An indoor and outdoor personnel positioning management method and device based on UWB and RTK

Abstract

The application provides an indoor and outdoor personnel positioning management method and system based on UWB and RTK, which comprises collecting UWB observation data and RTK observation data on the terminal side respectively; performing space-time alignment preprocessing and outlier screening on the UWB observation data and the RTK observation data to obtain an effective observation data set; dynamically configuring the solving confidence weight of the UWB observation data and the RTK observation data according to the space scene type where the terminal is currently located; based on the Kalman filtering framework, combining the effective observation data set and the corresponding confidence weight, performing double-observation-source fusion solving to output a fusion positioning result; and matching the preset scene switching judgment rule according to the historical positioning state and the current observation data characteristics to perform adaptive seamless switching of the UWB positioning mode and the RTK positioning mode. Through the double-mode data fusion solving and the intelligent seamless switching logic, the application solves the problem of unstable indoor and outdoor positioning switching and realizes continuous high-precision personnel positioning management and control in indoor and outdoor scenes.

Description

Technical Field

[0001] This invention relates to the field of personnel positioning and control technology, specifically to an indoor and outdoor personnel positioning management method and device based on UWB and RTK. Background Technology

[0002] With the advancement of intelligent transformation in industrial plants, precise personnel positioning and dynamic safety management have become core requirements for safe production control. Existing personnel positioning technologies include various methods such as Wi-Fi, RFID, Bluetooth, ZigBee, UWB, and satellite RTK differential positioning. While UWB positioning can achieve centimeter-level accuracy, it is only suitable for indoor and equipment areas, with insufficient coverage in outdoor environments. BeiDou RTK differential positioning can achieve meter-level outdoor positioning, but indoor signal obstruction leads to a significant drop in accuracy. Current conventional solutions often use a simple superposition of two positioning technologies, with each operating independently and calculating separately. This results in positioning gaps and coordinate jumps in indoor-outdoor transition areas, failing to achieve a smooth, seamless positioning experience. Furthermore, it is difficult to balance global coordinate consistency with local high-precision requirements, thus failing to fully meet the continuous and precise personnel positioning control requirements of industrial plants. In addition, existing solutions lack differentiated switching mechanisms for different floor levels within the plant, leading to positioning drift and incorrect switching during scene transitions, making them unsuitable for complex plant building structures and operating environments. Summary of the Invention

[0003] The purpose of this invention is to overcome the shortcomings of the prior art. The embodiments of this invention provide an indoor and outdoor personnel positioning management method and device based on UWB and RTK, which is applicable to personnel positioning management in industrial plants such as gas turbine power plants where there are mixed indoor and outdoor operation scenarios. By using dual-mode data fusion calculation and intelligent seamless switching logic, the problem of unstable indoor and outdoor positioning switching is solved, and continuous high-precision personnel positioning control is achieved in indoor and outdoor scenarios.

[0004] To solve the above-mentioned technical problems, the present invention provides the following technical solution: In a first aspect, the present invention provides an indoor and outdoor personnel positioning management method based on UWB and RTK, comprising the following steps: UWB observation data and RTK observation data were collected from the terminal side respectively; Spatiotemporal alignment preprocessing and outlier filtering were performed on UWB and RTK observation data to obtain a valid observation dataset. Based on the current spatial scene type of the terminal, dynamically configure the calculation confidence weights of UWB observation data and RTK observation data; Based on the Kalman filter framework, the effective observation dataset and corresponding confidence weights are combined to perform dual observation source fusion calculation and output the fusion localization result; Based on historical positioning status and current observation data characteristics, a preset scene switching judgment rule is matched to perform adaptive and seamless switching between UWB positioning mode and RTK positioning mode.

[0005] In one embodiment, the step of dynamically configuring the solution confidence weights of UWB observation data and RTK observation data according to the current spatial scene type of the terminal includes: Three types of spatial scenes are preset: indoor scenes, outdoor scenes, and transition areas; When the scene is determined to be indoors, UWB observation data is configured with high confidence weight, and RTK observation data is configured with low auxiliary weight. When the scene is determined to be outdoor, RTK observation data is configured as high confidence weight and UWB observation data is configured as constraint auxiliary weight. When a transition region is identified, the covariance parameters of the UWB and RTK observation data are dynamically adjusted based on the number of UWB beacon scans, signal strength, number of RTK satellite searches, and horizontal precision factor to achieve continuous and smooth changes in weights.

[0006] In one embodiment, when the scene is determined to be outdoor, configuring RTK observation data as high-confidence weights and UWB observation data as constraint auxiliary weights includes: Construct a state vector containing position and velocity parameters; The standard deviations of RTK positioning noise and UWB ranging noise are set separately to form the corresponding observation covariance matrix; Increase the confidence weight of RTK observations in open outdoor environments; When the number of satellites acquired by RTK decreases and a detectable UWB beacon exists, the calculation weight of UWB observations is automatically increased to correct RTK positioning drift using UWB ranging constraints.

