Combined multi-point fusion space positioning method and system based on UWB and RTK

Abstract

The invention provides a combined multipoint fusion space positioning method and system based on UWB and RTK, and relates to the technical field of space positioning, and the method comprises the steps: obtaining the first position information of a moving target based on a UWB positioning module; acquiring second position information of the moving target based on an RTK positioning module; performing position data fusion on the first position information and the second position information to obtain an initial position fusion result; positioning the position of the moving target area according to the initial position fusion result, and extracting building information of the initial position fusion result; matching a positioning mode of the positioning equipment based on the building information to obtain a positioning mode matching result; and controlling the positioning equipment to carry out real-time spatial position extraction according to a positioning mode matching result. The technical problem that indoor and outdoor continuous high-precision positioning is difficult to realize through a single precise positioning technology is solved, and high-precision positioning of seamless switching from indoor to outdoor is realized through data fusion of multiple sensors.

Description

Technical Field

[0001] This application relates to the field of spatial positioning technology, and specifically relates to a combined multi-point fusion spatial positioning method and system based on UWB and RTK. Background Art

[0002] With the rapid development of technologies such as the Internet of Things, unmanned driving, and robot navigation, spatial positioning technology is being applied more and more widely in various industries. From navigation, logistics to unmanned driving and intelligent manufacturing, precise positioning technology is everywhere. Both UWB and RTK technologies can provide centimeter-level positioning accuracy. The UWB technology uses a very wide frequency band to transmit data, and its characteristic is to send a large amount of data in an extremely short time, especially performing well in indoor environments. However, the coverage range of the UWB technology is limited, usually between dozens of meters and hundreds of meters, which limits its application in large open areas. UWB signals are easily affected by buildings, metal objects, and other radio frequency interferences, resulting in a decrease in positioning accuracy.

[0003] RTK is a technology that uses Global Navigation Satellite System (GNSS) signals for high-precision positioning. It receives signals from satellites and combines differential signals from ground base stations to eliminate most error sources, thereby achieving centimeter-level positioning accuracy and performing excellently in open areas. In urban areas with dense high-rise buildings or indoor environments, satellite signals are easily blocked, affecting the positioning effect of RTK. Due to signal reflection, the RTK system may be affected by the multipath effect, resulting in positioning errors. Therefore, it is difficult to achieve continuous and precise indoor and outdoor positioning relying solely on a single positioning technology. Summary of the Invention

[0004] This application provides a combined multi-point fusion spatial positioning method and system based on UWB and RTK, which solves the technical problem that a single precise positioning technology has limited applicable scenarios and it is difficult to achieve continuous high-precision indoor and outdoor positioning. Through the data fusion of multiple sensors, high-precision positioning with seamless switching from indoor to outdoor is achieved.

[0005] In view of the above problems, on the one hand, this application provides a combined multi-point fusion spatial positioning method based on UWB and RTK, including: obtaining the first position information of a moving target based on a UWB positioning module; obtaining the second position information of the moving target based on an RTK positioning module; performing position data fusion on the first position information and the second position information to obtain an initial position fusion result; performing position positioning of the moving target area according to the initial position fusion result, and extracting building information of the initial position fusion result; performing matching of the positioning device positioning mode based on the building information to obtain a positioning mode matching result; controlling the positioning device to perform real-time spatial position extraction according to the positioning mode matching result.

[0006] On the other hand, the present application also provides a combined multi-point fusion spatial positioning system based on UWB and RTK, including: a first position information acquisition unit for acquiring first position information of a moving target based on a UWB positioning module; a second position information acquisition unit for acquiring second position information of the moving target based on an RTK positioning module; a position data fusion unit for performing position data fusion on the first position information and the second position information to obtain an initial position fusion result; a building information extraction unit for performing regional position positioning of the moving target according to the initial position fusion result and extracting building information of the initial position fusion result; a positioning mode matching unit for matching the positioning mode of the positioning device based on the building information to obtain a positioning mode matching result; and a real-time position extraction unit for controlling the positioning device to perform real-time spatial position extraction according to the positioning mode matching result.

