CN107094288B - Train locating method based on clustering wireless sensor network network under major long tunnel environment - Google Patents
Train locating method based on clustering wireless sensor network network under major long tunnel environment Download PDFInfo
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Abstract
The invention discloses the train locating methods based on clustering wireless sensor network network under a kind of major long tunnel environment, the following steps are included: S1, to its poincare half plane is unfolded after tunnel horizontal segmentation, establish the space reflection relationship between three-dimensional tunnel and the two-dimensional surface of expansion, the objective plane disposed using the poincare half plane of expansion as WSN；S2, square net is divided on mapped two-dimensional surface, dispose WSN node according to grid；S3, parameter Estimation is carried out to train running speed, Doppler frequency shift and wireless sending and receiving transmission time delay difference；S4, train position estimation.The present invention is by establishing the mapping relations of three-dimensional tunnel and two-dimensional surface, using two-dimensional map plane as objective plane, carry out reasonable WSN node deployment and effective parameter Estimation, Optimization Mechanism, conscientiously it solves and how to dispose WSN in major long tunnel, and the pinpoint technical problem of train progress how to be advanced using WSN to high speed.
Description
Technical Field
The invention belongs to the technical field of train positioning, and relates to a train positioning method based on a wireless sensor network, in particular to a train positioning method based on a clustered wireless sensor network under a railway long tunnel environment.
Background
In recent years, as the number of high-speed railway tunnels which are put into use or are being built and planned to be built in China increases, the existence of long tunnels and extra-long tunnels is more and more common. The function of train positioning in the high-speed rail operation in the tunnel is mainly embodied in the following 2 aspects: (1) the ground control center performs interval control according to the position information of the train to ensure the safe interval of the train which tracks the running; (2) the vehicle-mounted equipment obtains the position and speed information of the train, can control according to the speed-mode curve, and can avoid repeated braking of the train and improve the running efficiency compared with the step control only carried out according to the speed. The core content of the intelligent railway transportation system is how to accurately detect the train position to control the train operation and the like by using a high-speed rail as a modern intelligent system.
However, the train positioning research in the long tunnel (with kilometer length) is still in the starting stage. Because GPS can not implement positioning in the tunnel, causing positioning blind area, the technical means of train positioning in the tunnel mainly adopts wired mode, including track circuit positioning, odometer positioning, inquiry-transponder positioning, cross induction loop positioning, etc., which have the defects of low positioning accuracy, incapability of real-time continuous positioning, high maintenance cost caused by setting trackside equipment, etc.
The Wireless Sensor Network (WSN) has the characteristics of low cost, wide coverage, easy deployment and maintenance and the like, and is a solution for positioning and tracking a real-time train. At present, researchers have made many researches on a WSN positioning algorithm, however, how to deploy the WSN in a long and large tunnel and how to accurately position a high-speed train by using the WSN still face a plurality of technical problems, and the invention makes innovative researches on the problems.
Disclosure of Invention
Aiming at the technical problems, the invention provides a train positioning method based on a clustering wireless sensor network in a long and large tunnel environment, which carries out reasonable WSN node deployment and an effective parameter estimation and optimization mechanism by establishing a mapping relation between a three-dimensional tunnel and a two-dimensional plane and taking the two-dimensional mapping plane as a target plane, thereby practically solving various technical problems of how to deploy WSN in the long and large tunnel and how to accurately position a train running at high speed by using the WSN.