[0007] In one embodiment, the dual-source fusion solution based on the Kalman filter framework, combined with the effective observation dataset and corresponding confidence weights, outputs the fusion localization result, including: Based on the optimal positioning state and motion model of the previous moment, calculate the prior state and prior covariance matrix of the current moment. The observation residuals are calculated using RTK observation data, and the Kalman gain corresponding to RTK is calculated by combining the RTK observation covariance. The first correction is then performed on the prior state. The observation residuals are calculated using UWB observation data, and the Kalman gain corresponding to UWB is calculated in combination with the dynamically configured UWB observation covariance. A second correction is then performed on the state after the first correction. The state after two corrections is output as the final fused positioning result, which includes the optimal estimated position and velocity information.

[0008] In one embodiment, the step of matching a preset scene switching determination rule with historical positioning status and current observation data characteristics to perform adaptive seamless switching between UWB positioning mode and RTK positioning mode includes: The floor scene corresponding to the previous location result is obtained, which is divided into the first floor location scene and the second floor and above floor location scene. For the first-level positioning scenario, the UWB beacon scanning conditions are determined first. If the threshold is met, the system switches to UWB positioning mode. If the threshold is not met, the system determines whether to enable RTK positioning mode based on the number of satellites searched and the number of consecutive observations. For positioning scenarios on the second floor and above, UWB positioning mode is maintained first. When the number of UWB beacons is insufficient, the system determines whether to switch to RTK positioning mode based on the number of satellite searches, the number of consecutive observations, and the positioning distance deviation threshold.

[0009] In one embodiment, the system further includes steps for detecting and classifying crowd gatherings, specifically including: Based on the fusion positioning results, the Haversine formula is used to calculate the ground distance between people, and a spatial clustering algorithm is used to identify clustered nodes. When the number of people in a cluster node reaches a preset tiered threshold, a warning message of the corresponding level is triggered. Perform hierarchical merging processing on spatially overlapping cluster nodes to generate merged cluster regions and geometric centers.

[0010] In one embodiment, a tiered electronic fence control step is also included, specifically comprising: Draw various types of electronic fences on electronic maps and configure control rules; Based on the personnel's identity category, the corresponding area access permissions are matched, and an intrusion alarm is triggered when unauthorized personnel enter the fenced area. Implement fence configuration and hierarchical isolation of data based on administrator permission levels.

[0011] Secondly, the present invention provides an indoor and outdoor personnel positioning and management system based on UWB and RTK, the device comprising: The data acquisition module is used to collect UWB observation data and RTK observation data from the terminal side, respectively. The preprocessing module is used to perform spatiotemporal alignment preprocessing and outlier filtering on UWB and RTK observation data to obtain a valid observation dataset. The weight configuration module is used to dynamically configure the calculation confidence weights of UWB observation data and RTK observation data according to the spatial scene type currently in which the terminal is located; The fusion solution module is used to perform dual-source fusion solution based on the Kalman filter framework, combining the effective observation dataset and corresponding confidence weights, and output the fusion localization result; The mode switching module is used to match preset scene switching judgment rules based on historical positioning status and current observation data characteristics, and to perform adaptive and seamless switching between UWB positioning mode and RTK positioning mode.

[0012] In one embodiment, the weight configuration module is specifically used for: Three types of spatial scenes are preset: indoor scenes, outdoor scenes, and transition areas. When a scene is determined to be indoor, UWB observation data is configured with high confidence weight, and RTK observation data is configured with low auxiliary weight. When the scene is determined to be outdoor, RTK observation data is configured as high confidence weight and UWB observation data is configured as constraint auxiliary weight. When a transition region is identified, the covariance parameters of the UWB and RTK observation data are dynamically adjusted based on the number of UWB beacon scans, signal strength, number of RTK satellite searches, and horizontal precision factor to achieve continuous and smooth changes in weights.

[0013] In one embodiment, when configuring outdoor scene weights, the weight configuration module is specifically used for: Construct a state vector containing position and velocity parameters; The standard deviations of RTK positioning noise and UWB ranging noise are set separately to form the corresponding observation covariance matrix; In open outdoor environments, increase the confidence weight of RTK observations; when the number of RTK satellites decreases and there are detectable UWB beacons, automatically increase the calculation weight of UWB observations to correct RTK positioning drift using UWB ranging constraints.