[0007] One or more technical solutions provided in the present application have at least the following technical effects or advantages:

[0008] Acquiring the first position information of the moving target based on the UWB positioning module ensures accurate acquisition of the position information of the moving target in an indoor or occluded environment. Acquiring the second position information of the moving target based on the RTK positioning module ensures that the position information of the moving target can reach centimeter-level accuracy in an open outdoor environment. Performing position data fusion on the first position information and the second position information to obtain an initial position fusion result, and processing the positioning data of the two technologies through algorithms to reduce errors and improve the continuity and consistency of positioning, providing a more accurate and comprehensive initial position estimate for the moving target. Performing regional position positioning of the moving target according to the initial position fusion result and extracting building information of the initial position fusion result helps to understand the environmental characteristics around the moving target. Matching the positioning mode of the positioning device based on the building information to obtain a positioning mode matching result can dynamically match the positioning mode according to the environmental characteristics, improving the flexibility and accuracy of positioning. Controlling the positioning device to perform real-time spatial position extraction according to the positioning mode matching result can dynamically adjust the positioning strategy according to the current environment to provide continuous and accurate position information.

[0009] In summary, by fusing UWB and RTK technologies, the present application can provide high-precision and high-reliability positioning results in different environments, overcome the limitations of single technologies, and further improve the accuracy and environmental adaptability of positioning by introducing building information for positioning mode matching.

[0010] The above description is only an overview of the technical solution of this application. In order to better understand the technical means of this application, it can be implemented according to the content of the specification. And in order to make the above and other purposes, features and advantages of this application more obvious and understandable, the following specifically illustrates the specific implementation manners of this application. BRIEF DESCRIPTION OF THE DRAWINGS

[0011] Figure 1 It is a schematic flowchart of a combined multi-point fusion spatial positioning method based on UWB and RTK provided by an embodiment of this application;

[0012] Figure 2 It is a schematic flowchart of obtaining the initial position fusion result in a combined multi-point fusion spatial positioning method based on UWB and RTK provided by an embodiment of this application;

[0013] Figure 3 It is a schematic flowchart of obtaining the positioning mode matching result in a combined multi-point fusion spatial positioning method based on UWB and RTK provided by an embodiment of this application;

[0014] Figure 4 It is a schematic structural diagram of a combined multi-point fusion spatial positioning system based on UWB and RTK provided by an embodiment of this application.

[0015] Description of reference numerals: The first position information acquisition unit 10, the second position information acquisition unit 20, the position data fusion unit 30, the building information extraction unit 40, the positioning mode matching unit 50, the real-time position extraction unit 60. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0016] By providing a combined multi-point fusion spatial positioning method and system based on UWB and RTK in an embodiment of this application, the technical problem that a single precise positioning technology has limited applicable scenarios and it is difficult to achieve continuous high-precision positioning indoors and outdoors is solved. Through the data fusion of multiple sensors, high-precision positioning with seamless switching from indoors to outdoors is realized.

[0017] Embodiment 1, as Figure 1 shown, an embodiment of this application provides a combined multi-point fusion spatial positioning method based on UWB and RTK, including:

[0018] Step S1: Obtain the first position information of the moving target based on the UWB positioning module.

[0019] Specifically, the UWB positioning module is a module that uses UWB technology for mobile target positioning. It contains one or more UWB transmitters and receivers, which communicate with the UWB devices on the mobile target to achieve high-precision positioning of the mobile target within a short distance. The mobile target refers to an object that moves in space, which can be a person, a vehicle, a robot, etc., and its position needs to be determined through positioning technology. The first position information refers to the position data of the mobile target obtained for the first time by the UWB positioning module, usually including coordinate information such as longitude, latitude, altitude, and a timestamp.

[0020] First, deploy several UWB base stations within the area to be located. These base stations are distributed at known positions to form a positioning network. Each base station is equipped with a UWB transmitter and a receiver, capable of transmitting and receiving ultra-wideband signals. The mobile target carries a UWB tag or sensor, which can emit UWB signals and communicate with the surrounding base stations. When the mobile target enters the coverage area of the UWB positioning network, the UWB tag it carries starts to work and emits UWB signals in a specific format. These signals are captured by nearby UWB base stations, and the time of flight of the signals is calculated through precise time measurement. Since the speed of light is known, the distance between the mobile target and each base station can be calculated through the time of flight. Then, using algorithms such as triangulation or fingerprint recognition, based on the distance information between the mobile target and at least three base stations, combined with the known positions of the base stations, the first position information of the mobile target is calculated. For example, if the distances between the mobile target and base stations A, B, and C are d1, d2, and d3 respectively, then spherical equations can be constructed in three-dimensional space, and the position of the mobile target can be determined by solving the intersections of these spheres.

[0021] Step S1 provides an initial position data point for the positioning process based on UWB technology. This data point will serve as the basis for subsequent data processing and fusion to achieve more accurate and reliable spatial positioning.

