Tunnel constructor continuous positioning system based on multi-source data fusion

Abstract

The invention belongs to the technical field of personnel positioning, and particularly discloses a tunnel construction personnel continuous positioning system based on multi-source data fusion, and the system comprises a positioning tag which comprises a GNSS positioning module, a UWB module, an IMU module, and a main control module; the GNSS base station is used for generating differential correction data; the anchor nodes are used for receiving the UWB signals and recording signal arrival timestamps; the main control module is configured to monitor a GNSS signal in real time, judge that a person is in a ground GNSS available area when the GNSS signal meets a certain condition, and switch to an RTK / PDR fusion positioning mode; and when the GNSS signal is completely lost or the quality is extremely poor, judging that a person enters underground or a GNSS shielding area, smoothly switching to a UWB / PDR fusion positioning mode, and performing positioning by using UWB distance measurement and IMU / PDR. According to the invention, the position tracking continuity of miners moving in different areas of a mining area can be guaranteed, and the coverage capability and adaptability in the whole range of the mining area are ensured.

Description

TECHNICAL FIELD

[0001] The present application belongs to the technical field of personnel positioning, and more particularly, to a tunnel construction personnel continuous positioning system based on multi-source data fusion. BACKGROUND

[0002] Mineral resources are an important foundation for the development of the national economy, and mineral exploitation operations involve complex geographical environments and high-risk working conditions. Whether it is an underground mine or an open-pit mine, real-time and high-precision position monitoring of operating personnel is a key link to ensure the safety of miners, improve production efficiency, and optimize resource scheduling. In particular, in the underground mine environment, the spatial structure is complex and variable, with roadways, mining fields, and chambers intersecting each other, and there are generally poor lighting, limited ventilation, and other adverse conditions, making it difficult to grasp the movement trajectory and position information of miners. At the same time, strong electromagnetic interference, signal blocking caused by equipment density, and potential gas and dust explosion hazards often occur in mining areas, which greatly increase the difficulty and uncertainty of personnel positioning. In the event of sudden accidents such as roof fall, rib spalling, water inrush, fire, or gas explosion, the ability to determine the precise location of trapped personnel in the shortest time directly affects the efficiency of rescue operations and the survival probability of miners. Therefore, it is of great practical significance and strategic value to build a system that can provide stable and reliable high-precision personnel positioning in complex mining environments.

[0003] For a long time, personnel positioning in mining areas has mainly relied on traditional manual check-in, regional identification, or simple wireless communication methods. These methods not only have low efficiency and are not timely in updating information, but also cannot provide accurate coordinates and dynamic trajectories of personnel, making it even more difficult to quickly locate personnel scattered throughout the mining area in emergency situations. With the development of wireless communication technology, some positioning technologies based on radio ranging, such as radio frequency identification (RFID), Wi-Fi positioning, ZigBee, and early ultra-wideband (UWB) technology, have begun to be introduced into mining areas. These technologies, while improving the timeliness of information acquisition to some extent, have limitations that are increasingly apparent in the extreme complexity of the mining environment, especially in underground mines. For example, RFID and Wi-Fi are susceptible to environmental interference and have severe signal attenuation, low positioning accuracy, and are easily blocked by metal structures and obstacles. Early UWB has high potential for accuracy, but in actual mine roadways, the problems of multipath effects and non-line-of-sight (NLOS) propagation are difficult to overcome, and the stability and accuracy of the signal are still insufficient to meet the high requirements of safety production.

[0004] Global Navigation Satellite System (GNSS), such as GPS, Beidou, etc., is a mature technology for realizing high-precision positioning in open areas. However, GNSS signals cannot penetrate the earth's crust and mine structure. For underground mines, GNSS signals are completely unavailable and cannot provide any positioning information. Even in open-pit mines or near mine ground facilities, signal shielding or multipath interference may occur near deep pit areas or tall equipment, affecting the positioning effect of GNSS. This makes it difficult for mine personnel, especially miners who need to frequently move underground and on the ground, to have a continuous positioning solution that seamlessly connects throughout the entire mine area.