[0014] In one embodiment, the fusion solution module is specifically used for: Based on the optimal positioning state and motion model of the previous moment, calculate the prior state and prior covariance matrix of the current moment. The observation residuals are calculated using RTK observation data, and the Kalman gain corresponding to RTK is calculated by combining the RTK observation covariance. The first correction is then performed on the prior state. The observation residuals are calculated using UWB observation data, and the Kalman gain corresponding to UWB is calculated in combination with the dynamically configured UWB observation covariance. A second correction is then performed on the state after the first correction. The state after two corrections is output as the final fused positioning result, which includes the optimal estimated position and velocity information.

[0015] In one embodiment, the mode switching module is specifically used for: The floor scene corresponding to the previous location result is obtained, which is divided into the first floor location scene and the second floor and above floor location scene. For the first-level positioning scenario, the UWB beacon scanning conditions are determined first. If the threshold is met, the system switches to UWB positioning mode. If the threshold is not met, the system determines whether to enable RTK positioning mode based on the number of satellites searched and the number of consecutive observations. For positioning scenarios on the second floor and above, UWB positioning mode is maintained first. When the number of UWB beacons is insufficient, the system determines whether to switch to RTK positioning mode based on the number of satellite searches, the number of consecutive observations, and the positioning distance deviation threshold.

[0016] In one embodiment, it further includes an aggregation detection and early warning module, used for: Based on the fusion positioning results, the Haversine formula is used to calculate the ground distance between people, and a spatial clustering algorithm is used to identify clustered nodes. When the number of people in a cluster node reaches a preset tiered threshold, a warning message of the corresponding level is triggered. Perform hierarchical merging processing on spatially overlapping cluster nodes to generate merged cluster regions and geometric centers.

[0017] In one embodiment, an electronic fence control module is also included, used for: Draw various types of electronic fences on electronic maps and configure control rules; Based on the personnel's identity category, the corresponding area access permissions are matched, and an intrusion alarm is triggered when unauthorized personnel enter the fenced area. Implement fence configuration and hierarchical isolation of data based on administrator permission levels.

[0018] Thirdly, the present invention provides an electronic device, comprising: a processor and a memory; The memory is used to store computer programs; The processor is configured to execute, by invoking the computer program, an indoor / outdoor personnel positioning management method based on UWB and RTK provided in any of the first aspects.

[0019] Fourthly, the present invention provides a computer-readable storage medium comprising a program, which, when executed by a processor, is used to implement an indoor and outdoor personnel positioning management method based on UWB and RTK provided in any of the first aspects.

[0020] The beneficial effects of this invention are as follows: By using a dual-mode data fusion solution algorithm, the UWB ranging characteristics and the advantages of RTK global coordinates are deeply combined, rather than simply superimposed with other technologies. This effectively suppresses the positioning drift and error of a single technology, improves the positioning accuracy across all scenarios, and achieves smooth and imperceptible switching between indoor and outdoor scenarios through intelligent seamless switching logic based on floor scenarios. This solves the positioning gap and jump problems of traditional solutions, adapts to the complex indoor and outdoor mixed scenarios in industrial plants, and can simultaneously meet the needs of high-precision positioning in the plant area and continuous positioning over a large area outdoors, providing stable and reliable location data support for the safety management of personnel in the plant area. Attached Figure Description

[0021] Figure 1 The diagram shown is a flowchart of an indoor and outdoor personnel positioning and management method based on UWB and RTK according to an embodiment of the present invention. Figure 2 The diagram shown is a structural schematic of an indoor and outdoor personnel positioning management system based on UWB and RTK according to an embodiment of the present invention. Figure 3 The diagram shown is a structural schematic of an electronic device according to an embodiment of the present invention. Detailed Implementation

[0022] To make the objectives, technical solutions, and advantages of this invention clearer and more understandable, the invention will be further described below in conjunction with the accompanying drawings and specific embodiments. Obviously, the described embodiments are merely some embodiments of this invention, and not all embodiments. Based on the embodiments of this invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this invention.

[0023] To address the shortcomings of existing technologies, this invention provides a specific implementation method for indoor and outdoor personnel positioning and management based on UWB and RTK, such as... Figure 1 As shown, the method includes the following steps: S110: Collects UWB observation data and RTK observation data from the terminal side respectively.

[0024] The terminal is a positioning badge worn by personnel. The badge is equipped with both a UWB positioning module and an RTK positioning module, which can generate UWB observation data and RTK observation data. The UWB observation data comes from UWB beacons deployed indoors and in the equipment area, while the RTK observation data comes from outdoor RTK base stations and satellite signals set up in the plant area.

[0025] S120: Perform spatiotemporal alignment preprocessing and outlier filtering on UWB and RTK observation data to obtain a valid observation dataset.

