Networking optimization method of strip-shaped CORS reference maintenance network

Abstract

The invention discloses a networking optimization method for a strip-shaped CORS reference maintenance network, and the method comprises the steps: S1, DT subdivision: selecting all reference sites along a railway, and carrying out the DT subdivision, so as to form a triangulation network, so as to guarantee that the circumcircle of each triangle does not contain any other sites; s2, optimizing baseline configuration, including graph construction, distance initialization, priority queue establishment, path updating and shortest path tree construction; and S3, final optimization and implementation of the baseline network. According to the method, a redundant heterogeneous long baseline which is easy to introduce a large error is eliminated by reconstructing a CORS station network type through an independent baseline, the baseline resolving precision is remarkably improved, and error propagation is reduced, especially in a long distance and a complex terrain; according to the method, the resolving time is remarkably shortened, the response speed and the processing capacity of the whole network are improved, and the reliability and the continuity of the CORS service are improved.

Description

Technical Field

[0001] The present invention relates to the field of railway surveying and mapping engineering, and in particular to a networking optimization method for a strip-shaped CORS reference maintenance network. Background Art

[0002] The Continuously Operating Reference Station System (CORS) is a critical component of the spatial data infrastructure. As a next-generation infrastructure, it not only serves global and regional location and time requirements but also possesses extremely important scientific and practical value. CORS enables long-term and transient monitoring of crustal movement, playing an irreplaceable role in understanding the dynamic changes of the global and regional crust. Furthermore, it provides high-precision spatial positioning services and diversified information services, which are crucial for fields such as meteorological status monitoring, disaster prevention, and urban planning. As the core infrastructure for establishing and maintaining global and regional coordinate reference frames, CORS is widely adopted by the International Earth Rotation and Reference Frame Service (IERS) and many countries and regions. These reference frames provide precise benchmarks for the Global Positioning System, ensuring data consistency and reliability across borders and globally.

[0003] For specific applications along railway lines, zonal CORS networks need to be specifically designed to suit their unique geographic and service requirements. These networks must be able to provide continuous and reliable data to support high-precision track monitoring and maintenance work, which is critical to ensuring railway safety and efficiency.

[0004] When the locations of the reference stations are already determined, traditional network calculations usually use a full baseline method to maintain the baseline of the CORS stations. This leads to several problems in the ribbon CORS network:

[0005] 1. Data redundancy: The full baseline method may include redundant measurements, which increases the complexity and cost of data processing.

[0006] 2. Heterogeneous Networks: Zip-shaped CORS networks along railways often have heterogeneous networks, meaning they contain diverse baselines of varying lengths. Excessively long baselines not only easily introduce significant errors but can also affect data stability and accuracy due to environmental factors (such as multipath effects).

[0007] 3. Degraded service quality: The existence of heterogeneous networks may lead to unstable service quality when providing real-time services, especially in railway applications with high precision requirements. Summary of the Invention

[0008] In order to solve the problems existing in the prior art, the present invention provides a networking optimization method for a banded CORS baseline maintenance network, which can effectively improve the efficiency and accuracy of baseline solution and has good stability.

[0009] To this end, the present invention adopts the following technical solutions:

[0010] A method for optimizing a network configuration for maintaining a banded CORS benchmark includes the following steps:

[0011] S1, DT segmentation: All reference stations along the railway are selected for DT segmentation to form a triangulated network, ensuring that the circumscribed circle of each triangle does not contain any other stations;

[0012] S2, optimizes the baseline configuration, including the following steps:

[0013] S21, graph construction: Perform shortest path optimization on the triangulated network after DT segmentation in S1, initialize the CORS sites and the graph G(V,E) connecting these sites, where the vertex set V represents all CORS sites, and the edge set E represents the connections between sites. The weight of each edge is determined according to the actual distance or signal transmission requirements.

[0014] S22, distance initialization: For each vertex v in the graph G(V,E), set the source point s, and the distance from the source point s to itself dist[s] = 0, s is the geographic location center or the CORS site with the most network connections; set the initial distance of all other vertices to the source point s as dist[v] = ∞, where v ≠ s, indicating that the distance from the source point to these vertices is unknown or unreachable before the algorithm starts;

[0015] S23, use a priority queue to store all vertices, and sort the queue by the value of dist[v] so that the vertex with the shortest path to the source point can be extracted from it each time;

[0016] S24, path update: extract vertex u from the priority queue, which is the vertex with the shortest distance currently considered; traverse all adjacent vertices v of vertex u, and update the shortest path of each adjacent vertex. If a shorter path from vertex v to the source can be found through vertex u, the shortest path of vertex v is updated and the priority queue is adjusted;