[0005] Therefore, for miners who need to frequently move underground and on the ground, how to build a continuous positioning system for miners throughout the entire mine area is a difficult problem in current research. SUMMARY

[0006] In view of the defects of the prior art, the purpose of the present application is to provide a tunnel construction personnel continuous positioning system based on multi-source data fusion, which can ensure the continuity of position tracking of miners moving in different areas of the mine, and ensure the coverage ability and adaptability in the entire mine area.

[0007] To achieve the above purpose, in a first aspect, the present application provides a tunnel construction personnel continuous positioning system based on multi-source data fusion, comprising: a positioning tag worn on the construction personnel, including a GNSS positioning module, a UWB module, an IMU module and a main control module; a GNSS base station arranged in the ground area for receiving satellite signals and generating differential correction data based on its known position; a plurality of anchor nodes deployed in the underground area for receiving UWB signals emitted by the UWB module and recording signal arrival timestamps; The main control module is configured to: monitor the GNSS signals emitted by the GNSS positioning module in real time, combine the GNSS signals with the differential correction data when the GNSS signals meet the set conditions, calculate the first absolute position of the construction personnel through the RTK algorithm, calculate the relative position of the construction personnel running track through the PDR algorithm using the motion data collected by the IMU module, and then fuse the first absolute position and the relative position through the EKF algorithm to obtain the positioning information of the construction personnel; otherwise, combine the timestamps obtained by the anchor nodes with the spatial coordinates of the anchor nodes, calculate the distance difference between the construction personnel and the anchor nodes and solve the second absolute position of the construction personnel, then calculate the relative position of the construction personnel running track through the PDR algorithm using the motion data, and then fuse the absolute position and the relative position of the construction personnel through the EKF algorithm to obtain the positioning information of the construction personnel.

[0008] As a further preferred, the master module adopts a TDOA positioning model, determines the position of the construction personnel by measuring the distance information of the UVB signal reaching at least three anchor nodes with known coordinates, and solves the second absolute position of the construction personnel by solving a hyperbolic equation set.

[0009] As a further preferred, the master module communicates and cooperatively controls with the GNSS positioning module, the UWB module and the IMU module through an interface, and the interface is SPI, UART or IIC.

[0010] As a further preferred, the anchor nodes are deployed in underground tunnels, chambers and ground areas.

[0011] As a further preferred, the motion data collected by the IMU module includes gait detection, step length estimation and heading estimation data. As a further preferred, the IMU module includes a three-axis accelerometer, a three-axis gyroscope and a three-axis magnetometer.

[0012] As a further preferred, the positioning tag further includes a power management unit and a sound alarm module, the power management unit is used to provide power management for each module in the positioning tag, and the sound alarm module is used to send a sound alarm signal in a specific situation.

[0013] As a further preferred, the system further includes a data communication module for transmitting the obtained positioning information of the construction personnel to a server.

[0014] As a further preferred, the anchor node adopts an IP65 waterproof and explosion-proof shell.

[0015] In a second aspect, the application provides an application of the tunnel construction personnel continuous positioning system based on multi-source data fusion, which is applied in mines and underground engineering or tunnels and subway construction.

[0016] The tunnel construction personnel continuous positioning system based on multi-source data fusion provided by the application has the following effects: (1) The system continuously monitors the availability of GNSS signals. When the GNSS signals meet certain conditions, the system determines that the personnel are in the ground GNSS available area and switches to or preferentially uses the RTK / PDR fusion positioning mode. In this mode, the absolute position information provided by RTK is used as the main observation data of EKF, and PDR provides continuous relative motion information. EKF fusion uses high-precision RTK observation data to correct the calculated position of PDR, improves the overall positioning accuracy and robustness, and especially when the GNSS signal is temporarily interrupted, PDR can provide smooth transition. When the GNSS signal is completely lost or the quality is extremely poor, the system determines that the personnel are in the underground or GNSS shielding area, and smoothly switches to the UWB / PDR fusion positioning mode, which uses UWB ranging and IMU / PDR for positioning. This switching is based on real-time judgment of environmental signals, and since both fusion modes contain PDR information, the state estimation of EKF can provide continuity, making the switching process as smooth as possible, reducing positioning interruption or jump, and ensuring the continuity of the location tracking of the miners when moving in different areas of the mine.