[0026] Specifically, the following steps are performed when obtaining a valid observation dataset: The latitude and longitude coordinates of RTK observation data are converted into coordinates in a unified plane coordinate system, and the UWB ranging data are solved into plane coordinates in the same coordinate system through trilateration.

[0027] The sampling timestamps of UWB and RTK observation data are aligned using time interpolation to achieve spatiotemporal unification.

[0028] The residual analysis method based on the chi-square test eliminates UWB non-line-of-sight abnormal ranging points (caused by metal obstruction or signal reflection) and RTK multipath interference data points, retaining the effective observation data to form an effective observation dataset.

[0029] S130: Dynamically configure the calculation confidence weights of UWB observation data and RTK observation data according to the current spatial scene type of the terminal.

[0030] Three types of spatial scenes are preset: indoor scenes, outdoor scenes, and transition areas.

[0031] When the scene is determined to be indoors, UWB observation data is configured with high confidence weight, and RTK observation data is configured with low auxiliary weight, with UWB positioning as the primary method to ensure high-precision indoor positioning.

[0032] When the scene is determined to be outdoor, RTK observation data is configured with high confidence weights, while UWB observation data is configured with constraint auxiliary weights. Specifically, a state vector containing position and velocity parameters is constructed, and the standard deviations of RTK positioning noise and UWB ranging noise are set respectively to form corresponding observation covariance matrices. In open outdoor environments, the confidence weight of RTK observations is increased. When the number of RTK satellites acquired decreases and a detectable UWB beacon is available, the calculation weight of UWB observations is automatically increased to correct RTK positioning drift using UWB ranging constraints.

[0033] When a transition region is identified, the covariance parameters of the UWB and RTK observation data are dynamically adjusted based on the number of UWB beacon scans, signal strength, number of RTK satellite searches, and horizontal precision factor to achieve continuous and smooth changes in weights.

[0034] S140: Based on the Kalman filter framework, combining the effective observation dataset with the corresponding confidence weights, perform dual observation source fusion calculation and output fusion localization results.

[0035] Specifically, the following steps are performed when obtaining the fused localization results: Based on the optimal positioning state and motion model of the previous moment, the prior state and prior covariance matrix of the current moment are calculated.

[0036] The observation residuals are calculated using RTK observation data, and the Kalman gain corresponding to RTK is calculated by combining the RTK observation covariance. The first correction is then performed on the prior state.

[0037] The observation residuals are calculated using UWB observation data, and the Kalman gain corresponding to UWB is calculated in combination with the dynamically configured UWB observation covariance. A second correction is then performed on the state after the first correction.

[0038] The state after two corrections is output as the final fused localization result, which includes the optimal estimated position and velocity information.

[0039] The fusion formula is: ; In the formula, These are the predicted values ​​of the prior state. The Kalman gain corresponding to RTK observations. For RTK observation residuals, The Kalman gain corresponding to UWB observations. For UWB observation residuals, This is the final fusion positioning result.

[0040] S150: Based on historical positioning status and current observation data characteristics, match the preset scene switching judgment rules and perform adaptive seamless switching between UWB positioning mode and RTK positioning mode.

[0041] The floor scene corresponding to the previous location result is obtained, which is divided into the first floor location scene and the second floor and above floor location scene.

[0042] For first-floor positioning scenarios, the system prioritizes determining UWB beacon scanning conditions; if a threshold is met, it switches to UWB positioning mode. For example, if four UWB beacons are detected, and three of them are on the same floor (2nd floor or above), the system switches to UWB positioning mode.

[0043] If the conditions are not met, the decision to enable RTK positioning mode will be made based on the number of satellites searched and the number of consecutive observations. For example, if the conditions for switching to UWB positioning mode are not met but the number of satellites searched is greater than 22, satellite positioning will be used; or if the conditions for switching to UWB positioning mode are still not met, but the number of satellites searched is greater than 10 and satellites are detected at least 3 times consecutively, satellite positioning will also be used.

[0044] For positioning scenarios on the second floor and above, UWB positioning mode is maintained first. When the number of UWB beacons is insufficient, the decision to switch to RTK positioning mode is made based on the number of satellites searched, the number of consecutive observations, and the positioning distance deviation threshold. For example, for positioning scenarios on the second floor and above, UWB positioning mode is maintained first. When at least 4 UWB beacons are scanned, UWB positioning is maintained. If this condition is not met, but the number of satellites searched is greater than 30 and at least 3 consecutive satellite searches are completed, satellite positioning is switched to. If the distance between the current satellite positioning and the previous positioning is greater than twice the positioning switching distance threshold, satellite positioning is also switched to.