[0017] S25, construction of the shortest path tree: After processing all vertices, the array dist[] stores the shortest path length from the source point s to every other vertex in the graph;

[0018] S3, final optimization and implementation of the baseline network, the specific steps are as follows:

[0019] S31, Network Verification and Adjustment:

[0020] (1) Simulation test: simulate the optimized CORS network in a virtual environment, simulating different usage scenarios and environmental conditions to test the stability and responsiveness of the network;

[0021] (2) Performance evaluation: Based on the simulation test results, performance evaluation is performed, focusing on the network response time, data accuracy, and error rate;

[0022] (3) Adjust optimization parameters: Based on the results of performance evaluation, adjust the configuration parameters of the network, including adjusting the connection method between sites, changing the location of certain sites, or optimizing the data transmission path.

[0023] Wherein, S1 includes the following sub-steps:

[0024] S11, data collection: collect the coordinate data of the benchmark stations along the railway and arrange them in ascending order of x coordinates to obtain the coordinate data set P of the benchmark stations = {p1, p2, p3, ..., p n}, where p i =(X i ,Y i ), represents the geographical coordinates, i = 1 to n, n is the total number of benchmark sites;

[0025] S12, initializing the super triangle: adding two auxiliary points p to the periphery of all points in the coordinate data set P. -1 and p -2 These two auxiliary points and any extreme point p0 in the data set P form a super triangle p0p -1 p -2 , the super triangle is large enough to contain all points p i ;

[0026] S13, for super triangle p0p -1 p -2 Every point p in i , determine which triangle Δp falls within the current DT segmentation m-1 p m p m+1 In the example, m+1≤n, by connecting p i to Δp m-1 p m p m+1 The vertices m-1, m, m+1 generate three new triangles Δp i p m p m+1 ,Δp i p m-1 p m and Δp i p m-1 p m+1 ;

[0027] S14, edge validity check: Perform a DT validity check on the edges of each newly formed triangle. If the DT condition is met, proceed to step S17. If not, there must be two adjacent triangles △ABC and △ABD, and their common side AB is an illegal edge, so proceed to step S15.

[0028] S15, edge flipping: deleting the common side AB and connecting CD to form two new triangles △ACD and △BCD;

[0029] S16, redundant edge cleaning: After all illegal edges are processed, remove the auxiliary point p -1 and p -2 and its related edges to obtain the DT decomposition of the pure point set P; perform a final check to ensure that all triangles meet the circumscribed circle condition, so that the entire triangulation conforms to the strict definition of DT decomposition.

[0030] The extreme point mentioned in S12 is the leftmost, rightmost, topmost or bottommost point in the coordinate data set P.

[0031] The core of this invention is an optimized independent baseline networking strategy. First, a triangulated network is generated by performing a DT triangulation on a specified set of benchmark sites, ensuring that the circumcircle of each triangle does not contain any other benchmark points. These triangles are then treated as vertices and edges of a graph, where the weight of each edge is defined based on the Euclidean distance between vertices. Dijkstra's algorithm is applied to this graph to find the shortest path, forming an independent baseline network. This optimizes the network structure and improves overall efficiency.

[0032] Compared with the prior art, the present invention has the following beneficial effects:

[0033] 1. This invention reconstructs the CORS station network using independent baselines, eliminating redundant, heterogeneous long baselines that can easily introduce significant errors. This significantly improves baseline solution accuracy and reduces error propagation, especially over long distances and in complex terrain. This optimization supports the precise positioning and intelligent management of rail transit systems, providing a strong technical foundation for rail transit safety and efficiency.

[0034] 2. By applying the Dijkstra algorithm to optimize path selection, the present invention significantly reduces solution time and improves the response speed and processing capacity of the overall network;

[0035] 3. The present invention reduces stability issues caused by network heterogeneity by optimizing network networking and improves the reliability and continuity of CORS services. BRIEF DESCRIPTION OF THE DRAWINGS

[0036] Figure 1This is the network diagram before strip networking optimization;

[0037] Figure 2 This is the optimized network diagram for strip networking. DETAILED DESCRIPTION

[0038] The technical solution of the present invention is described in detail below with reference to the accompanying drawings and embodiments.

[0039] The present invention's method for optimizing the network of a ribbon-shaped CORS baseline maintenance network utilizes CORS stations already deployed along the railway, employs DT segmentation and independent baselines, and reconstructs the CORS network by simulating user trajectories. The method includes the following steps:

[0040] S1, DT segmentation: Select all benchmark stations along the railway line for DT segmentation to form a triangulated network, ensuring that the circumscribed circle of each triangle does not contain any other stations. The specific steps include the following:

[0041] S11, data collection: collect the coordinate data of the benchmark stations along the railway, and arrange them in ascending order of x coordinates (in the direction of the railway), and obtain the coordinate data set P of the benchmark stations = {p1, p2, p3, ..., p n}, where p i =(X i ,Y i ), represents the geographical coordinates, i = 1 ~ n, n is the total number of benchmark sites.