The invention realizes the purpose through the following technical scheme:
a train positioning method based on a clustering wireless sensor network in a long tunnel environment comprises the following steps:
s1, horizontally dividing the tunnel, expanding the upper half plane of the tunnel, establishing a space mapping relation between the actual three-dimensional tunnel and the expanded two-dimensional plane, and taking the expanded upper half plane as a target plane for deploying the WSN;
s2, dividing a square grid on the mapped two-dimensional plane, and deploying wireless sensor network nodes according to the divided grid; defining 3 WSN nodes of common nodes, cluster head nodes and sink nodes; the common node is responsible for performing azimuth angle measurement of the target node and receiving information from the target node; the cluster head node is responsible for communicating with common nodes in the cluster and communicating with adjacent cluster head nodes; the sink node is responsible for receiving multi-hop positioning information from the cluster head node and transmitting the information to receiving equipment outside the tunnel;
s3, aiming at the deviation of the target node position estimation caused by the delay difference of high-speed train operation and wireless receiving and transmitting, performing parameter estimation on the train operation speed, the Doppler frequency shift and the delay difference of wireless receiving and transmitting;
s4, building a functional relation between the train position estimation coordinates before and after the deviation by using the estimated parameters, and obtaining the corrected train position by using a least square method LS as an optimization tool.
As an optimization scheme of the scheme, 2 embedded current sensors ECS arranged in series are configured on a train to estimate the train running speed v, and the Doppler frequency shift is performed based on the estimated value of the train running speed vf m And wireless receiving and transmitting transmission delay differencet m And (6) estimating.
As an optimization scheme of the scheme, in the step 4, the train position is estimated by using a least square method assisted by a target azimuth angle.
As an optimization scheme of the scheme, in the step 2, based on the coverage efficiency and the network connectivity, the side length of the square grid is determined according to a wireless link budget theory considering the special environment of the tunnel.
As an optimization scheme of the scheme, in the step 2, based on the wireless sensor network node deployment of the divided square grids based on the clustering, each cluster is composed of 4 square grids, a common node is located at the center of the grid, a cluster head node is located at the center of the cluster, a sink node is located at two ends of a tunnel, 3 common nodes participate in a target positioning algorithm in each cluster, and 1 common node provides communication redundancy.
The invention has the beneficial effects that:
1. the spatial mapping relation between the three-dimensional tunnel and the two-dimensional plane is established, and the complexity of WSN deployment is reduced under the condition that a problem target is not weakened;
2. in the WSN node deployment, a wireless link budget theory considering the special environment of the tunnel is utilized, and the influence of the tunnel wall and the like on wireless signals is fully considered, so that the node distribution has better connectivity and uniformity and can provide certain communication redundancy;
3. considering the influence of parameters such as train running speed, Doppler frequency shift, wireless receiving/transmitting transmission delay difference and the like on the final train position positioning, an effective estimation mechanism is designed for the parameters so as to improve the precision of a positioning result;
4. researching train position deviation caused by azimuth angle quantization error and parameter estimation error, and completing target azimuth angle auxiliary train positioning by using a least square method as an optimization tool;
5. the technical problems of how to effectively deploy the WSN in the long and large tunnel and how to position the train running at high speed by using the WSN are practically solved.
Drawings
FIG. 1 is a schematic diagram of a mapping between a three-dimensional tunnel and a two-dimensional plane in the cluster-based WSN train positioning method of the present invention;
FIG. 2 is a schematic diagram of grid shape selection in the cluster-based WSN train positioning method of the present invention;
FIG. 3 is a schematic diagram of grid and node deployment in the cluster-based WSN train positioning method of the present invention;
FIG. 4 is a schematic diagram of a train positioning principle in the cluster WSN-based train positioning method of the present invention;
fig. 5 is a correlation characteristic curve of speed and output signals in the cluster-based WSN train positioning method of the present invention.
Detailed Description
The invention and its effects will be further explained with reference to the drawings and the embodiments.