[0022] Step S2: Obtain the second position information of the mobile target based on the RTK positioning module.

[0023] Specifically, the RTK positioning module: is a module that uses RTK positioning technology for mobile target positioning. By using one or more fixed reference receivers (base stations) to correct the positioning errors of the mobile receiver (rover station), centimeter-level positioning accuracy is achieved. The second position information refers to another set of position data of the mobile target obtained by the RTK positioning module, which complements the first position information obtained by the UWB positioning module and jointly participates in the subsequent data fusion process.

[0024] First, one or more RTK base stations need to be set within or near the positioning area. These base stations can receive signals from GNSS satellites and calculate their own high-precision positions. At the same time, an RTK rover is carried on the moving target, which can also receive signals from the same set of GNSS satellites. When the moving target starts to move, the RTK rover will receive satellite signals in real time and compare them with the signals received by the base station. By calculating these differential signals, most of the errors can be eliminated, thus improving the positioning accuracy of the rover. Using the differential correction data, the rover can calculate its own second position information, which has a very high accuracy, usually at the centimeter level.

[0025] The second position information obtained based on RTK technology in step S2 is combined with the first position information obtained through the UWB positioning module in step S1, providing a basis for subsequent data fusion. By fusing position data from different technical sources, the reliability and robustness of positioning can be improved.

[0026] Step S3: Perform position data fusion on the first position information and the second position information to obtain an initial position fusion result.

[0027] Specifically, position data fusion refers to the process of integrating multi-source position information from different positioning systems, aiming to improve the accuracy, stability, and reliability of overall positioning. The initial position fusion result refers to the position information obtained after preliminary fusion processing. It is a preliminary combination of the position information obtained based on the UWB and RTK positioning modules and is the basis for subsequent further precise positioning.

[0028] First, the first position information obtained from the UWB positioning module and the second position information obtained from the RTK positioning module are input into a data fusion algorithm. This algorithm can be a simple weighted average or a more complex Kalman filter, particle filter, or other adaptive fusion algorithms. They can process data from different sources and consider the uncertainty and correlation of the data. During the fusion process, the algorithm will consider the characteristics of each positioning technology, such as the excellent performance of UWB in indoor environments and the centimeter-level accuracy of RTK in open areas. According to these characteristics and the current environmental conditions, the data fusion algorithm will synthesize the data of these two positioning technologies and perform real-time processing on these position data, continuously optimizing the position estimate through iterative updates.

[0029] In step S3, through the data fusion algorithm, combining the advantages of the UWB and RTK positioning technologies, a more accurate and reliable initial position fusion result is obtained, providing a more precise starting point for subsequent regional position positioning and positioning mode matching.

[0030] Furthermore, as Figure 2As shown, step S3 of the embodiment of the present application further includes:

[0031] Step S31: Perform a difference analysis on the first position information and the second position information to obtain a position difference parameter.

[0032] Step S32: Determine whether the position difference parameter is less than or equal to a preset difference threshold.

[0033] Step S33: If it is less than or equal to the preset difference threshold, perform a position fusion calculation on the first position information and the second position information to obtain an initial position fusion result.

[0034] Furthermore, as Figure 2 shown, step S3 of the embodiment of the present application further includes:

[0035] Step S34: If the position difference parameter is greater than the preset difference threshold, construct a position data fusion module.

[0036] Step S35: Input the first position information and the second position information into the position data fusion module for multi-point spatial position fusion to obtain an initial position fusion result.

[0037] Specifically, the position difference parameter refers to the difference value obtained by comparing the first position information and the second position information, which reflects the deviation degree between the position information obtained by the two positioning technologies and can be a distance, an angle, or other related indicators. The preset difference threshold is a pre-set value used to determine whether the position difference is within an acceptable range. If the position difference is less than or equal to this threshold, it is considered that the two position information is consistent enough to be fused; if it is greater than this threshold, additional measures need to be taken to handle the difference. The position data fusion module is a specially designed algorithm or software module for processing and fusing position data from different positioning systems.