[0042] S12, initializing the super triangle: adding two auxiliary points p to the periphery of all points in the coordinate data set P. -1 and p -2 These two auxiliary points and any extreme point p0 in the data set P form a super triangle p0p -1 p -2 This super triangle should be large enough to contain all points p i The purpose of establishing this super triangle is to simplify boundary processing at the beginning and end of the algorithm and ensure that all points are included inside.

[0043] You can choose the leftmost, rightmost, topmost, or bottommost point in the point set as the extreme point. The specific direction of the point to be selected depends on the distribution of the point set and the specific needs of the segmentation.

[0044] S13, for super triangle p0p -1 p -2 Every point p in i , determine which triangle Δp falls within the current DT segmentation m-1 p m p m+1In the example, m+1≤n, by connecting p i to Δp m-1 p m p m+1 The vertices m-1, m, m+1 generate three new triangles Δp i p m p m+1 ,Δp i p m-1 p m and Δp i p m-1 p m+1 .

[0045] S14, edge validity check: Perform DT validity check on the edges of each newly formed triangle. If the DT condition is met, execute step S17; if the DT condition is not met, there must be two adjacent triangles △ABC and △ABD, and their common side is AB (illegal side), execute step S15.

[0046] S15, edge flipping: delete the common side AB and connect CD to form two new triangles △ACD and △BCD.

[0047] S17, redundant edge cleaning: After all illegal edges are processed, remove the auxiliary point p -1 and p -2 and its related edges, and obtain the DT decomposition of the pure point set P. A final check is performed to ensure that all triangles meet the circumcircle condition, so that the entire triangulation conforms to the strict definition of DT decomposition.

[0048] S2. Optimizing baseline configuration: Determining the shortest path is crucial in baseline configuration for railway CORS stations. Dijkstra's algorithm, a well-known single-source shortest path algorithm, effectively processes and optimizes path lengths between vertices in a graph. It is suitable for baseline optimization in CORS networks to ensure transmission efficiency and accuracy. The specific steps for optimizing baseline configuration are as follows:

[0049] S21, Graph Construction: Perform shortest path optimization on the triangulated network generated by DT in S1. Initialize the CORS sites and the graph G(V,E) connecting them. The vertex set V represents all CORS sites, and the edge set E represents the connections between sites. The weight of each edge is determined based on the actual distance or signal transmission requirements.

[0050] S22, distance initialization: For each vertex v in the graph G(V,E), set the source point s, and the distance from the source point s to itself is zero dist[s] = 0, where s is usually the geographic location center or the CORS site with the most network connections; set the initial distances of all other vertices to the source point s to infinity, that is, dist[v] = ∞, where v≠s, indicating that before the algorithm starts, the distances from the source point to these vertices are unknown or unreachable.

[0051] S23, use a priority queue (usually implemented based on a binary heap) to store all vertices. The queue is sorted by the value of dist[v] so that the vertex with the shortest path from the source point can be extracted each time.

[0052] S24, path update: Extract vertex u from the priority queue, which is the vertex with the shortest distance currently considered. Traverse all adjacent vertices v of vertex u and update the shortest path for each adjacent vertex. If a shorter path from vertex v to the source can be found through vertex u, update the shortest path for vertex v and adjust the priority queue.

[0053] S25, construction of the shortest path tree: After processing all vertices, the array dist[] stores the shortest path length from the source point s to each other vertex in the graph.

[0054] S3, Final Optimization and Implementation of the Baseline Network: After completing the DT segmentation and optimization of the baseline configuration, this step focuses on the final adjustment, verification, and implementation of the network to ensure that the CORS network can meet the expected performance standards in actual applications. The specific steps are as follows:

[0055] S31, Network Verification and Adjustment:

[0056] (1) Simulation test: Perform simulation tests on the optimized CORS network in a virtual environment. Simulate different usage scenarios and environmental conditions to test the stability and responsiveness of the network.

[0057] (2) Performance evaluation: Perform performance evaluation based on simulation test results, focusing on key indicators such as network response time, data accuracy, and error rate.

[0058] (3) Adjust optimization parameters: Based on the results of performance evaluation, adjust the configuration parameters of the network, including adjusting the connection method between sites, changing the location of certain sites, or optimizing the data transmission path.

[0059] This completes the network optimization.

[0060] After completing the network optimization, carry out on-site implementation:

[0061] (1) Deploy sites: After ensuring that all parameters and configurations are optimized, begin deploying CORS sites in the field. Ensure that each site is installed strictly according to the optimized design.

