Accurate positioning system for highway tunnel

Abstract

The invention discloses a highway tunnel precise positioning system comprising an intelligent positioning switching module which is responsible for monitoring GPS and WIFI signal intensity and positioning precision, and determining and selecting an optimal positioning mode in real time; the buffering and smoothing processing module is responsible for caching positioning data within a certain time period and processing the data by utilizing a smoothing algorithm; the optimization positioning algorithm module is responsible for simplifying and optimizing the regression prediction model; the environment self-adaptive configuration module is responsible for automatically adjusting a positioning algorithm and parameters according to the environment condition of the tunnel; the meteorological data fusion module is responsible for accessing real-time meteorological data and taking the real-time meteorological data as input parameters of a positioning algorithm; the user interaction module provides a user interface; in the invention, through an intelligent switching algorithm and a buffer mechanism, smooth switching of positioning modes inside and outside the tunnel is realized, continuity and accuracy of a positioning result are ensured, a positioning system adapted to different tunnel environment conditions is designed, and applicability and stability of the system are improved.

Description

Technical Field

[0001] The present invention relates to the technical field of highway tunnel positioning, and in particular to a highway tunnel precise positioning system. Background Art

[0002] With the development of information technology, positioning services are becoming more and more important and playing an indispensable basic supporting role. With the development of driverless cars and highway platoon technology, users and developers are increasingly in need of a stable and precise positioning technology for highway tunnels.

[0003] After searching, the invention patent with Chinese patent number CN114185072A discloses a seamless positioning system and method inside and outside highway tunnels based on regression prediction model, which belongs to the field of positioning technology. It adopts GPS positioning module outside the tunnel, WI FI positioning module inside the tunnel, seamless positioning module inside and outside the tunnel, and comprehensive map display module; it solves the problem that the traditional GPS positioning and WI FI positioning methods at the junction of the inside and outside of the tunnel cannot provide user location information, receives coordinate information from the GPS positioning module outside the tunnel or the WI FI positioning module inside the tunnel, predicts the user's coordinates based on the positioning information obtained inside or outside the tunnel, and transmits the user's predicted coordinates to the comprehensive map display module.

[0004] Compared with the existing technology, the invention patent with Chinese patent number CN114185072A, the seamless positioning module inside and outside the tunnel is based on the fusion positioning method of the regression prediction model, which realizes accurate seamless positioning inside and outside the tunnel. The regression prediction model can make a more accurate prediction of the user's position change based on a small number of sample points, and provide the user's position information with lower computational complexity.

[0005] However, when the above device is in use, there may be a delay in the switching of GPS and WIFI signals near the tunnel entrance, resulting in discontinuity in the positioning results, causing positioning drift or jumps during the switching process. The discontinuity and jumps in the positioning results will confuse the user and even mislead the user to make wrong driving decisions. Therefore, a highway tunnel precise positioning system is proposed. Summary of the invention

[0006] The purpose of the present invention is to solve the problem in the prior art that there may be a delay in the switching of GPS and WIFI signals near the tunnel entrance, resulting in discontinuity in positioning results, causing positioning drift or jump during the switching process. The discontinuity and jump of positioning results will confuse users and even mislead users to make wrong driving decisions. A highway tunnel precise positioning system is proposed to solve the problem that there may be a delay in the switching of GPS and WIFI signals near the tunnel entrance, resulting in discontinuity in positioning results, causing positioning drift or jump during the switching process, and the discontinuity and jump of positioning results will confuse users and even mislead users to make wrong driving decisions.

[0007] In order to achieve the above object, the present invention adopts the following technical solutions:

[0008] A highway tunnel precise positioning system, comprising:

[0009] Intelligent positioning switching module: responsible for monitoring the signal strength and positioning accuracy of GPS and WIFI (or other indoor positioning technologies such as Bluetooth, UWB, etc.), and making real-time judgments and selecting the optimal positioning method based on the preset algorithm;

[0010] Buffering and smoothing processing module: During the switching of positioning modes, it is responsible for caching positioning data within a certain period of time and processing these data using a smoothing algorithm to reduce the jump and fluctuation of positioning results;

[0011] Optimization positioning algorithm module: responsible for simplifying and optimizing the regression prediction model to reduce the amount of calculation and improve the calculation efficiency;