[0038] First, perform a detailed difference analysis on the first position information provided by the UWB positioning module and the second position information provided by the RTK positioning module. Compare the direct differences between the two position coordinates, including calculating the Euclidean distance, angular deviation, or other relevant metrics between them, so as to obtain a position difference parameter. Then, preset a difference threshold according to the application scenario and accuracy requirements. Compare this position difference parameter with the preset difference threshold. If the position difference parameter is less than or equal to the preset threshold, it is considered that the results of the two positioning technologies are within an acceptable range and can be directly fused. Then, use data fusion algorithms, such as weighted average, Kalman filter, etc., to perform position fusion calculations, combine the two position data, and obtain the initial position fusion result. Exemplarily, obtain the position difference parameter by calculating the Euclidean distance and use the weighted average algorithm to perform position data fusion. Assume that the first position coordinate provided by the UWB positioning module is (20, 30, 10), the second position coordinate provided by the RTK positioning module is (20.01, 30.02, 9.99), and the preset difference threshold is 0.05 meters. First, calculate the Euclidean distance between the two sets of coordinates:

[0039] Therefore, directly perform position data fusion. Set the weight of UWB positioning to 0.3 and the weight of RTK positioning to 0.7. Then, the fused position coordinates can be calculated as:

[0040] Finally, the initial position fusion result is obtained as (20.007, 30.014, 9.997).

[0041] If the position difference parameter is greater than the preset difference threshold, it indicates that there are significant differences in the data of the two positioning technologies. At this time, construct a position data fusion module, and input the first position information and the second position information into the constructed position data fusion module for multi-point spatial position fusion. This module will comprehensively consider the data of the two positioning technologies and the differences between them, and generate the initial position fusion result through advanced data processing technologies.

[0042] Step S3, through the above process, flexibly selects different data fusion methods according to the difference degree between the first position and the second position information to obtain the initial position fusion result, which maximally eliminates the influence of positioning technology differences on the position fusion result and ensures the accuracy and reliability of the initial position fusion result.

[0043] Preferably, step S34 of the embodiment of the present application further includes:

[0044] Step S34-1: Collect sample first position information and sample second position information to obtain sample training data.

[0045] Step S34-2: Perform fusion position identification on the sample training data to obtain sample fusion position identification data.

[0046] Step S34-3: Use the sample training data and the sample fusion position identification data as training data to construct a position data fusion module.

[0047] Specifically, the sample first position information refers to a series of known position data obtained from the UWB positioning module, which are used as part of the training set to train the position data fusion module. The sample second position information refers to a series of known position data obtained from the RTK positioning module, also used as part of the training set. The sample training data refers to the combination of the above two position information, that is, the data set jointly composed of the sample first position information and the sample second position information. The fusion position identification refers to manually or automatically marking the sample training data to determine its true or ideal position state, which is used as a benchmark for training the position data fusion module. The sample fusion position identification data refers to the sample training data that has been marked, that is, each sample point has a corresponding fusion position identification.

[0048] Collect the position information obtained by the UWB positioning module and the RTK positioning module under different environments and conditions as the sample first position information and the sample second position information, and combine them to obtain the sample training data. These sample training data represent the performance of the two positioning technologies under various conditions and are the basis for constructing the position data fusion module. Then, perform the processing of fusion position identification on these sample training data. It can be through manual calibration or using the real position data obtained from a third-party high-precision positioning system as the identification. The purpose of the fusion position identification is to provide a reference standard for evaluating the training effect of the position data fusion module.

[0049] Perform data preprocessing on the sample training data and sample fusion location identification data, including data cleaning, format unification, and necessary conversions, to ensure that they can be correctly processed by machine learning algorithms. Use data management tools, such as SQL databases or NoSQL databases, to pair each pair of sample first location information and sample second location information with their corresponding sample fusion location identification data. That is, there should be a "ground truth" or ideal fusion location identification associated with the two sensor data of each sample point. Split the prepared dataset into a training set and a validation set. Usually, most of the data is used for training, and a small part is used to verify the generalization ability of the model. Use the sample training data and sample fusion location identification data as input and output, and select a suitable machine learning model to construct the location data fusion module. Machine learning models include simple linear regression, decision trees, random forests, support vector machines, or more complex neural networks, such as convolutional neural networks (CNNs) or recurrent neural networks (RNNs), etc. Depending on the selected model, use algorithms such as gradient descent, stochastic gradient descent (SGD), backpropagation, etc. to train the selected model. During the training process, the model will learn how to predict the sample fusion location identification based on the sample first location information and sample second location information. Then use the validation set to verify the trained model and evaluate its performance on unseen data to ensure that the model is not overfitting and has good generalization ability. According to the verification results, adjust the model parameters or select a different model architecture to optimize the performance of the model. Exemplarily, a recurrent neural network model can be constructed through the TensorFlow machine learning framework, and the collected sample data is used as the training set to train the machine learning model. Adjust the weights of the model through the backpropagation algorithm to minimize the prediction error. Use techniques such as cross-validation to evaluate the performance of the model.