[0045] As can be seen from the above steps, the embodiments of the present invention do not simply superimpose UWB and RTK positioning technologies independently, but achieve deep fusion of UWB observation data and RTK observation data through a unified fusion solution framework. At the same time, differentiated scene switching logic is designed for the floor structure of the factory area, which not only ensures the positioning accuracy of 0.5-0.8 meters in the indoor device area and 1-3 meters in the outdoor area, but also solves the positioning discontinuity and coordinate jump problem in the indoor-outdoor transition area, realizing seamless positioning in all scenarios. The positioning continuity and stability are significantly improved, and it can better adapt to the complex working environment of industrial plants.

[0046] Based on the method in the above embodiments, the method of this embodiment further includes S160: a personnel gathering detection and graded early warning step, specifically including: Based on the fusion positioning results, the Haversine formula is used to calculate the ground distance between people, and a spatial clustering algorithm is used to identify clustered nodes. When the number of people in a cluster node reaches a preset tiered threshold, a warning message of the corresponding level is triggered. Perform hierarchical merging processing on spatially overlapping cluster nodes to generate merged cluster regions and geometric centers.

[0047] In this embodiment, based on the personnel coordinate data obtained from fusion positioning, the Haversine formula is used to calculate the ground distance between any two personnel. Each person is considered a potential gathering center, and the number of personnel within a specified radius (15 meters) is counted. When the number exceeds a preset threshold (3 people), it is marked as a gathering node. The calculation results are refreshed every 30 seconds. Then, hierarchical merging processing is performed on spatially overlapping gathering nodes. The distance between the center points of two gathering nodes is calculated. When the distance is less than 0.7 times the sum of the radii of the two nodes, it is determined to be overlapping. Nodes with more personnel are retained first. If the number is the same, nodes closer to the center of the factory area are retained. After merging, a new gathering area and geometric center are generated. The personnel list is deduplicated and merged. At the same time, special processing of complete inclusion and chain overlap is supported. Finally, a graded warning is executed according to the number of people gathered: 3 people trigger a yellow warning, 4-6 people trigger an orange warning, and 7 or more people trigger a red warning. The warning is automatically upgraded or downgraded when the number of people changes. The warning is automatically lifted after the personnel disperse. At the same time, a silent area can be configured, such as the central control room and conference room. In the silent area, no gathering alarm is triggered, but the number of people is still counted. The silent function can be dynamically turned on or off according to time period.

[0048] This embodiment uses spatial clustering and hierarchical merging algorithms to identify and manage personnel gatherings, effectively avoiding repeated alarms in overlapping areas, improving the accuracy of early warnings, and adapting to the differentiated management needs of different areas in the factory.

[0049] Based on the method in the above embodiments, the method of this embodiment further includes S170: a hierarchical electronic fence control step, specifically including: Draw various types of electronic fences on electronic maps and configure control rules; Based on the personnel's identity category, the corresponding area access permissions are matched, and an intrusion alarm is triggered when unauthorized personnel enter the fenced area. Implement fence configuration and hierarchical isolation of data based on administrator permission levels.

[0050] In this embodiment, polygonal electronic fences can be drawn on an electronic map through a configuration interface. Fence names and types can be set, including hazardous areas, restricted areas, and loitering areas. Corresponding control rules can be configured for different fence types. Restricted areas can have their effective period and time set; entering these areas triggers an alarm if non-whitelisted personnel enter. Areas with limited personnel can have upper and lower limits on the number of personnel; exceeding these limits triggers an alarm. Loitering areas can have a maximum allowed loitering time set; exceeding this time triggers an alarm. A hierarchical authorization mechanism is also configured: super administrators can configure fences for the entire plant, while department administrators can only configure fences within their designated areas. Permissions can be refined to the device level, automatically filtering data from unauthorized areas based on account permissions to achieve data isolation.

[0051] This embodiment implements a hierarchical design for fence configuration, access control, and data isolation, which not only meets the needs of unified management across the entire plant, but also ensures the management flexibility and data security of each local department, and is adapted to the organizational structure characteristics of hierarchical management in industrial plants.

[0052] Based on the methods in the above embodiments, the method of this invention further includes alarm linkage and emergency assistance steps, specifically including: When an alarm event is detected, the video surveillance equipment in the corresponding area is automatically activated to retrieve the monitoring footage of the time period before and after the alarm point. In emergency scenarios, it supports personnel trajectory playback, SOS location highlighting, and evacuation route density monitoring to assist in rescue command and dispatch.