[0012] Environmental adaptive configuration module: responsible for automatically adjusting the positioning algorithm and parameters according to the environmental conditions such as the length, structure, and material of the tunnel to adapt to different tunnel environments;

[0013] Meteorological data fusion module: responsible for accessing real-time meteorological data (such as temperature, humidity, wind speed, visibility, etc.) and using it as input parameters for the positioning algorithm;

[0014] User interaction module: provides user interface;

[0015] When the intelligent positioning switching module determines that the positioning mode needs to be switched, it will notify the buffering and smoothing processing module to start caching the positioning data. The intelligent positioning switching module will pass the real-time signal strength and positioning accuracy data to the optimization positioning algorithm module. The environmental adaptive configuration module will pass the collected tunnel environmental parameter data to the optimization positioning algorithm module. The optimization positioning algorithm module automatically adjusts the algorithm parameters and configuration according to the environmental parameters to adapt to different tunnel environments. The meteorological data fusion module will pass the real-time meteorological data to the optimization positioning algorithm module. The optimization positioning algorithm module will make real-time corrections to the positioning algorithm according to the meteorological data to cope with the impact of weather changes on positioning accuracy.

[0016] The above technical solution further includes:

[0017] Furthermore, the intelligent positioning switching module includes a signal monitoring unit, a positioning accuracy evaluation unit, an intelligent switching algorithm unit and a positioning service unit. The signal monitoring unit is responsible for real-time collection of signal strength and stability data of GPS, WIFI (or other indoor positioning technologies such as Bluetooth, UWB), and the signal monitoring unit sends the collected signal strength and stability data to the positioning accuracy evaluation unit and the intelligent switching algorithm unit. The positioning accuracy evaluation unit is responsible for calculating the positioning accuracy of the current position using different positioning algorithms (such as GPS positioning algorithm, WIFI fingerprint positioning algorithm, Bluetooth / UWB positioning algorithm). The positioning accuracy evaluation unit sends the positioning accuracy evaluation result to the intelligent switching algorithm unit. The intelligent switching algorithm unit is responsible for deciding whether to switch the positioning mode according to the evaluation results of the signal strength and positioning accuracy, and calculating the optimal switching time and method. The intelligent switching algorithm unit sends a switching instruction to the positioning service unit, including the switching positioning mode, switching timing, etc. The positioning service unit is responsible for calling the corresponding positioning algorithm for positioning according to the instruction of the intelligent switching algorithm unit, and providing the positioning result to the application layer.

[0018] Furthermore, the buffering and smoothing processing module includes a positioning data collection unit, a data cache unit, a smoothing processing unit and a positioning service unit. The positioning data collection unit is responsible for collecting positioning data (such as GPS, WIFI, etc.) in real time and sending the data to the data cache unit. The data cache unit receives data from the positioning data collection unit and stores it in the cache. At the same time, it also provides cached data for the smoothing processing unit. The smoothing processing unit obtains cached data and real-time data from the data cache unit, applies a smoothing algorithm for processing, and outputs a smoothed positioning result. The positioning service unit receives the positioning result output by the smoothing processing unit and provides it to an application layer (such as a navigation system, a location tracking system, etc.). The positioning data collection unit transmits the positioning data to the data cache unit in real time. The data cache unit provides cached data and real-time data to the smoothing processing unit. The smoothing processing unit transmits the smoothed positioning result to the positioning service unit.

[0019] Furthermore, the smoothing processing unit uses a moving window average algorithm to perform on-site analysis and calculation:

[0020] Step 1: Determine the time window size for calculating the average power;

[0021] Step 2: Collect PV power data within a certain time window;

[0022] Step 3: Sum the collected power data and divide it by the size of the time window to get the average power value;

[0023] Step 4: Based on the average power value, determine whether the current photovoltaic power generation output is too high or too low;

[0024] Step 5: The moving window average algorithm needs to continuously update the time window. After each calculation of the average power, the time window is slid back by a time interval to continue collecting new power data.

[0025] Step 6: Repeat step 1, step 2, step 3, step 4 and step 5.