[0050] The above steps construct a location data fusion module, which learns and adapts to the differences between the two positioning techniques through machine learning techniques, so as to more effectively fuse location data. Ensure that a relatively accurate initial location fusion result can be obtained even when there are significant differences between the two positioning techniques.

[0051] Step S4: Perform location positioning of the moving target area based on the initial location fusion result, and extract the building information of the initial location fusion result.

[0052] Specifically, the location positioning of the moving target area refers to further determining the exact location of the moving target within a specific area based on the initial location fusion result. The building information refers to the data of the buildings related to the area where the moving target is located, including information such as the shape, size, height, and use of the buildings.

[0053] Based on the initial position fusion result obtained in step S3, combined with tools such as indoor positioning technology or Geographic Information System (GIS), the position of the moving target is refined to improve the accuracy and stability of positioning. Using Geographic Information System (GIS) or high-precision map data, building information in the area where the moving target is located is extracted. For example, computer vision algorithms are used to identify and extract building features from satellite images or street view images. The building information obtained in step S4 helps to provide a more accurate positioning service and assist in the matching of subsequent positioning modes.

[0054] Step S5: Based on the building information, perform matching of the positioning mode of the positioning device to obtain a positioning mode matching result.

[0055] Specifically, the positioning mode of the positioning device refers to different positioning strategies or algorithms used by the positioning device in different environments. These modes may be adjusted according to factors such as the openness of the environment, occlusion, signal interference, etc. The positioning mode matching result refers to the result obtained after the matching process, which indicates the positioning mode most suitable for the current environment.

[0056] First, analyze the building information to judge the characteristics of the current environment, such as whether it is a dense urban area, an open area, an indoor environment, or an industrial site with a large amount of metal structures. Then, according to the results of the environmental analysis, select the positioning mode most suitable for the current conditions.

[0057] Furthermore, the positioning modes described in step S5 of the embodiment of the present application include: UWB single output mode, fusion output mode, and RTK single output mode.

[0058] Specifically, the UWB single output mode means that the positioning device only uses UWB technology for positioning and does not fuse with RTK positioning technology. The UWB technology can provide accurate distance measurement because it can accurately measure the propagation time of the signal in time with extremely short pulses or signals. This mode is suitable for scenarios that require high-precision indoor positioning, such as factory workshops, warehouse management, etc. The fusion output mode means that the positioning device uses both UWB and RTK positioning technologies for positioning and fuses the output results of these technologies to obtain a more accurate positioning result. This mode can combine the high-precision indoor positioning ability of UWB and the high-precision outdoor positioning ability of RTK, and is suitable for scenarios that require seamless indoor and outdoor positioning, such as intelligent transportation systems, unmanned driving, etc. The RTK single output mode means that the positioning device only uses RTK technology for positioning. RTK is a differential GPS technology that eliminates GPS signal errors by comparing GPS signals between a reference station and a mobile device and can achieve centimeter-level precise positioning. This mode is suitable for scenarios that require high-precision outdoor positioning, such as agricultural mapping, geological exploration, etc.

[0059] In practical applications, it is crucial to select the most suitable positioning mode according to specific environments and requirements. For example, in a large warehouse, the UWB single-output mode may be selected to locate goods and personnel; while when conducting surveying and mapping in a farmland, the RTK single-output mode may be chosen to obtain high-precision position data. The fusion output mode may be applicable to driverless vehicles, which need to maintain high-precision positioning capabilities in different environments such as urban roads and highways.

[0060] Step S5 matches the corresponding positioning mode according to the building information, which can meet the requirements of different scenarios and improve the environmental adaptability of the positioning technology.

[0061] Furthermore, as Figure 3 shown, step S5 of the embodiment of the present application further includes:

[0062] Step S51: Extract the building features included in the building information, where the building features include indoor features, outdoor features, and fusion features.

[0063] Step S52: The fusion feature is the area range where the initial position fusion result of the moving target is less than or equal to the preset distance from the building edge.

[0064] Step S53: Based on the building features, match the positioning mode of the positioning device to obtain the positioning mode matching result.