[0053] More specifically, the method in this example supports multiple alarm types, including SOS calls, intrusion into dangerous areas, stationary alarms, low battery alarms, overcrowding / undercrowding, stranded individuals, and crowd gatherings. When an alarm occurs, an audio-visual alert pops up and an alarm log is generated. Alarms in public areas are pushed to the gate monitoring room, and alarms in equipment areas are pushed to the local central control room. SOS alarms require intervention within 1 minute, and other alarms within 5 minutes. After handling, a processing opinion is filled out to complete the loop. Alarms not handled within the time limit are automatically escalated and pushed to higher-level management. When an alarm is triggered, the corresponding area's video surveillance is automatically activated. Monitoring footage of the minute before and after the alarm point can be directly retrieved, or real-time video can be retrieved via camera icons on the map. In emergency scenarios, the trajectory playback function can be used to view historical personnel movement routes. When an SOS is triggered, the location is automatically highlighted, and the density of people in evacuation routes and assembly points is monitored in real time to assist in command and dispatch of evacuation.

[0054] Compared with existing single location alarm solutions, this embodiment realizes alarm hierarchical handling, automatic video linkage and full-process emergency assistance, which greatly improves the efficiency of factory safety emergency response and the accuracy of rescue command.

[0055] Based on the same inventive concept, this application also provides an indoor and outdoor personnel positioning and management device based on UWB and RTK, which can be used to implement the indoor and outdoor personnel positioning and management method based on UWB and RTK described in the above embodiments, as shown in the following embodiments. Since the principle and method of solving the problem are similar, the implementation of the device can refer to the method implementation, and repeated details will not be elaborated further. The terms "unit" or "module" used below can refer to a combination of software and / or hardware that implements a predetermined function. Although the system described in the following embodiments is preferably implemented in software, hardware implementation or a combination of software and hardware is also possible and contemplated.

[0056] This invention provides an indoor and outdoor personnel positioning and management system based on UWB and RTK, such as... Figure 2 As shown. In Figure 2 The device includes: Data acquisition module 210 is used to acquire UWB observation data and RTK observation data from the terminal side respectively; Preprocessing module 220 is used to perform spatiotemporal alignment preprocessing and outlier filtering on UWB observation data and RTK observation data to obtain effective observation datasets; The weight configuration module 230 is used to dynamically configure the calculation confidence weights of UWB observation data and RTK observation data according to the spatial scene type where the terminal is currently located. The fusion solution module 240 is used to perform dual-source fusion solution based on the Kalman filter framework, combining the effective observation dataset and corresponding confidence weights, and output the fusion localization result; The mode switching module 250 is used to match the preset scene switching judgment rules based on the historical positioning status and the characteristics of the current observation data, and to perform adaptive and seamless switching between UWB positioning mode and RTK positioning mode.

[0057] In one embodiment, the weight configuration module 230 is specifically used for: Three types of spatial scenes are preset: indoor scenes, outdoor scenes, and transition areas. When a scene is determined to be indoor, UWB observation data is configured with high confidence weight, and RTK observation data is configured with low auxiliary weight. When the scene is determined to be outdoor, RTK observation data is configured as high confidence weight and UWB observation data is configured as constraint auxiliary weight. When a transition region is identified, the covariance parameters of the UWB and RTK observation data are dynamically adjusted based on the number of UWB beacon scans, signal strength, number of RTK satellite searches, and horizontal precision factor to achieve continuous and smooth changes in weights.

[0058] In one embodiment, when configuring outdoor scene weights, the weight configuration module 230 is specifically used for: Construct a state vector containing position and velocity parameters; The standard deviations of RTK positioning noise and UWB ranging noise are set separately to form the corresponding observation covariance matrix; In open outdoor environments, increase the confidence weight of RTK observations; when the number of RTK satellites decreases and there are detectable UWB beacons, automatically increase the calculation weight of UWB observations to correct RTK positioning drift using UWB ranging constraints.

[0059] In one embodiment, the fusion solution module 240 is specifically used for: Based on the optimal positioning state and motion model of the previous moment, calculate the prior state and prior covariance matrix of the current moment. The observation residuals are calculated using RTK observation data, and the Kalman gain corresponding to RTK is calculated by combining the RTK observation covariance. The first correction is then performed on the prior state. The observation residuals are calculated using UWB observation data, and the Kalman gain corresponding to UWB is calculated in combination with the dynamically configured UWB observation covariance. A second correction is then performed on the state after the first correction. The state after two corrections is output as the final fused localization result, which includes the optimal estimated position and velocity information.

[0060] In one embodiment, the mode switching module 250 is specifically used for: The floor scene corresponding to the previous location result is obtained, which is divided into the first floor location scene and the second floor and above floor location scene. For the first-level positioning scenario, the UWB beacon scanning conditions are determined first. If the threshold is met, the system switches to UWB positioning mode. If the threshold is not met, the system determines whether to enable RTK positioning mode based on the number of satellites searched and the number of consecutive observations. For positioning scenarios on the second floor and above, UWB positioning mode is maintained first. When the number of UWB beacons is insufficient, the system determines whether to switch to RTK positioning mode based on the number of satellite searches, the number of consecutive observations, and the positioning distance deviation threshold.