[0026] Further, the optimization positioning algorithm module includes a data collection unit, a data processing unit, a positioning algorithm unit, an adaptive learning module and a positioning service unit, the data collection unit is responsible for collecting positioning data in real time and transmitting it to the data processing unit, the data processing unit is responsible for receiving data from the data collection unit, performing preprocessing and acceleration processing, and sending the processed data to the positioning algorithm unit, the positioning algorithm unit is responsible for receiving the processed data, executing the positioning algorithm, and calling the adaptive learning module for parameter adjustment and model update as needed. The positioning result will be sent to the positioning service unit, the adaptive learning module is responsible for collecting and analyzing positioning data, adjusting algorithm parameters and model structure, and sending the updated algorithm parameters and model to the positioning algorithm unit, the positioning service unit is responsible for receiving the positioning result output by the positioning algorithm unit, and providing it to the application layer for use, the data collection unit transmits the positioning data to the data processing unit in real time, the data processing unit transmits the processed data to the positioning algorithm unit, the positioning algorithm unit provides the positioning data and performance evaluation results to the adaptive learning module, the adaptive learning module provides the updated algorithm parameters and model to the positioning algorithm unit, and the positioning algorithm unit transmits the positioning result to the positioning service unit.

[0027] Furthermore, the environment adaptive configuration module includes an environment parameter acquisition unit, an algorithm adaptive adjustment unit, a control unit and a hardware device unit. The environment parameter acquisition unit is responsible for collecting the environment parameter data in the tunnel in real time through various sensors installed in the tunnel (such as temperature sensors, humidity sensors, signal strength sensors, etc.). The environment parameter acquisition unit sends the collected data to the database management unit for storage, and may directly or indirectly affect the algorithm adaptive adjustment unit through the control unit. The algorithm adaptive adjustment unit is responsible for analyzing the characteristics of the tunnel environment according to the environment parameter data provided by the database management unit, and automatically adjusting the parameters and configuration of the positioning algorithm accordingly to improve the positioning accuracy and stability. The adjustment unit obtains environmental data from the environmental parameter acquisition unit. After adjusting the positioning algorithm, it may be necessary to feed back the adjustment results to the control unit or directly adjust the relevant hardware equipment (such as signal amplifier). The control unit is responsible for serving as the hub of the entire system, receiving instructions from the algorithm adaptive adjustment unit, and controlling the operation of relevant hardware equipment in the tunnel (such as adjusting the power of the signal amplifier). The control unit communicates with the algorithm adaptive adjustment unit in a two-way manner, receives adjustment instructions and sends execution results; at the same time, it may also conduct indirect data interaction with the environmental parameter acquisition unit and the database management unit. The hardware equipment unit is responsible for equipment used for auxiliary positioning in the tunnel, including signal amplifiers, positioning base stations, etc. These devices adjust their working status according to the instructions of the control unit.

[0028] Furthermore, the meteorological data fusion module includes a meteorological data interface unit, a data fusion unit, a real-time data processing unit and a positioning algorithm unit. The meteorological data interface unit is responsible for accessing and verifying meteorological data and passing the data to the data fusion unit. The data fusion unit is responsible for receiving meteorological data and positioning data, performing data fusion processing, and passing the processing results to the real-time data processing unit. The real-time data processing unit is responsible for real-time processing and analysis of the fused data, evaluating the positioning results, and feeding the results back to the positioning algorithm and the data fusion algorithm. The positioning algorithm unit is responsible for receiving the processed data as input parameters, executing the positioning algorithm, and outputting the positioning results. At the same time, it also needs to adjust the algorithm parameters and configuration according to the feedback mechanism.

[0029] Furthermore, the data fusion unit uses Kalman filtering to perform fusion processing on multi-source heterogeneous data, including the following steps:

[0030] Initialization: Setting the initial state estimate and its covariance matrix P0;

[0031] predict:

[0032] State prediction: Use the state transfer matrix F and the optimal estimate of the previous moment To predict the current state

[0033] Covariance prediction: using the state transfer matrix F and the covariance P of the previous moment k-1 To predict the covariance P at the current moment k :P k =FP k-1 F T +Q, where Q is the covariance matrix of the process noise;

[0034] renew:

[0035] Calculate the Kalman gain: Use the prediction covariance P k and the covariance R of the observation noise to calculate the Kalman gain K k :K k =P k H T (HP k H T +R) -1 ; Where H is the observation matrix;

[0036] State update: Use Kalman gain K k , predicted value z k and predicted status To update the optimal state estimate at the current moment

[0037] Covariance update: using Kalman gain K k and the predicted covariance P k To update the covariance Pk at the current moment: Pk = (IK k H)P k ; where I is the identity matrix;

[0038] Iteration:

[0039] The optimal state estimate at the current moment The and covariance Pk are used as the initial state estimate and covariance at the next moment, and the prediction and update are repeated.