[0065] Specifically, analyze the building information and extract the key features that are helpful for positioning. The building features include indoor features, outdoor features, and fusion features. Among them, indoor features include room layout, corridor width, door position, etc., which are helpful for precise positioning in the indoor environment; outdoor features include the appearance size of the building, facade materials, surrounding roads and landscapes, etc., which are helpful for positioning in the outdoor environment; the fusion feature means that when the initial position fusion result of the moving target shows that its distance from the building edge does not exceed the preset distance, this area is regarded as the fusion feature area, which means that the positioning device may be in the transition area between indoor and outdoor, such as the entrance of the building, transition area, etc. The preset distance can be customized in advance according to the actual application scenario and positioning requirements. Extracting these building features can better understand the environment and thus provide a basis for selecting the appropriate positioning mode.

[0066] Based on the extracted building features, select the most suitable positioning mode. When the extracted building features are indoor features, it is considered that the moving target is indoors, and the UWB single output mode is selected; when the extracted building features are outdoor features, it is considered that the moving target is in an open outdoor environment, and the RTK single output mode is selected. When the extracted building features include fusion features, it is considered that the moving target is in the transition area between indoors and outdoors, and the fusion output mode is selected. For example, in a large shopping mall, customers may move between the indoor shopping area (where the UWB single output mode is applicable) and the open-air square (where the RTK single output mode is applicable), and the fusion output mode can ensure continuous and accurate positioning services in transition areas such as the mall entrance.

[0067] The above steps dynamically adjust the positioning mode by analyzing the building features, ensuring that the optimal positioning solution can be provided regardless of the environment, improving the flexibility and adaptability of the positioning system, and enabling it to work stably in complex and changing environments.

[0068] Step S6: Control the positioning device to extract the real-time spatial position according to the positioning mode matching result.

[0069] Specifically, configure the positioning device according to the positioning mode matched in step S5, including adjusting the reception sensitivity, updating the filtering algorithm, setting the signal transmission frequency, etc., so that it works according to the selected positioning mode, extracts the spatial position information of the moving target in real time, and provides high-precision and high-reliability positioning results.

[0070] Furthermore, step S6 of the embodiment of the present application further includes:

[0071] Step S61: Extract the real-time position of the moving target, update the building information of the real-time position of the moving target, and obtain the updated building information.

[0072] Step S62: Based on the updated building information, perform matching of the positioning mode of the positioning device to obtain the updated positioning mode matching result.

[0073] Step S63: Control the positioning device to collect the position of the moving target in real time based on the updated positioning mode matching result until the moving target leaves the target monitoring area.

[0074] Specifically, the real-time position of the moving target refers to the exact position of the moving target (such as a person, vehicle, robot, etc.) in space at a specific moment. The target monitoring area refers to the specific area where the moving target is monitored and positioned, which may be a floor indoors, a parking lot outdoors, or the entire campus, etc.

[0075] First, extract the real-time position of the moving target, and update the relevant data of the building based on this position information to reflect the latest environmental conditions. This is because the position change of the moving target may reveal new environmental features or change the original environmental perception. For example, if the moving target moves from one room to another, the indoor layout information needs to be updated, or if the moving target approaches a specific area of the building, the detailed features of that area need to be updated. Then, based on this updated building information, re-evaluate and select the most suitable positioning mode. This process is similar to the positioning mode matching in step S5. For example, if the updated information shows that the moving target has moved from an open area to an indoor environment with multiple reflecting surfaces, the system may switch from the RTK single output mode to the UWB single output mode to adapt to the new environment.

[0076] According to the updated positioning mode matching result, continue to control the positioning device to collect the position data of the moving target in real time until the moving target leaves the monitoring area. During this process, it is necessary to continuously monitor and respond to environmental changes, and repeat the above process to ensure that the positioning device is always operating in the optimal mode. For example, if the moving target frequently switches between indoor and outdoor environments, it is necessary to quickly switch between the UWB and RTK single output modes, and even enable the fusion output mode in some cases to ensure the continuity and accuracy of positioning.

[0077] The above steps continuously monitor environmental changes and positioning effects based on the real-time position of the moving target, so as to adjust the positioning mode in a timely manner to ensure that the positioning system can maintain high performance in various complex environments and provide continuous and accurate positioning services.