The invention researches a train positioning method based on a clustering wireless sensor network under a long tunnel environment, which comprises the following steps:
s1, horizontally dividing the tunnel, expanding the upper half plane of the tunnel, establishing a space mapping relation between the actual three-dimensional tunnel and the expanded two-dimensional plane, and taking the expanded upper half plane as a target plane for deploying the tunnel wireless sensor network WSN. The railway tunnel is cylindrical, and the sensor nodes are arranged on the tunnel wall or the tunnel ground, so that the problem of three-dimensional space is solved, and the complexity of WSN node arrangement is increased; the invention proposes that the upper half plane of the tunnel is expanded after the tunnel is horizontally divided, and the expanded upper half plane is taken as a target plane for the WSN deployment of the tunnel, so that a space mapping relation is established between the actual three-dimensional tunnel and the two-dimensional plane (as shown in figure 1). The establishment of this mapping relationship is based on the following facts: compared with a mapped two-dimensional plane, the WSN network connectivity of the three-dimensional tunnel is better because the communication distance of any 2 WSN receiving and sending nodes in the three-dimensional tunnel is slightly shorter than that of the two-dimensional plane, so that the WSN node deployment research on the mapped two-dimensional plane can not weaken the target of WSN deployment in the three-dimensional tunnel.
S2, dividing a square grid on the mapped two-dimensional plane, and deploying wireless sensor network nodes according to the divided grid; defining 3 WSN nodes including a common node (represented by SN), a cluster head node (represented by RN) and a Sink node (represented by Sink); the common node is responsible for performing azimuth angle measurement of the target node and receiving information from the target node; the cluster head node is responsible for communicating with common nodes in the cluster and communicating with adjacent cluster head nodes; the aggregation node is responsible for receiving multi-hop positioning information from the cluster head node and transmitting the information to receiving equipment outside the tunnel.
The method comprises the steps of firstly dividing a region into regular grids, and then deploying the nodes, wherein the nodes are deployed on a two-dimensional plane mapped by a three-dimensional tunnel, the WSN nodes belong to a node deployment problem covered by a deterministic region, and the common method comprises the steps of dividing the region into regular grids, and then deploying the nodes, wherein mathematically, a regular polygon is used for covering a plane region without gaps or overlapping, and available shapes comprise 3 types of shapes, namely, a regular triangle, a square and a regular hexagon, then selecting the most suitable shape? from the 3 types of shapes, the WSN grid facing the method has different constraint conditions and optimization targets from the selection problem of cell shapes of a cellular mobile communication network, in order to meet the constraint condition b of WSN anchor node deployment, the WSN taking cluster head nodes (RNs) as relay nodes has full connectivity, the coverage efficiency of regions with different grid shapes when the distances between adjacent RNs are the same (set as D) needs to be evaluated, the coverage area of the square grids is the largest as shown in figure 2, namely, the number of nodes required for realizing the region coverage of the square is the coverage area coverage is the square, otherwise, the square grids is determined based on the theoretical coverage of the wireless network coverage, the wireless network coverage area, the theoretical coverage of the square nodes is not considered, otherwise, the wireless network coverage of the square is larger coverage area, the square coverage area is determined based on the budget of the wireless network coverage of the wireless network deployment, the wireless network coverage of the square nodes, the square coverage of the wireless network
（2）
Wherein,P r receiving power for a node (in)dBmA meter),P t is the transmission power (in)dBmA meter),G T 、G R gain for transmitting and receiving antenna, respectivelydBiA meter),PL(r) To receive and transmit at a distance ofrTime-of-flight path loss (to)dBA meter),L FM and (4) fading reserve in a tunnel environment.
When receiving powerP r Greater than or equal to receiver sensitivityβ(in dBm), the connectivity requirement of the network can be met. In the formula (2), the reaction mixture is,P t 、G T 、G R is a preset value, andPL(r)、L FM depending on the wireless transmission environment. For the long tunnel environment of the project, the curved tunnel with concrete lining material is consideredPL(r)、L FM As a reference, corresponding correction factors are given to the propagation environments of different types of tunnelsMF。MFThe value of (A) is determined by the following factors: the positions of the receiving and transmitting antennas of the nodes, tunnel lining materials, tunnel curvature, working frequency bands and QoS indexes (interruption probability) required by a train positioning algorithm. Then, will correctPL(r)、L FM Substituting the value into a path loss and Ricean fading model to obtain the value according to a wireless link budget formulaP r And calculate whenMaximum communication distance between nodes of timeD. As can be seen from FIG. 3, under the constraint condition of satisfying the network full connectivity, the side length of the square grid takes on the value ofD/2。
The ideal position of the cluster head node RN is located at the cluster center, and if the actually selected cluster head node RN is not located at the cluster center, the consumed energy is 2.4 times of the situation that the cluster head node RN is located at the cluster center. Therefore, from the perspective of green energy conservation and target positioning execution, the clustering WSN node deployment scheme adopted by the invention is shown in FIG. 3; in the figure, each cluster is composed of 4 square grids, common nodes are located at the center of the grids, cluster head nodes are located at the center of the clusters, sink nodes are located at two ends of a tunnel, 3 common nodes participate in a target positioning algorithm in each cluster, and 1 common node provides communication redundancy. Due to the arrangement, the node positions achieve better uniformity, and the optimal energy use efficiency is achieved, so that the network life cycle is prolonged, and the constraint condition of WSN node arrangement in a tunnel environment is met.