[0040] The present invention has the following beneficial effects:

[0041] 1. In the present invention, the smooth switching of the positioning modes inside and outside the tunnel is achieved through the intelligent switching algorithm and the buffer mechanism, thereby ensuring the continuity and accuracy of the positioning results.

[0042] 2. In the present invention, the regression prediction model is optimized, the amount of calculation is reduced, the calculation efficiency is improved, and the demand for real-time positioning is met.

[0043] 3. In the present invention, a positioning system adapted to different tunnel environmental conditions is designed to improve the applicability and stability of the system, and a meteorological data fusion module is introduced to perform real-time corrections on the positioning algorithm to cope with the impact of weather changes on positioning accuracy. BRIEF DESCRIPTION OF THE DRAWINGS

[0044] Figure 1 This is a system block diagram of a highway tunnel precise positioning system proposed by the present invention. DETAILED DESCRIPTION

[0045] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0046] See also Figure 1 As shown, the present invention is a highway tunnel precise positioning system, comprising:

[0047] Intelligent positioning switching module: responsible for monitoring the signal strength and positioning accuracy of GPS and WIFI (or other indoor positioning technologies such as Bluetooth, UWB, etc.), and making real-time judgments and selecting the optimal positioning method based on the preset algorithm;

[0048] Buffering and smoothing processing module: During the switching of positioning modes, it is responsible for caching positioning data within a certain period of time and processing these data using a smoothing algorithm to reduce the jump and fluctuation of positioning results;

[0049] Optimization positioning algorithm module: responsible for simplifying and optimizing the regression prediction model to reduce the amount of calculation and improve the calculation efficiency;

[0050] Environmental adaptive configuration module: responsible for automatically adjusting the positioning algorithm and parameters according to the environmental conditions such as the length, structure, and material of the tunnel to adapt to different tunnel environments;

[0051] Meteorological data fusion module: responsible for accessing real-time meteorological data (such as temperature, humidity, wind speed, visibility, etc.) and using it as input parameters for the positioning algorithm;

[0052] User interaction module: provides user interface;

[0053] When the intelligent positioning switching module determines that the positioning mode needs to be switched, it will notify the buffering and smoothing processing module to start caching the positioning data. The intelligent positioning switching module will pass the real-time signal strength and positioning accuracy data to the optimization positioning algorithm module. The environmental adaptive configuration module will pass the collected tunnel environmental parameter data to the optimization positioning algorithm module. The optimization positioning algorithm module automatically adjusts the algorithm parameters and configuration according to the environmental parameters to adapt to different tunnel environments. The meteorological data fusion module will pass the real-time meteorological data to the optimization positioning algorithm module. The optimization positioning algorithm module will make real-time corrections to the positioning algorithm according to the meteorological data to cope with the impact of weather changes on positioning accuracy.

[0054] The working principle of the highway tunnel precise positioning system proposed by the present invention is that the intelligent positioning switching module works to monitor the signal strength and positioning accuracy of GPS, WIFI (or other indoor positioning technologies) in real time, applies a preset algorithm to analyze the signal data, evaluates the reliability, stability and accuracy of each positioning method, and selects the optimal positioning method in real time according to the evaluation results;

[0055] When it is determined that the positioning mode needs to be switched, the buffer and smoothing processing module is notified to start caching the data of the positioning mode to be replaced. During the process of switching the positioning mode, the buffer and smoothing processing module caches the old positioning data within a certain period of time and the preliminary data of the new positioning mode, and applies the moving window average algorithm to process the cached data to reduce the jump and fluctuation caused by the switching of the positioning mode, and improve the stability and continuity of the positioning results;

[0056] The environment adaptive configuration module collects environmental parameters such as the length, structure, and material of the tunnel through sensors, and passes the real-time environmental parameters to the optimization positioning algorithm module. The optimization positioning algorithm module automatically adjusts the algorithm parameters and configurations according to the environmental parameters to adapt to different tunnel environments, such as adjusting the signal attenuation model and path loss factor. The meteorological data fusion module receives real-time meteorological data (temperature, humidity, wind speed, visibility, etc.) and passes the meteorological data as input parameters to the optimization positioning algorithm module for real-time correction of the positioning algorithm, taking into account the impact of weather changes on signal propagation and positioning accuracy.