[0061] In one embodiment, it further includes an aggregation detection and early warning module 260, used for: Based on the fusion positioning results, the Haversine formula is used to calculate the ground distance between people, and a spatial clustering algorithm is used to identify clustered nodes. When the number of people in a cluster node reaches a preset tiered threshold, a warning message of the corresponding level is triggered. Perform hierarchical merging processing on spatially overlapping cluster nodes to generate merged cluster regions and geometric centers.

[0062] In one embodiment, an electronic fence control module 270 is also included, for: It supports drawing various types of electronic fences on electronic maps and configuring control rules; Based on the personnel's identity category, the corresponding area access permissions are matched, and an intrusion alarm is triggered when unauthorized personnel enter the fenced area. It supports hierarchical isolation of fence configuration and data based on administrator privilege levels.

[0063] This application also provides a specific implementation of an electronic device capable of implementing all the steps of the methods described above. See [link to implementation details]. Figure 3 The electronic device 300 specifically includes the following: Processor 310, memory 320, communication unit 330 and bus 340; The processor 310, memory 320, and communication unit 330 communicate with each other via bus 340; the communication unit 330 is used to realize information transmission between server-side devices and terminal devices and other related devices.

[0064] The processor 310 is used to call the computer program in the memory 320. When the processor executes the computer program, it implements all the steps in the method in the above embodiments.

[0065] Those skilled in the art will understand that memory can be, but is not limited to, Random Access Memory (RAM), Read-Only Memory (ROM), Programmable Read-Only Memory (PROM), Erasable Programmable Read-Only Memory (EPROM), and Electrically Erasable Programmable Read-Only Memory (EEPROM). The memory stores programs, which are then executed by the processor upon receiving execution instructions. Furthermore, the software programs and modules within the memory may include an operating system, which may include various software components and / or drivers for managing system tasks (e.g., memory management, storage device control, power management), and can communicate with various hardware or software components to provide an operating environment for other software components.

[0066] A processor can be an integrated circuit chip with signal processing capabilities. The aforementioned processor can be a general-purpose processor, including a Central Processing Unit (CPU), a Network Processor (NP), etc. It can implement or execute the methods, steps, and logic block diagrams disclosed in the embodiments of this application. The general-purpose processor can be a microprocessor or any conventional processor.

[0067] This application also provides a computer-readable storage medium including a program that, when executed by a processor, performs the method provided in any of the foregoing method embodiments.

[0068] Those skilled in the art will understand that all or part of the steps in the above-described method embodiments can be implemented by hardware related to program instructions. The aforementioned program can be stored in a computer-readable storage medium. When executed, the program performs the steps of the above-described method embodiments; and the aforementioned storage medium includes various media capable of storing program code, such as ROM, RAM, magnetic disks, or optical disks, and this application does not limit the specific type of media.

[0069] The above description is merely a preferred embodiment of the present invention and is not intended to limit the present invention in any way. Although the present invention has been disclosed above with reference to preferred embodiments, it is not intended to limit the present invention. Any person skilled in the art can make some modifications or alterations to the above-disclosed technical content to create equivalent embodiments without departing from the scope of the present invention. Any simple modifications, equivalent changes and alterations made to the above embodiments based on the technical essence of the present invention without departing from the scope of the present invention shall still fall within the scope of the present invention.

Claims

1. A method for indoor and outdoor personnel positioning and management based on UWB and RTK, characterized in that, Includes the following steps: UWB observation data and RTK observation data were collected from the terminal side respectively; Spatiotemporal alignment preprocessing and outlier filtering were performed on UWB and RTK observation data to obtain a valid observation dataset. Based on the current spatial scene type of the terminal, dynamically configure the calculation confidence weights of UWB observation data and RTK observation data; Based on the Kalman filter framework, the effective observation dataset and corresponding confidence weights are combined to perform dual observation source fusion calculation and output the fusion localization result; Based on historical positioning status and current observation data characteristics, a preset scene switching judgment rule is matched to perform adaptive and seamless switching between UWB positioning mode and RTK positioning mode.

2. The indoor and outdoor personnel positioning management method based on UWB and RTK as described in claim 1, characterized in that, The step of dynamically configuring the confidence weights for solving UWB observation data and RTK observation data based on the current spatial scene type of the terminal includes: Three types of spatial scenes are preset: indoor scenes, outdoor scenes, and transition areas; When the scene is determined to be indoors, UWB observation data is configured with high confidence weight, and RTK observation data is configured with low auxiliary weight. When the scene is determined to be outdoor, RTK observation data is configured as high confidence weight and UWB observation data is configured as constraint auxiliary weight. When a transition region is identified, the covariance parameters of the UWB and RTK observation data are dynamically adjusted based on the number of UWB beacon scans, signal strength, number of RTK satellite searches, and horizontal precision factor to achieve continuous and smooth changes in weights.