[0062] (2) On-site testing: After deployment, each site will be tested to ensure that network performance in the field is consistent with expectations. Any problems encountered will be quickly diagnosed and corrected.

[0063] Afterwards, ongoing monitoring and maintenance:

[0064] (1) Establish a monitoring system: Establish a 24 / 7 monitoring system for the CORS network to track the network's operating status and performance in real time.

[0065] (2) Regular maintenance: Develop a regular maintenance plan, including hardware inspections, software updates, and performance reassessments.

[0066] (3) Technical support: Provide continuous technical support to solve any technical problems encountered by users during use.

Claims

1. A method for optimizing a network configuration for maintaining a CORS benchmark, comprising the following steps: S1, DT segmentation: All reference stations along the railway are selected for DT segmentation to form a triangulated network, ensuring that the circumscribed circle of each triangle does not contain any other stations; S2, optimizes the baseline configuration, including the following steps: S21, graph construction: Perform shortest path optimization on the triangulated network after DT segmentation in S1, initialize the CORS sites and the graph G(V,E) connecting these sites, where the vertex set V represents all CORS sites, and the edge set E represents the connections between sites. The weight of each edge is determined according to the actual distance or signal transmission requirements. S22, distance initialization: For each vertex v in the graph G(V,E), set the source point s, and the distance from the source point s to itself dist[s] = 0, s is the geographic location center or the CORS site with the most network connections; set the initial distance of all other vertices to the source point s as dist[v] = ∞, where v ≠ s, indicating that the distance from the source point to these vertices is unknown or unreachable before the algorithm starts; S23, use a priority queue to store all vertices, and sort the queue by the value of dist[v] so that the vertex with the shortest path to the source point can be extracted from it each time; S24, path update: extract vertex u from the priority queue, which is the vertex with the shortest distance currently considered; traverse all adjacent vertices v of vertex u, and update the shortest path of each adjacent vertex. If a shorter path from vertex v to the source can be found through vertex u, the shortest path of vertex v is updated and the priority queue is adjusted; S25, construction of the shortest path tree: After processing all vertices, the array dist[] stores the shortest path length from the source point s to every other vertex in the graph; S3, final optimization and implementation of the baseline network, the specific steps are as follows: S31, Network Verification and Adjustment: (1) Simulation test: simulate the optimized CORS network in a virtual environment, simulating different usage scenarios and environmental conditions to test the stability and responsiveness of the network; (2) Performance evaluation: Based on the simulation test results, performance evaluation is performed, focusing on the network response time, data accuracy, and error rate; (3) Adjust optimization parameters: Based on the results of performance evaluation, adjust the configuration parameters of the network, including adjusting the connection method between sites, changing the location of certain sites, or optimizing the data transmission path.

2. The network optimization method according to claim 1, characterized in that: S1 includes the following sub-steps: S11, data collection: collect the coordinate data of the benchmark stations along the railway and arrange them in ascending order of x coordinates to obtain the coordinate data set P of the benchmark stations = {p1, p2, p3, ..., p n }, where p i =(X i ,Y i ), represents the geographical coordinates, i = 1 to n, n is the total number of benchmark sites; S12, initializing the super triangle: adding two auxiliary points p to the periphery of all points in the coordinate data set P. -1 and p -2 These two auxiliary points and any extreme point p0 in the data set P form a super triangle p0p -1 p -2 , the super triangle is large enough to contain all points p i ; S13, for super triangle p0p -1 p -2 Every point p in i , determine which triangle Δp falls within the current DT segmentation m-1 p m p m+1 In the example, m+1≤n, by connecting p i to Δp m-1 p m p m+1 The vertices m-1, m, m+1 generate three new triangles Δp i p m p m+1 ,Δp i p m-1 p m and Δp i p m-1 p m+1 ; S14, edge validity check: Perform a DT validity check on the edges of each newly formed triangle. If the DT condition is met, proceed to step S17. If not, there must be two adjacent triangles △ABC and △ABD, and their common side AB is an illegal edge, so proceed to step S15. S15, edge flipping: deleting the common side AB and connecting CD to form two new triangles △ACD and △BCD; S16, redundant edge cleaning: After all illegal edges are processed, remove the auxiliary point p -1 and p -2 and its related edges to obtain the DT decomposition of the pure point set P; perform a final check to ensure that all triangles meet the circumscribed circle condition, so that the entire triangulation conforms to the strict definition of DT decomposition.

3. The network optimization method according to claim 2, characterized in that: The extreme point mentioned in S12 is the leftmost, rightmost, topmost or bottommost point in the coordinate data set P.

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