[0057] The positioning result after smoothing and correction of environmental and meteorological data is generated by the optimization positioning algorithm module, and the user interaction module displays the final positioning result on the user interface for users to view.

[0058] In one embodiment, for the above-mentioned intelligent positioning switching module, the intelligent positioning switching module includes a signal monitoring unit, a positioning accuracy evaluation unit, an intelligent switching algorithm unit and a positioning service unit. The signal monitoring unit is responsible for real-time collection of signal strength and stability data of GPS, WIFI (or other indoor positioning technologies such as Bluetooth, UWB), and the signal monitoring unit sends the collected signal strength and stability data to the positioning accuracy evaluation unit and the intelligent switching algorithm unit. The positioning accuracy evaluation unit is responsible for using different positioning algorithms (such as GPS positioning algorithm, WIFI fingerprint positioning algorithm, Bluetooth / UWB positioning algorithm) to calculate the positioning accuracy of the current position. The positioning accuracy evaluation unit sends the positioning accuracy evaluation result to the intelligent switching algorithm unit. The intelligent switching algorithm unit is responsible for deciding whether to switch the positioning mode according to the evaluation results of the signal strength and positioning accuracy, and calculating the optimal switching time and method. The intelligent switching algorithm unit sends a switching instruction to the positioning service unit, including the switching positioning mode, switching timing, etc. The positioning service unit is responsible for calling the corresponding positioning algorithm for positioning according to the instruction of the intelligent switching algorithm unit, and providing the positioning result to the application layer.

[0059] In one embodiment, for the above-mentioned buffering and smoothing processing module, the buffering and smoothing processing module includes a positioning data collection unit, a data cache unit, a smoothing processing unit and a positioning service unit. The positioning data collection unit is responsible for collecting positioning data (such as GPS, WIFI, etc.) in real time and sending these data to the data cache unit. The data cache unit receives data from the positioning data collection unit and stores it in the cache. At the same time, it also provides cached data for the smoothing processing unit. The smoothing processing unit obtains the cached data and real-time data from the data cache unit, applies a smoothing algorithm for processing, and outputs a smoothed positioning result. The positioning service unit receives the positioning result output by the smoothing processing unit and provides it to the application layer (such as a navigation system, a position tracking system, etc.). The positioning data collection unit transmits the positioning data to the data cache unit in real time. The data cache unit provides the cached data and real-time data to the smoothing processing unit. The smoothing processing unit transmits the smoothed positioning result to the positioning service unit.

[0060] In one embodiment, for the above-mentioned smoothing processing unit, the smoothing processing unit processes the cached data using a moving window average algorithm:

[0061] Step 1: Determine the time window size for calculating the average power;

[0062] Step 2: Collect PV power data within a certain time window;

[0063] Step 3: Sum the collected power data and divide it by the size of the time window to get the average power value;

[0064] Step 4: Based on the average power value, determine whether the current photovoltaic power generation output is too high or too low;

[0065] Step 5: The moving window average algorithm needs to continuously update the time window. After each calculation of the average power, the time window is slid back by a time interval to continue collecting new power data.

[0066] Step 6: Repeat step 1, step 2, step 3, step 4 and step 5.

[0067] In one embodiment, for the above-mentioned optimization positioning algorithm module, the optimization positioning algorithm module includes a data collection unit, a data processing unit, a positioning algorithm unit, an adaptive learning module and a positioning service unit, the data collection unit is responsible for collecting positioning data in real time and transmitting it to the data processing unit, the data processing unit is responsible for receiving data from the data collection unit, performing preprocessing and acceleration processing, and sending the processed data to the positioning algorithm unit, the positioning algorithm unit is responsible for receiving the processed data, executing the positioning algorithm, and calling the adaptive learning module for parameter adjustment and model update as needed. The positioning result will be sent to the positioning service unit, the adaptive learning module is responsible for collecting and analyzing positioning data, adjusting algorithm parameters and model structure, and sending the updated algorithm parameters and model to the positioning algorithm unit, the positioning service unit is responsible for receiving the positioning result output by the positioning algorithm unit, and providing it to the application layer for use, the data collection unit transmits the positioning data to the data processing unit in real time, the data processing unit transmits the processed data to the positioning algorithm unit, the positioning algorithm unit provides the positioning data and performance evaluation results to the adaptive learning module, the adaptive learning module provides the updated algorithm parameters and model to the positioning algorithm unit, and the positioning algorithm unit transmits the positioning result to the positioning service unit.