[0017] (2) According to the signal environment of different areas in the mine, intelligently switch or fuse different positioning technology combinations. In the open area with good ground GNSS signal, the system mainly uses GNSS RTK technology for high-precision absolute positioning, and fuses with PDR data to improve the smoothness and robustness of positioning. In the underground mine area where GNSS signal is unavailable or limited, the system switches or focuses on using UWB technology and PDR data for fusion positioning. This way of dynamically adjusting the positioning strategy according to environmental characteristics ensures the coverage and adaptability of the system in the whole mine area. BRIEF DESCRIPTION OF DRAWINGS

[0018] Figure 1 is a structural block diagram of a tunnel construction personnel continuous positioning system based on multi-source data fusion provided by the embodiments of the present application; Figure 2 is a system software architecture flowchart provided by the embodiments of the present application; Figure 3 is a workflow diagram of a CORS system provided by the embodiments of the present application; Figure 4 is a TDOA hyperbolic positioning schematic diagram provided by the embodiments of the present application; Figure 5 is a PDR algorithm principle diagram provided by the embodiments of the present application. DETAILED DESCRIPTION

[0019] In order to make the purposes, technical solutions and advantages of the present application clearer, further detailed description will be given below in combination with the drawings and examples. It should be understood that the specific examples described herein are only used to explain the present application and not to limit the present application.

[0020] It should be understood that, in the description of the present application, the term "a plurality of" means two or more, unless otherwise explicitly and specifically limited; the terms "first" and "second" are used to distinguish different objects, not to describe the specific order of the objects.

[0021] The present application provides a tunnel construction personnel continuous positioning system based on multi-source data fusion, which can be applied to personnel positioning in mine and underground engineering, tunnel and subway construction. The following will mainly explain the application in mine and underground process.

[0022] As shown in Figure 1 The tunnel construction personnel continuous positioning system based on multi-source data fusion provided by the present application includes a positioning tag, a GNSS base station and a plurality of anchor nodes.

[0023] Among them, the positioning tag provided by the present application is worn on the construction personnel, which includes a GNSS positioning module, a UWB module, an IMU module and a main control module.

[0024] In the present application, the GNSS positioning module integrates a GNSS receiver, which is used to collect satellite observation data of the position of the miner and send GNSS signals to the main control module. The UWB module is used to send UVB signals. The IMU module includes three-axis acceleration, angular velocity and magnetometer, which is used to collect the motion data of the miner, specifically including gait detection, step length estimation and heading estimation data. The GNSS base station provided by the present application is arranged in the ground area, which is used to receive satellite signals sent by navigation satellites of GNSS system such as Beidou / GPS, and generate differential correction data based on its known position.

[0025] The plurality of anchor nodes provided by the present application are deployed in the underground area, which are used to receive UWB signals sent by the UWB module and record signal arrival time stamp.

[0026] The main control module provided in this application is configured to: monitor the GNSS signal emitted by the GNSS positioning module in real time; when the GNSS signal meets the set conditions, combine the GNSS signal with differential correction data, calculate the first absolute position of the construction personnel using the RTK algorithm, and calculate the relative position of the construction personnel's trajectory using the motion data collected by the IMU module using the PDR algorithm; then fuse the first absolute position and the relative position using the EKF algorithm to obtain the positioning information of the construction personnel; otherwise, when the GNSS signal fails, combine the timestamp obtained by the anchor node with the spatial coordinates of the anchor node, calculate the distance difference between the construction personnel and the anchor node and solve the second absolute position of the construction personnel, then calculate the relative position of the construction personnel's trajectory using the PDR algorithm, and then fuse the absolute position and the relative position of the construction personnel using the EKF algorithm to obtain the positioning information of the construction personnel.