3. The indoor and outdoor personnel positioning management method based on UWB and RTK as described in claim 2, characterized in that, When the scene is determined to be outdoor, configuring RTK observation data as high-confidence weight and UWB observation data as constraint auxiliary weight includes: Construct a state vector containing position and velocity parameters; The standard deviations of RTK positioning noise and UWB ranging noise are set separately to form the corresponding observation covariance matrix; Increase the confidence weight of RTK observations in open outdoor environments; When the number of satellites acquired by RTK decreases and a detectable UWB beacon exists, the calculation weight of UWB observations is automatically increased to correct RTK positioning drift using UWB ranging constraints.

4. The indoor and outdoor personnel positioning management method based on UWB and RTK as described in claim 1, characterized in that, The Kalman filter-based framework, combined with the effective observation dataset and corresponding confidence weights, performs dual-source fusion calculation, and outputs the fusion localization results, including: Based on the optimal positioning state and motion model of the previous moment, calculate the prior state and prior covariance matrix of the current moment. The observation residuals are calculated using RTK observation data, and the Kalman gain corresponding to RTK is calculated by combining the RTK observation covariance. The first correction is then performed on the prior state. The observation residuals are calculated using UWB observation data, and the Kalman gain corresponding to UWB is calculated in combination with the dynamically configured UWB observation covariance. A second correction is then performed on the state after the first correction. The state after two corrections is output as the final fused positioning result, which includes the optimal estimated position and velocity information.

5. The indoor and outdoor personnel positioning management method based on UWB and RTK as described in claim 1, characterized in that, The step of matching preset scene switching rules based on historical positioning status and current observation data characteristics to perform adaptive seamless switching between UWB positioning mode and RTK positioning mode includes: The floor scene corresponding to the previous location result is obtained, which is divided into the first floor location scene and the second floor and above floor location scene. For the first-level positioning scenario, the UWB beacon scanning conditions are determined first. If the threshold is met, the system switches to UWB positioning mode. If the threshold is not met, the system determines whether to enable RTK positioning mode based on the number of satellites searched and the number of consecutive observations. For positioning scenarios on the second floor and above, UWB positioning mode is maintained first. When the number of UWB beacons is insufficient, the system determines whether to switch to RTK positioning mode based on the number of satellite searches, the number of consecutive observations, and the positioning distance deviation threshold.

6. The indoor and outdoor personnel positioning management method based on UWB and RTK as described in claim 1, characterized in that, It also includes measures for detecting and tiered early warning of gatherings of people, specifically including: Based on the fusion positioning results, the Haversine formula is used to calculate the ground distance between people, and a spatial clustering algorithm is used to identify clustered nodes. When the number of people in a cluster node reaches a preset tiered threshold, a warning message of the corresponding level is triggered. Perform hierarchical merging processing on spatially overlapping cluster nodes to generate merged cluster regions and geometric centers.

7. The indoor and outdoor personnel positioning management method based on UWB and RTK as described in claim 1, characterized in that, It also includes a tiered electronic fence management process, specifically including: Draw various types of electronic fences on electronic maps and configure control rules; Based on the personnel's identity category, the corresponding area access permissions are matched, and an intrusion alarm is triggered when unauthorized personnel enter the fenced area. Implement fence configuration and hierarchical isolation of data based on administrator permission levels.

8. An indoor / outdoor personnel positioning management system based on UWB and RTK, characterized in that, The system includes: The data acquisition module is used to collect UWB observation data and RTK observation data from the terminal side, respectively. The preprocessing module is used to perform spatiotemporal alignment preprocessing and outlier filtering on UWB and RTK observation data to obtain a valid observation dataset. The weight configuration module is used to dynamically configure the calculation confidence weights of UWB observation data and RTK observation data according to the spatial scene type currently in which the terminal is located; The fusion solution module is used to perform dual-source fusion solution based on the Kalman filter framework, combining the effective observation dataset and corresponding confidence weights, and output the fusion localization result; The mode switching module is used to match preset scene switching judgment rules based on historical positioning status and current observation data characteristics, and to perform adaptive and seamless switching between UWB positioning mode and RTK positioning mode.

9. An electronic device, characterized in that, include: Processor and memory; The memory is used to store computer programs; The processor is configured to execute the method as described in any one of claims 1 to 7 by invoking the computer program.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium includes a program that, when executed by a processor, is used to implement the method of any one of claims 1 to 7.

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