[0068] In one embodiment, for the above-mentioned environment adaptive configuration module, the environment adaptive configuration module includes an environment parameter acquisition unit, an algorithm adaptive adjustment unit, a control unit and a hardware device unit. The environment parameter acquisition unit is responsible for collecting the environment parameter data in the tunnel in real time through various sensors installed in the tunnel (such as temperature sensors, humidity sensors, signal strength sensors, etc.). The environment parameter acquisition unit sends the collected data to the database management unit for storage, and may directly or indirectly affect the algorithm adaptive adjustment unit through the control unit. The algorithm adaptive adjustment unit is responsible for analyzing the characteristics of the tunnel environment according to the environment parameter data provided by the database management unit, and automatically adjusting the parameters and configuration of the positioning algorithm accordingly to improve the positioning accuracy and stability. Qualitatively, the algorithm adaptive adjustment unit obtains environmental data from the environmental parameter collection unit. After adjusting the positioning algorithm, it may be necessary to feed back the adjustment result to the control unit or directly adjust the relevant hardware equipment (such as signal amplifier). The control unit is responsible for serving as the hub of the entire system, receiving instructions from the algorithm adaptive adjustment unit, and controlling the operation of relevant hardware equipment in the tunnel (such as adjusting the power of the signal amplifier). The control unit communicates with the algorithm adaptive adjustment unit in a two-way manner, receives adjustment instructions and sends execution results; at the same time, it may also conduct indirect data interaction with the environmental parameter collection unit and the database management unit. The hardware equipment unit is responsible for equipment used for auxiliary positioning in the tunnel, including signal amplifiers, positioning base stations, etc. These devices adjust their working status according to the instructions of the control unit.

[0069] In one embodiment, for the above-mentioned meteorological data fusion module, the meteorological data fusion module includes a meteorological data interface unit, a data fusion unit, a real-time data processing unit and a positioning algorithm unit. The meteorological data interface unit is responsible for accessing and verifying meteorological data and passing the data to the data fusion unit. The data fusion unit is responsible for receiving meteorological data and positioning data, performing data fusion processing, and passing the processing results to the real-time data processing unit. The real-time data processing unit is responsible for real-time processing and analysis of the fused data, evaluating the positioning results, and feeding back the results to the positioning algorithm and the data fusion algorithm. The positioning algorithm unit is responsible for receiving the processed data as input parameters, executing the positioning algorithm, and outputting the positioning results. At the same time, it also needs to adjust the algorithm parameters and configuration according to the feedback mechanism.

[0070] In one embodiment, for the above data fusion unit, the data fusion unit uses Kalman filtering to perform fusion processing on multi-source heterogeneous data, including the following steps:

[0071] Initialization: Setting the initial state estimate and its covariance matrix P0;

[0072] predict:

[0073] State prediction: Use the state transfer matrix F and the optimal estimate of the previous moment To predict the current state

[0074] Covariance prediction: using the state transfer matrix F and the covariance P of the previous moment k-1 To predict the covariance P at the current moment k :P k =FP k-1 F T +Q, where Q is the covariance matrix of the process noise;

[0075] renew:

[0076] Calculate the Kalman gain: Use the prediction covariance P k and the covariance R of the observation noise to calculate the Kalman gain K k :K k =P k H T (HP k H T +R) -1 ; Where H is the observation matrix;

[0077] State update: Use Kalman gain K k , predicted value z k and predicted status To update the optimal state estimate at the current moment

[0078] Covariance update: using Kalman gain K k and the predicted covariance P k To update the covariance Pk at the current moment: Pk = (IK k H)P k ; where I is the identity matrix;

[0079] Iteration:

[0080] The optimal state estimate at the current moment The and covariance Pk are used as the initial state estimate and covariance at the next moment, and the prediction and update are repeated.