And S3, parameter estimation, wherein the deviation of the target node position is caused by the delay difference of the high-speed running and the wireless receiving and transmitting of the train, so that the running speed, the Doppler frequency shift and the delay difference of the wireless receiving and transmitting are estimated.
The following idea is adopted for train positioning, as shown in fig. 4. We have mapped the deployment of WSNs to a two-dimensional plane, and deployed WSN nodes, train locations on this plane: (x, y) Measurable by these nodesAnd obtaining azimuth angle information. Let (x m , y m ) For WSN within a single clustermThe position coordinates of the individual common nodes are,θ m is as followsmTarget azimuth measured by a common node (m=1,2,…, M). But the measured angle is due to the influence of doppler shift and radio wave propagation delayθmFrom the actual angleθm′There is always a deviation, resulting in an offset to the final train position fix.
2 embedded current sensors ECS arranged in series are configured on the train to complete the estimation of the running speed v of the train; the estimation of the train running speed v is specifically as follows:
let the output signals of 2 ECSs be s1(t) 、s2(t), and ssa1(t) 、ssa2(t) each represents s1S of (t)2(t) the velocity v can be determined by analyzing s1(t) 、s2The cross-correlation characteristic of (t) is obtained (as shown in FIG. 5) by shifting the corresponding peak of the waveform to
（3）
The estimate of the train running speed v is l/deltat.
Doppler shiftf m And wireless receiving and transmitting transmission delay differencet m Estimation of (2):
the high speed movement of the train causes the frequency of the received signal to be relative to the frequency of the transmitted signalf 0 Frequency shift of, i.e. Doppler shiftf m (ii) a Based on train running speedvEstimated value of (c), target azimuth measured by mth ordinary nodeθ m (0º <θ m <180 degrees) to obtain the doppler shift of the target nodef m =(f 0 * v/c)cosθ m (m=1,2,...M)；
Let (x m , y m )，m=1,2,.., MIs a firstmThe coordinates of a single common node are,θ m is as followsmThe target azimuth angle measured by the common node,θ m can be expressed asOr (180 degree)θ m ) Depending on the direction of movement of the train relative to the anchor node. First, themDistance between the common node and the target noded m The value of (d) is then estimated by:
（4）
whereinFor considering common nodes under the condition of Doppler frequency shiftmThe power of the received signal, wherein,s(f)is the received signal power spectral density. Is estimated to obtaind m Under the condition of (2), the estimated value of the wireless receiving and transmitting transmission delay difference can be obtained ast m =d m /c (m=1,2,…, M) Where c is the propagation velocity of the radio wave, which is equivalent to the speed of light.
S4, determining the position of the train, constructing a functional relation between the estimated coordinates of the position of the train before and after the deviation by using the estimated parameters, and obtaining the corrected position coordinates of the train by using a least square method LS as an optimization tool.