[0078] In summary, the combined multi-point fusion spatial positioning method based on UWB and RTK provided by the embodiments of the present application has the following technical effects:

[0079] The first position information of the moving target is obtained based on the UWB positioning module, ensuring accurate acquisition of the position information of the moving target in indoor or occluded environments. The second position information of the moving target is obtained based on the RTK positioning module, ensuring that the position information of the moving target can reach centimeter-level accuracy in open outdoor environments. According to the positioning differences between the two technologies, the first position information and the second position information are subjected to position data fusion through a data fusion algorithm or a position data fusion module to obtain an initial position fusion result, so as to reduce errors and improve the continuity and consistency of positioning, providing a more accurate and comprehensive initial position estimate for the moving target. Regional position positioning of the moving target is performed according to the initial position fusion result, and the building information of the initial position fusion result is extracted, which helps to understand the environmental characteristics around the moving target. Matching of the positioning mode of the positioning device is performed based on the building information to obtain a positioning mode matching result, which can dynamically match the positioning mode according to the environmental characteristics, improving the flexibility and accuracy of positioning. The positioning device is controlled according to the positioning mode matching result to perform real-time spatial position extraction, and based on the real-time position of the moving target, the building information is updated and the positioning mode of the positioning device is re-matched until the moving target leaves the target monitoring area. This process can dynamically adjust the positioning mode environment according to the real-time position change of the moving target, realizing continuous and accurate positioning of the moving target.

[0080] In summary, through the integration of UWB and RTK technologies, the embodiments of the present application can provide high-precision and high-reliability positioning results in different environments, overcome the limitations of single technologies, further improve the accuracy and environmental adaptability of positioning by introducing building information for positioning mode matching, can also track the position of the moving target in real time, and adjust the positioning mode according to environmental changes to ensure the continuous provision of accurate position information.

[0081] Embodiment 2, as Figure 4 shown, the embodiments of the present application provide a combined multi-point fusion spatial positioning system based on UWB and RTK, including:

[0082] A first position information acquisition unit 10, where the first position information acquisition unit 10 is used to obtain the first position information of the moving target based on the UWB positioning module.

[0083] A second position information acquisition unit 20, where the second position information acquisition unit 20 is used to obtain the second position information of the moving target based on the RTK positioning module.

[0084] A position data fusion unit 30, where the position data fusion unit 30 is used to perform position data fusion on the first position information and the second position information to obtain an initial position fusion result.

[0085] A building information extraction unit 40, which is configured to perform positioning of the moving target area location according to the initial position fusion result and extract the building information of the initial position fusion result.

[0086] A positioning mode matching unit 50, which is configured to match the positioning mode of the positioning device based on the building information and obtain a positioning mode matching result.

[0087] A real-time position extraction unit 60, which is configured to control the positioning device to perform real-time spatial position extraction according to the positioning mode matching result.

[0088] Furthermore, the position data fusion unit 30 in the embodiment of the present application is further configured to perform the following steps:

[0089] Perform a difference analysis on the first position information and the second position information to obtain a position difference parameter.

[0090] Determine whether the position difference parameter is less than or equal to a preset difference threshold.

[0091] If it is less than or equal to the preset difference threshold, perform position fusion calculation on the first position information and the second position information to obtain an initial position fusion result.

[0092] Furthermore, the position data fusion unit 30 in the embodiment of the present application is further configured to perform the following steps:

[0093] If the position difference parameter is greater than the preset difference threshold, construct a position data fusion module.

[0094] Input the first position information and the second position information into the position data fusion module for multi-point spatial position fusion to obtain an initial position fusion result.

[0095] Preferably, the position data fusion unit 30 in the embodiment of the present application is further configured to perform the following steps:

[0096] Collect sample first position information and sample second position information to obtain sample training data.

[0097] Perform a fusion position identification on the sample training data to obtain sample fusion position identification data.

[0098] Use the sample training data and the sample fusion position identification data as training data to construct a position data fusion module.

[0099] Further, in the positioning mode matching unit 50 in the embodiment of the present application, the positioning modes include: UWB single output mode, fusion output mode, and RTK single output mode.

[0100] Furthermore, the positioning mode matching unit 50 in the embodiments of the present application is further configured to perform the following steps:

[0101] Extract the building features included in the building information, where the building features include indoor features, outdoor features, and fusion features.

[0102] The fusion feature is the area range where the distance between the initial position fusion result of the moving target and the building edge is less than or equal to a preset distance.

[0103] Match the positioning mode of the positioning device based on the building features to obtain a positioning mode matching result.

[0104] Furthermore, the real-time position extraction unit 60 in the embodiments of the present application is further configured to perform the following steps:

[0105] Extract the real-time position of the moving target, update the building information of the real-time position of the moving target, and obtain updated building information.

[0106] Based on the updated building information, match the positioning mode of the positioning device to obtain an updated positioning mode matching result.

[0107] Control the positioning device to collect the position of the moving target in real time based on the updated positioning mode matching result until the moving target leaves the target monitoring area.