[0027] The continuous positioning system for tunnel construction personnel based on multi-source data fusion provided in this application has the following effects: (1) The system continuously monitors the availability of GNSS signals. When the GNSS signal meets certain conditions, the system determines that the personnel are in a GNSS-available area on the ground and switches to or prioritizes the use of RTK / PDR fusion positioning mode. In this mode, the absolute position information provided by RTK serves as the main observation data for EKF, while PDR provides continuous relative motion information. EKF fusion utilizes high-precision RTK observation data to correct the estimated position of PDR, improving overall positioning accuracy and robustness. In particular, PDR can provide a smooth transition when the GNSS signal is briefly interrupted. When the GNSS signal is completely lost or of extremely poor quality, the system determines that the personnel have entered an underground or GNSS-shielded area and smoothly switches to UWB / PDR fusion positioning mode, using UWB ranging and IMU / PDR for positioning. This switching is based on real-time judgment of environmental signals, and since both fusion modes contain PDR information, the state estimation of EKF can provide continuity, making the switching process as smooth as possible, reducing positioning interruptions or jumps, and ensuring the continuity of position tracking for miners moving in different areas of the mining area.

[0028] (2) The system intelligently switches or fuses different positioning technology combinations according to the signal environment of different areas in the mining area. In open areas with good ground GNSS signals, the system mainly uses GNSS RTK technology for high-precision absolute positioning and fuses it with PDR data to improve the smoothness and robustness of positioning. In underground mine areas where GNSS signals are unavailable or limited, the system switches or focuses on using UWB technology to fuse positioning with PDR data. This method of dynamically adjusting the positioning strategy according to environmental characteristics ensures the system's coverage and adaptability throughout the entire mining area.

[0029] In one embodiment, the technical solution for achieving the above objective can be specifically as follows: Figure 1 As shown, a continuous positioning system for tunnel construction workers based on multi-source data fusion is provided, which consists of positioning tags worn by miners (or modules integrated into safety helmets) and positioning base stations (or UWB anchor nodes) deployed in key locations in the mining area (including underground roadways, chambers, and surface areas).

[0030] The system primarily comprises a main control module, a UWB module for underground positioning, a GNSS RTK module for surface positioning, an IMU module providing auxiliary information, an audible alarm module, and a power management unit. These modules communicate and coordinate with the main control module via interfaces such as SPI, UART, and IIC to jointly acquire, process, and transmit positioning information. The hardware design fully considers the harshness of the mining environment. Key components, such as the positioning base station, utilize high-protection-level housings (e.g., IP65 waterproof and explosion-proof), while the positioning tags emphasize lightweight and miniaturization to meet the needs of miners. Specific hardware circuit designs, such as the main control module, UWB module, RTK module, and IMU module, have been carefully selected and designed to ensure system performance and reliability.

[0031] like Figure 2 As shown, the system's software is built on the FreeRTOS real-time operating system and the ESP-IDF development framework, employing a layered modular design. The bottom layer is the hardware driver layer, responsible for interacting with various hardware modules; the middle layer provides abstract interfaces and task management; and the application layer implements functions such as location data acquisition, processing of the core location algorithm, data communication with the server via the MQTT protocol, and support for OTA remote firmware upgrades. Location-related tasks are designed to be executed concurrently as independent threads, exchanging and synchronizing data through message queues and semaphores.

[0032] The core of this system's high-precision continuous positioning lies in its multi-source data fusion positioning algorithm. The system can intelligently adopt different positioning modes or fusion strategies to address the differences between the surface and underground environments of the mining area.

[0033] In open areas with good GNSS signals in the mining area, the system primarily utilizes GNSS RTK technology for high-precision absolute positioning. RTK technology, by receiving differential correction data from the CORS base station network deployed in the mining area or from local base stations, can eliminate most errors related to satellite signal propagation, achieving centimeter-level positioning accuracy. For example... Figure 3 As shown, the RTK module receives satellite signals and sends the raw observation data to the data processing center to obtain corrections, and then uses the corrections to calculate the precise location.