[0081] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A highway tunnel precise positioning system, characterized in that: include: Intelligent positioning switching module: responsible for monitoring the signal strength and positioning accuracy of GPS and WIFI, and making real-time judgments and selecting the optimal positioning method; Buffering and smoothing processing module: responsible for caching positioning data within a certain period of time and processing these data using smoothing algorithms; Optimization positioning algorithm module: responsible for simplifying and optimizing the regression prediction model; Environmental adaptive configuration module: responsible for automatically adjusting the positioning algorithm and parameters according to the environmental conditions of the tunnel; Meteorological data fusion module: responsible for accessing real-time meteorological data and using it as input parameters for positioning algorithms; User interaction module: provides user interface; When the intelligent positioning switching module determines that the positioning mode needs to be switched, it will notify the buffering and smoothing processing module to start caching the positioning data. The intelligent positioning switching module will pass the real-time signal strength and positioning accuracy data to the optimization positioning algorithm module. The environmental adaptive configuration module will pass the collected tunnel environmental parameter data to the optimization positioning algorithm module. The meteorological data fusion module will pass the real-time meteorological data to the optimization positioning algorithm module.

2. A highway tunnel precise positioning system according to claim 1, characterized in that: The intelligent positioning switching module includes a signal monitoring unit, a positioning accuracy evaluation unit, an intelligent switching algorithm unit and a positioning service unit. The signal monitoring unit is responsible for collecting the signal strength and stability data of GPS and WIFI in real time. The signal monitoring unit sends the collected signal strength and stability data to the positioning accuracy evaluation unit and the intelligent switching algorithm unit. The positioning accuracy evaluation unit is responsible for calculating the positioning accuracy of the current position using different positioning algorithms. The positioning accuracy evaluation unit sends the positioning accuracy evaluation result to the intelligent switching algorithm unit. The intelligent switching algorithm unit is responsible for deciding whether to switch the positioning mode according to the evaluation results of the signal strength and positioning accuracy, and calculating the optimal switching time and method. The intelligent switching algorithm unit sends a switching instruction to the positioning service unit. The positioning service unit is responsible for calling the corresponding positioning algorithm for positioning according to the instruction of the intelligent switching algorithm unit, and providing the positioning result to the application layer.

3. A highway tunnel precise positioning system according to claim 1, characterized in that: The buffer and smoothing processing module includes a positioning data collection unit, a data cache unit, a smoothing processing unit and a positioning service unit. The positioning data collection unit is responsible for collecting positioning data in real time and sending the data to the data cache unit. The data cache unit receives data from the positioning data collection unit and stores it in the cache. At the same time, the data cache unit provides cached data for the smoothing processing unit. The smoothing processing unit obtains the cached data and real-time data from the data cache unit, applies a smoothing algorithm for processing, and outputs a smoothed positioning result. The positioning service unit receives the positioning result output by the smoothing processing unit. The positioning data collection unit transmits the positioning data to the data cache unit in real time. The data cache unit provides the cached data and real-time data to the smoothing processing unit. The smoothing processing unit transmits the smoothed positioning result to the positioning service unit.

4. A highway tunnel precise positioning system according to claim 3, characterized in that: The smoothing processing unit processes the cached data using a moving window average algorithm: Step 1: Determine the time window size for calculating the average power; Step 2: Collect PV power data within a certain time window; Step 3: Sum the collected power data and divide it by the size of the time window to get the average power value; Step 4: Based on the average power value, determine whether the current photovoltaic power generation output is too high or too low; Step 5: The moving window average algorithm needs to continuously update the time window. After each calculation of the average power, the time window is slid back by a time interval to continue collecting new power data. Step 6: Repeat step 1, step 2, step 3, step 4 and step 5.