[0108] Through the foregoing detailed description of a combined multi-point fusion spatial positioning method based on UWB and RTK in this specification, those skilled in the art can clearly know a combined multi-point fusion spatial positioning system based on UWB and RTK in this embodiment. For the system disclosed in Embodiment 2, since it corresponds to the method disclosed in Embodiment 1, it has corresponding functional units and beneficial effects. For the relevant parts, reference can be made to the description in the method part.

[0109] The above description of the disclosed embodiments enables those skilled in the art to implement or use the present application. Various modifications to these embodiments will be obvious to those skilled in the art, and the general principles defined herein can be implemented in other embodiments without departing from the spirit or scope of the present application. Therefore, the present application will not be limited to these embodiments shown herein, but will be accorded the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A combined multi-point fusion spatial positioning method based on UWB and RTK, characterized in that: include: Acquire first position information of the mobile target based on the UWB positioning module; Acquire second position information of the mobile target based on the RTK positioning module; Performing position data fusion on the first position information and the second position information to obtain an initial position fusion result; Position the moving target area according to the initial position fusion result, and extract the building information of the initial position fusion result; Matching a positioning pattern of a positioning device based on the building information to obtain a positioning pattern matching result; The positioning device is controlled to extract the real-time spatial position according to the positioning pattern matching result.

2. According to claim 1, a combined multi-point fusion spatial positioning method based on UWB and RTK is characterized in that: The performing position data fusion on the first position information and the second position information to obtain an initial position fusion result includes: Performing difference analysis on the first location information and the second location information to obtain a location difference parameter; Determine whether the position difference parameter is less than or equal to a preset difference threshold; If it is less than or equal to the preset difference threshold, a position fusion calculation is performed on the first position information and the second position information to obtain an initial position fusion result.

3. According to claim 2, a combined multi-point fusion spatial positioning method based on UWB and RTK is characterized in that: The method further comprises: If the position difference parameter is greater than the preset difference threshold, constructing a position data fusion module; The first position information and the second position information are input into the position data fusion module to perform spatial position multi-point fusion to obtain an initial position fusion result.

4. According to claim 3, a combined multi-point fusion spatial positioning method based on UWB and RTK is characterized in that: The method further comprises: Collecting sample first position information and sample second position information to obtain sample training data; Performing fusion position identification on the sample training data to obtain sample fusion position identification data; The sample training data and the sample fusion position identification data are used as training data to construct a position data fusion module.

5. According to claim 1, a combined multi-point fusion spatial positioning method based on UWB and RTK is characterized in that: The positioning modes include: UWB single output mode, fusion output mode and RTK single output mode.

6. According to claim 1, a combined multi-point fusion spatial positioning method based on UWB and RTK is characterized in that: Matching a positioning pattern of a positioning device based on the building information to obtain a positioning pattern matching result includes: Extracting architectural features contained in the building information, wherein the architectural features include indoor features, outdoor features, and fusion features; The fusion feature is the area range where the fusion result of the initial position of the moving target is less than or equal to a preset distance from the edge of the building; The positioning pattern of the positioning device is matched based on the building features to obtain a positioning pattern matching result.

7. According to claim 1, a combined multi-point fusion spatial positioning method based on UWB and RTK is characterized in that: The method further comprises: Extracting the real-time position of the mobile target, and updating the building information of the real-time position of the mobile target, to obtain the updated building information; Based on the updated building information, matching of positioning patterns of positioning devices is performed to obtain updated positioning pattern matching results; Based on the updated positioning pattern matching result, the positioning device is controlled to collect the position of the moving target in real time until the moving target leaves the target monitoring area.

8. A combined multi-point fusion spatial positioning system based on UWB and RTK, characterized in that: include: A first position information acquisition unit, wherein the first position information acquisition unit is used to acquire first position information of a mobile target based on a UWB positioning module; A second position information acquisition unit, the second position information acquisition unit is used to acquire the second position information of the mobile target based on the RTK positioning module; A position data fusion unit, the position data fusion unit is used to perform position data fusion on the first position information and the second position information to obtain an initial position fusion result; A building information extraction unit, the building information extraction unit is used to locate the moving target area according to the initial position fusion result, and extract the building information of the initial position fusion result; A positioning pattern matching unit, the positioning pattern matching unit is used to match the positioning pattern of the positioning device based on the building information to obtain a positioning pattern matching result; A real-time position extraction unit is used to control the positioning device to perform real-time spatial position extraction according to the positioning pattern matching result.

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