[0034] In areas where GNSS signals are limited on the surface of the mining area, and in environments where GNSS signals are completely unavailable underground, the system relies on UWB technology and IMU data for fusion positioning. UWB technology uses multiple UWB anchor nodes with known coordinates deployed in underground tunnels to obtain distance information between the positioning tag and the anchor nodes using ranging principles. For example... Figure 4 As shown, this scheme uses the TDOA positioning model, which determines the tag's position by measuring the time difference of the signal arriving at different anchor nodes. Using the known coordinates of at least three anchor nodes R1, R2, and R3, the distance difference from tag M(x, y) to each anchor node is calculated as follows: With time difference Related. These distance differences form hyperbolas with the corresponding anchor nodes as foci, and the label's position is the intersection of these hyperbolas. For example, for anchor nodes R1, R2, and R3, the following system of distance difference equations can be established:

[0035] in, This represents the distance difference between the tag and anchor node i and anchor node j, where c is the electromagnetic wave propagation speed. These are the timestamps of the signals emitted by the tag arriving at anchor node i and anchor node j, respectively. denoted as , where are the two-dimensional coordinates of anchor node i and anchor node j respectively, and x, y are the coordinates of the positioning label to be solved.

[0036] By solving these nonlinear equations, the absolute position information obtained from UWB ranging can be obtained.

[0037] Meanwhile, the system uses the IMU module to collect the miners' movement data and estimates their relative positions and trajectories using the Pedestrian Dead Retrieval (PDR) algorithm. The PDR algorithm process is as follows: Figure 5 As shown, it includes gait detection, step size estimation, and heading estimation. Gait detection is typically based on the periodic analysis of acceleration signals. Step size estimation can be obtained through empirical or adaptive models, such as simplified linear models:

[0038] Where SL represents the step size and f represents the step frequency. and These are empirical parameters. Heading estimation uses IMU sensors (accelerometers and gyroscopes) and magnetometer data to determine the vehicle's attitude and orientation. For example, it uses Euler angles or quaternions to transform the magnetometer measurements from the vehicle's coordinate system to the navigation coordinate system, and then calculates magnetic north. Based on the estimated step size and heading, PDR calculates the relative position from the previous position. The basic kinematic formula is: in, , This indicates the relative position in the east and north directions at the end of step k. , Indicates the first The position at the end of the step, d k Let θ represent the step size at the k-th step. k This represents the heading angle at the k-th step.

[0039] Because the relative positioning of PDR accumulates errors over time, and UWB may experience significant measurement noise or interruptions in NLOS environments, this system employs the Extended Kalman Filter (EKF) algorithm to fuse UWB ranging data (obtaining distance information between the positioning tag and the anchor node using ranging principles) and PDR relative position (estimating the miner's relative position and trajectory). EKF, based on a linearized system model, combines the statistical characteristics of process noise and measurement noise to provide optimal estimation of the system state. In the UWB / PDR fusion mode, the EKF state vector can be defined as the PDR positioning error and parameters affecting PDR accuracy, for example:

[0040] in, , This refers to the positioning error of the PDR in the east and north directions. It is the step size estimation error. This refers to the heading estimation error. The system's state transition model describes how these errors evolve over time, while the observation model uses the residual between UWB ranging information and PDR-estimated distance as the observation. Observation vector Z k It can be defined as the combination of the differences between the distance measured by multiple UWB anchor nodes and the distance estimated from the current PDR position. For i anchor nodes:

[0041] in, It is the distance measurement value from the tag to the i-th anchor node by UWB at time k. It is the current position estimated by PDR at time k. To the coordinates of the i-th anchor node ( , The estimated distance is calculated as follows:

[0042] The EKF algorithm uses sparse or noisy absolute position information provided by UWB through iterative prediction and update steps to estimate and correct the EKF state vector (PDR error). The estimated error is then compensated into the PDR-calculated position, thereby achieving high-precision positioning of underground miners and effectively suppressing the cumulative drift of PDR.