Estimating the position of the train by adopting a target azimuth angle assisted least square method;
specifically, on a two-dimensional plane mapped by the three-dimensional tunnel, setting a running track of a train, namely a target node, in the execution time of a positioning algorithm as a straight line, establishing a plane coordinate system, and taking the running track parallel to the target node as an x axis, wherein (1)x m , y m ) For WSN within a single clustermThe position coordinates of the individual common nodes are,θ m is as followsmMeasured by a common nodeTarget azimuth angle (m=1,2,…,M) The following equation set can be obtained
（5）
And is；
The above formula (5) is an overdetermined equation set, and is solved by adopting a least square method, and the cost function is defined as
（6）
In the formula,θ m is the value after the target azimuth is quantized;
due to Doppler shiftf m And wireless receiving and transmitting transmission delay differencet m Causing a shift in the azimuth of the target, i.e.θ m →θ m 'And the offset of the target position coordinates, i.e. (x, y) →: (b)x m ', y m ') (ii) a They satisfy the following relation:
（7）
wherein,(ii) a In the formula (5), the reaction mixture is,v、t m the values of the time delay difference are based on the running speed of the train and the estimated values of the wireless receiving and transmitting time delay difference in the step 3;
with the minimization of the formula (6) as the optimization target, the nodes of different common nodes are combinedx m ', y m ') After quantizationθ m '、t m Value is sent to the cluster head of the clusterAnd at the node, performing least square method train positioning estimation again by the cluster head node to obtain the position coordinates (x ', y') of the target node.
The above embodiments are merely exemplary and are not intended to limit the present invention, and it should be noted that other equivalent variations and modifications made by those skilled in the art in light of the teachings of the present invention should be considered to be within the scope of the present invention.
Claims (5)
1. A train positioning method based on a clustering wireless sensor network in a long tunnel environment is characterized by comprising the following steps:
s1, horizontally dividing the tunnel, expanding the upper half plane of the tunnel, establishing a space mapping relation between the actual three-dimensional tunnel and the expanded two-dimensional plane, and taking the expanded upper half plane as a target plane for deploying the WSN;
s2, dividing a square grid on the mapped two-dimensional plane, and deploying wireless sensor network nodes according to the divided grid; defining 3 WSN nodes of common nodes, cluster head nodes and sink nodes; the common node is responsible for performing azimuth angle measurement of the target node and receiving information from the target node; the cluster head node is responsible for communicating with common nodes in the cluster and communicating with adjacent cluster head nodes; the sink node is responsible for receiving multi-hop positioning information from the cluster head node and transmitting the information to receiving equipment outside the tunnel;
s3, aiming at the deviation of the target node position estimation caused by the delay difference of high-speed train operation and wireless receiving and transmitting, performing parameter estimation on the train operation speed, the Doppler frequency shift and the delay difference of wireless receiving and transmitting;
s4, building a functional relation between the train position estimation coordinates before and after the deviation by using the estimated parameters, and obtaining the corrected train position by using a least square method LS as an optimization tool.
2. The train positioning method based on the clustered wireless sensor network under the long tunnel environment according to claim 1, characterized in that: by being in a column2 embedded current sensors ECS arranged in series are configured on the train to complete the estimation of the train running speed v, and the Doppler frequency shift f is carried out based on the train running speed vmAnd wireless receiving and transmitting transmission delay difference tmAnd (6) estimating.
3. The train positioning method based on the clustered wireless sensor network under the long tunnel environment according to claim 1, characterized in that: in step S4, the train position is estimated by using a least square method assisted by a target azimuth.
4. The train positioning method based on the clustered wireless sensor network under the long tunnel environment according to claim 1, characterized in that: in step S2, based on the coverage efficiency and the network connectivity, the square grid determines the side length of the grid according to the wireless link budget theory considering the tunnel special environment.
5. The train positioning method based on the clustered wireless sensor network under the long tunnel environment according to claim 1, characterized in that: in the step S2, the wireless sensor network nodes based on clustering are deployed according to the divided square grids, each cluster is composed of 4 square grids, the common node is located at the center of the grid, the cluster head node is located at the center of the cluster, the sink node nodes are located at two ends of the tunnel, 3 common nodes participate in the target location algorithm in each cluster, and 1 common node provides communication redundancy.
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