5. A highway tunnel precise positioning system according to claim 1, characterized in that: The optimized positioning algorithm module includes a data acquisition unit, a data processing unit, a positioning algorithm unit, an adaptive learning module and a positioning service unit. The data acquisition unit is responsible for collecting positioning data in real time and transmitting it to the data processing unit. The data processing unit is responsible for receiving data from the data acquisition unit, performing preprocessing and acceleration processing, and sending the processed data to the positioning algorithm unit. The positioning algorithm unit is responsible for receiving the processed data, executing the positioning algorithm, and calling the adaptive learning module for parameter adjustment and model update as needed. The positioning result will be sent to the positioning service unit. The adaptive learning module is responsible for collecting and analyzing positioning data, adjusting algorithm parameters and model structure, and sending the updated algorithm parameters and model to the positioning algorithm unit. The positioning service unit is responsible for receiving the positioning result output by the positioning algorithm unit and providing it to the application layer for use. The data acquisition unit transmits the positioning data to the data processing unit in real time. The data processing unit transmits the processed data to the positioning algorithm unit. The positioning algorithm unit provides the positioning data and performance evaluation results to the adaptive learning module. The adaptive learning module provides the updated algorithm parameters and model to the positioning algorithm unit. The positioning algorithm unit transmits the positioning result to the positioning service unit.

6. A highway tunnel precise positioning system according to claim 1, characterized in that: The environment adaptive configuration module includes an environment parameter collection unit, an algorithm adaptive adjustment unit, a control unit and a hardware device unit. The environment parameter collection unit is responsible for real-time collection of environment parameter data in the tunnel. The environment parameter collection unit sends the collected data to the database management unit for storage, and directly or indirectly affects the algorithm adaptive adjustment unit through the control unit. The algorithm adaptive adjustment unit is responsible for analyzing the characteristics of the tunnel environment according to the environment parameter data provided by the database management unit, and automatically adjusting the parameters and configuration of the positioning algorithm accordingly. The algorithm adaptive adjustment unit obtains the environment data from the environment parameter collection unit, adjusts the positioning algorithm, and then feeds back the adjustment result to the control unit. The control unit is responsible for serving as the hub of the entire system, receiving instructions from the algorithm adaptive adjustment unit, and controlling the operation of related hardware devices in the tunnel. The control unit communicates with the algorithm adaptive adjustment unit in a two-way manner, receives adjustment instructions and sends execution results; at the same time, the control unit and the algorithm adaptive adjustment unit perform indirect data exchange with the environment parameter collection unit and the database management unit. The hardware device unit is responsible for the equipment used for auxiliary positioning in the tunnel.

7. A highway tunnel precise positioning system according to claim 1, characterized in that: The meteorological data fusion module includes a meteorological data interface unit, a data fusion unit, a real-time data processing unit and a positioning algorithm unit. The meteorological data interface unit is responsible for accessing and verifying meteorological data and passing the data to the data fusion unit. The data fusion unit is responsible for receiving meteorological data and positioning data, performing data fusion processing, and passing the processing results to the real-time data processing unit. The real-time data processing unit is responsible for real-time processing and analysis of the fused data, evaluating the positioning results, and feeding the results back to the positioning algorithm and the data fusion algorithm. The positioning algorithm unit is responsible for receiving the processed data as input parameters, executing the positioning algorithm, and outputting the positioning results. At the same time, the positioning algorithm unit adjusts the algorithm parameters and configuration according to the feedback mechanism.

8. A highway tunnel precise positioning system according to claim 1, characterized in that: The data fusion unit uses Kalman filtering to perform fusion processing on multi-source heterogeneous data, including the following steps: Initialization: Setting the initial state estimate and its covariance matrix P0; predict: State prediction: Use the state transfer matrix F and the optimal estimate of the previous moment To predict the current state Covariance prediction: using the state transfer matrix F and the covariance P of the previous moment k-1 To predict the covariance P at the current moment k :P k =FP k-1 F T +Q, where Q is the covariance matrix of the process noise; renew: Calculate the Kalman gain: Use the prediction covariance P k and the covariance R of the observation noise to calculate the Kalman gain K k :K k =P k H T (HP k H T +R) -1 ; Where H is the observation matrix; State update: Use Kalman gain K k , predicted value z k and predicted status To update the optimal state estimate at the current moment Covariance update: using Kalman gain K k and the predicted covariance P k To update the covariance Pk at the current moment: Pk = (IK k H)P k ; where I is the identity matrix; Iteration: The optimal state estimate at the current moment The and covariance Pk are used as the initial state estimate and covariance at the next moment, and the prediction and update are repeated.

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