[0043] To achieve seamless positioning between surface and underground areas in the mining area, the system employs an intelligent switching mechanism for environmental perception and positioning modes. The system continuously monitors GNSS signal availability. When GNSS signal conditions are met, the system determines that personnel are in a GNSS-available area and switches to or prioritizes the use of RTK / PDR fusion positioning mode. In this mode, the absolute position information provided by RTK serves as the primary observation data for EKF (External Kinematics), while PDR provides continuous relative motion information. EKF fusion utilizes high-precision RTK observation data to correct the PDR's calculated position, improving overall positioning accuracy and robustness, especially providing a smooth transition during brief GNSS signal interruptions. When GNSS signals are completely lost or of extremely poor quality, the system determines that personnel have entered underground or GNSS-shielded areas and smoothly switches to UWB / PDR fusion positioning mode, utilizing UWB ranging and IMU / PDR for positioning. This switching is based on real-time assessment of environmental signals, and because both fusion modes include PDR information, EKF state estimation provides continuity, making the switching process as smooth as possible and reducing positioning interruptions or jumps.

[0044] Through the aforementioned hardware and software co-design and multi-source data fusion positioning method, this system can effectively integrate the advantages of RTK, UWB and PDR technologies, overcome the limitations of single technologies in the complex environment of mining areas, achieve high-precision, continuous and reliable location tracking of mining personnel, and significantly improve the level of safety production management and emergency response capabilities in mining areas.

[0045] The implementation scheme of this application aims to solve the problem of high-precision continuous positioning of personnel in complex mining environments, especially in underground mines with no GNSS signal, areas with limited GNSS signal on the ground, and transitional areas between the two. Its core lies in constructing a system that integrates multiple positioning technologies such as RTK, UWB, and PDR, and achieving deep fusion and intelligent processing of multi-source data through an advanced extended Kalman filter (EKF) algorithm.

[0046] Specifically, the key technical features of this solution are reflected in the following aspects: First, the system intelligently switches between or fuses different positioning technologies based on the signal environment of different areas within the mining area. In open areas with good GNSS signals, the system primarily uses GNSS RTK technology for high-precision absolute positioning, fusing it with PDR data to improve the smoothness and robustness of the positioning. However, in underground mining areas where GNSS signals are unavailable or limited, the system switches to or emphasizes using UWB technology fused with PDR data for positioning. This dynamic adjustment of the positioning strategy based on environmental characteristics ensures the system's coverage and adaptability throughout the entire mining area.

[0047] Secondly, it innovatively combines ranging or location information acquired by UWB technology with relative motion trajectories calculated by IMU sensors using PDR algorithms for high-precision positioning in areas without GNSS signals, such as underground mines. Multiple UWB anchor nodes are deployed for TDOA ranging to obtain the absolute position information of the positioning tag as a reference. Simultaneously, acceleration and angular velocity data collected by IMU sensors are used to calculate the relative displacement of personnel through PDR algorithms such as gait detection, stride length estimation, and heading estimation. This combination fully utilizes the centimeter-level accuracy potential of UWB in local areas and the continuity of PDR without relying on external signals.

[0048] Third, the Extended Kalman Filter (EKF) algorithm is used as the core data fusion engine to perform real-time fusion processing of UWB and PDR data. The EKF model can effectively handle the nonlinear relationship between UWB ranging or position information and PDR-calculated trajectory. By using the absolute position information provided by UWB as the observation, it periodically corrects the accumulated relative position error of PDR. This allows the PDR positioning results to remain within a high accuracy range for a long time, overcoming the inherent error drift problem of PDR, and significantly improving the accuracy and stability of underground mine positioning. Even when the UWB signal is temporarily blocked or there is NLOS error, PDR can provide a smooth transition.

[0049] Fourth, it achieves seamless intelligent switching between the ground-based RTK / PDR fusion positioning mode and the underground UWB / PDR fusion positioning mode in the mining area. The system can sense the status of GNSS signals in real time (e.g., by monitoring the number of visible satellites and signal quality), and use this as a basis to determine the current environment and trigger the switching of positioning modes. This switching is smooth and continuous, thanks to the EKF algorithm's ability to use continuous motion information provided by PDR for state estimation in both modes, thereby avoiding positioning interruptions or jumps and ensuring the continuity of position tracking for miners moving in different areas of the mining area.

