiring geomagnetic field data on a vehicle running route in real time; the odometer is used for measuring the mileage driven by the vehicle; the electronic compass is used for measuring the running course of the vehicle; the dead reckoning module is used for obtaining a real-time driving position estimation value of the vehicle in a road network environment according to the mileage and the course;
the road network geomagnetic matching calculation module comprises an actual measurement geomagnetic sequence acquisition unit, an initial road section acquisition unit and a matching calculation unit; the measured geomagnetic sequence acquisition unit is used for sampling the geomagnetic field data at equal mileage intervals based on the mileage to obtain a measured geomagnetic sequence; the initial road section obtaining unit is used for determining an initial driving road section of the vehicle in a preset road network geomagnetic reference library based on the driving position calculation value by adopting a minimum track difference method; the matching and resolving unit is used for matching and resolving the actually measured geomagnetic sequence and a reference geomagnetic sequence corresponding to an initial driving road section in a road network geomagnetic reference library by adopting a maximum correlation coefficient method to obtain an initial matching position to realize vehicle positioning under the initial driving road section, then determining a current driving road section of a vehicle from road sections possibly driven behind the initial driving road section including a straight road section, a left-turning road section, a right-turning road section and a turning road section according to the maximum criterion of a correlation coefficient peak value when the vehicle drives to an intersection, and finally matching and resolving the actually measured geomagnetic sequence and the reference geomagnetic sequence corresponding to the current driving road section in the road network geomagnetic reference library to obtain the current matching position to realize vehicle positioning under the current driving road section;
and the data fusion filtering module is used for performing fusion filtering processing on the driving position calculation value and the current matching position, and an obtained fusion result is used as a vehicle driving position to realize vehicle positioning in a road network environment.
6. The system according to claim 5, wherein the dead reckoning module is configured to obtain the real-time estimated driving position of the vehicle in the road network environment according to the mileage and the heading by:
obtaining a starting position (e) of the vehicle0,n0) Wherein e is0Is the initial east position, n0Is the initial north position;
according to the starting position (e)0,n0) Obtaining the estimated value (e) of the driving position at the k-th timek,nk) Specifically, the method comprises the following steps:
wherein e iskEast position at time k, nkNorth orientation at time k, diIs the mileage increment at the ith time, thetaiI is the heading angle at time i, i is 0,1,2, …, k-1, θkIs the heading angle, θ, at time kg,kMagnetic heading, θ, at time kbIs the declination.
7. The system according to claim 5, wherein the initial road segment obtaining unit is configured to determine, in the preset road network geomagnetic reference library, an initial driving road segment of the vehicle by using a minimum track difference method, specifically:
acquiring a track difference between the driving position calculation value at each moment and each road section in the road network geomagnetic reference library, wherein the road section corresponding to the minimum value of the track difference at each moment is a road section to be selected for driving; if the corresponding road sections to be selected at more than 5 continuous moments are the same road section loptThen road section loptAs an initial travel segment of the vehicle.
8. The system according to claim 7, wherein the calculation method of the track difference comprises:
wherein, Delta trjlCalculating a value x for the driving position at the k-th timeDR,kTrack difference from the first road section, xDR,k＝(ek,nk) Estimate of the driving position at the k-th time, xmap,nThe position of the nth sampling point theta of the first road section in the geomagnetic reference library of the road networkkIs the heading angle, θ, at time kmap,nThe N-th heading angle of the first road section in the road network geomagnetic reference library is 1,2, …, Nl，NlThe total number of sampling points of the first road segment is 1,2, …, and L is the total number of road segments in the road network geomagnetic reference library.
9. The system as claimed in claim 5, wherein the data fusion filtering module is further configured to obtain a mileage increment error estimation value and a heading angle error estimation value, and feed back the mileage increment error estimation value and the heading angle error estimation value to the dead reckoning module, so that the dead reckoning module corrects the mileage and the heading according to the mileage increment error estimation value and the heading angle error estimation value.
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