[0050] Fifth, the hardware and software provide reliable support for the aforementioned positioning methods. The hardware design employs modular, miniaturized, and high-protection-level components, ensuring the system's reliability and maintainability in the harsh environment of the mining area. The software design is based on a real-time operating system, enabling independent parallel operation and efficient collaboration of each functional module. It supports data communication based on the MQTT protocol and remote OTA firmware upgrades, further improving the system's practicality and manageability.

[0051] By combining the above key points, this system can provide high-precision, continuous, and reliable personnel positioning services in the complex environment of the mining area, effectively improving the level of safety production management and emergency response capabilities in the mining area.

[0052] The beneficial effects of this application are: The high-precision continuous positioning method and system for personnel in mining areas proposed in this application, based on the fusion of RTK, UWB, and PDR data, has undergone comprehensive software and hardware implementation and testing. Its effectiveness and superiority have been verified in a simulated complex mining environment (including simulated underground mines and surface areas). Actual test results show that this system can significantly improve the positioning accuracy, continuity, reliability, and energy efficiency of personnel in mining areas, effectively overcoming the limitations of existing single technologies or simple combinations of technologies.

[0053] In positioning accuracy tests conducted in a simulated underground mine environment, the system successfully achieved precise personnel location tracking using a UWB and PDR fusion algorithm. Even under complex conditions where obstacles obstruct UWB signal propagation occurs at non-line-of-sight (NLOS), the system's positioning error remained effectively controlled. By employing an extended Kalman filter (EKF) to fuse and correct UWB ranging data and PDR-calculated position, cumulative errors were significantly suppressed. Test results show that in a simulated line-of-sight (LOS) environment, the system's positioning accuracy is better than 5 cm; in the more challenging simulated non-line-of-sight (NLOS) environment, the positioning accuracy also reaches a level better than 10 cm. This level of accuracy far surpasses the performance of traditional Wi-Fi, RFID, or PDR technologies in similar complex environments, meeting the high requirements for refined personnel location management and emergency positioning in narrow mine tunnels and work areas.

[0054] In positioning tests conducted in a simulated mining area, the system utilized an RTK / PDR fusion algorithm. This fully leveraged the advantages of RTK in achieving high-precision absolute positioning in open areas, while combining PDR data to improve the smoothness of the positioning trajectory and its continuity during brief periods of RTK signal instability. Test results showed that the positioning accuracy in the simulated ground environment was better than 1 meter (root mean square error less than 1.414 meters). This accuracy is sufficient to meet the needs of personnel attendance, activity monitoring, and safety management in mining area facilities, roads, and entrances. Compared to the signal interference or obstruction problems that traditional single GNSS technology may encounter in some mining areas, the RTK / PDR fusion of this system provides a more stable and reliable ground positioning capability.

[0055] Another significant advantage of this application is the achievement of seamless and continuous positioning between the surface and underground areas of the mining area. Through the system's intelligent sensing of GNSS signal status and smooth switching mechanism of positioning modes, positioning services can be provided uninterruptedly when personnel move from the surface to the underground or vice versa. This eliminates the positioning blind spots or prolonged interruptions that may occur at area boundaries in traditional positioning schemes, ensuring that miners' location information is always available throughout the entire mining area and greatly improving the comprehensiveness of safety monitoring.

[0056] Furthermore, the system achieved its expected power consumption targets. Through carefully designed low-power hardware module selection and software optimization strategies, particularly the adoption of a high-efficiency power management unit and optimized communication protocols, the average current consumption of the positioning tag under stable operation is well below 250 mA. Combined with a 6000 mAh polymer lithium battery, the battery life after a single charge can reach approximately 24 hours, far exceeding the 12-hour single-shift work requirement, effectively reducing equipment maintenance frequency and charging burden, and improving system practicality. The system's MQTT data communication function and OTA remote upgrade function have also been tested, confirming the stability of data transmission and the feasibility of remote maintenance, providing convenience for system deployment and subsequent management.

[0057] In summary, the high-precision continuous positioning system for personnel in mining areas implemented in this application significantly improves positioning accuracy and continuity through the integration and intelligent processing of RTK, UWB, and PDR technologies. It effectively adapts to the complex and ever-changing geographical and signal environments of mining areas and exhibits excellent performance in terms of power consumption and reliability. These achievements provide solid technical support for improving operational safety in mining areas, optimizing management efficiency, and ensuring the safety of miners' lives.

[0058] Those skilled in the art will readily understand that the above description is merely a preferred embodiment of this application and is not intended to limit this application. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this application should be included within the protection scope of this application.

Claims

1. A continuous positioning system for tunnel construction personnel based on multi-source data fusion, characterized in that, include: The positioning tag, worn by construction workers, includes a GNSS positioning module, a UWB module, an IMU module, and a main control module; GNSS base stations are set up in ground areas to receive satellite signals and generate differential correction data based on their known locations; Multiple anchor nodes are deployed in the underground area to receive UWB signals emitted by the UWB module and record the signal arrival timestamp; The main control module is configured to: monitor the GNSS signal emitted by the GNSS positioning module in real time; when the GNSS signal meets the set conditions, combine the GNSS signal with differential correction data, calculate the first absolute position of the construction personnel using the RTK algorithm, and calculate the relative position of the construction personnel's trajectory using the PDR algorithm based on the motion data collected by the IMU module; then fuse the first absolute position and the relative position using the EKF algorithm to obtain the positioning information of the construction personnel; otherwise, combine the timestamp obtained by the anchor node with the spatial coordinates of the anchor node, calculate the distance difference between the construction personnel and the anchor node, and solve the second absolute position of the construction personnel; then calculate the relative position of the construction personnel's trajectory using the PDR algorithm based on the motion data; and finally fuse the absolute position and the relative position of the construction personnel using the EKF algorithm to obtain the positioning information of the construction personnel.

2. The continuous positioning system for tunnel construction personnel based on multi-source data fusion as described in claim 1, characterized in that, The main control module adopts the TDOA positioning model, which determines the position of the construction personnel by measuring the distance information of the UVB signal to at least three anchor nodes with known coordinates, and calculates the second absolute position of the construction personnel by solving the hyperbolic equation system.

3. The continuous positioning system for tunnel construction personnel based on multi-source data fusion as described in claim 1, characterized in that, The main control module communicates and coordinates with the GNSS positioning module, UWB module, and IMU module through interfaces, which are SPI, UART, or IIC.

4. The continuous positioning system for tunnel construction personnel based on multi-source data fusion as described in claim 1, characterized in that, The anchor nodes are deployed in underground tunnels, chambers, and surface areas.

5. The continuous positioning system for tunnel construction personnel based on multi-source data fusion as described in claim 1, characterized in that, The motion data collected by the IMU module includes gait detection, stride length estimation, and heading estimation data.

6. The continuous positioning system for tunnel construction personnel based on multi-source data fusion as described in claim 1 or 5, characterized in that, The IMU module includes a three-axis accelerometer, a three-axis gyroscope, and a three-axis magnetometer.

7. The continuous positioning system for tunnel construction personnel based on multi-source data fusion as described in claim 1, characterized in that, The positioning tag also includes a power management unit and a sound alarm module. The power management unit is used to provide power management for each module in the positioning tag, and the sound alarm module is used to emit a sound alarm signal under specific circumstances.

8. The continuous positioning system for tunnel construction personnel based on multi-source data fusion as described in claim 1, characterized in that, The system also includes a data communication module for transmitting the acquired location information of construction workers to the server.

9. The continuous positioning system for tunnel construction personnel based on multi-source data fusion as described in claim 1, characterized in that, The anchor node is equipped with an IP65 waterproof and explosion-proof shell.

10. An application of a continuous positioning system for tunnel construction personnel based on multi-source data fusion, characterized in that, It is used in mining and underground engineering or tunnel and subway construction.

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