Rotary single station positioning method and device for 5G-A industrial internet environment

Abstract

The invention provides a rotary single-station positioning method and device for a 5G-A industrial internet environment, and the method comprises the steps: obtaining a coordinate of a target base station, and a course angle sequence and a distance measurement sequence which are in time-space synchronization in a rotation process of a target object, and carrying out the fitting of the course angle sequence and the distance measurement sequence, obtaining a sine function curve for describing the change of the distance measurement value along with the course angle; determining an orientation moment when the target object directly faces the target base station according to an extreme point of the sine function curve; determining a target course angle and a target distance measurement value corresponding to the orientation moment respectively according to the course angle sequence and the distance measurement sequence; and determining position coordinates of the target object according to the target course angle, the target distance measurement value and the target base station coordinates. A self-contained positioning model is constructed through a single base station in combination with a ranging sequence and course angle information generated in the rotation process of a target object, and reliable position information is provided for a complex rescue scene in a low-cost and simple-operation mode.

Description

Technical Field

[0001] The present application relates to the field of industrial Internet and communication technology, and in particular to a rotating single-station positioning method and device for a 5G-A industrial Internet environment. Background Art

[0002] 5G-A (5G-Advanced), as an enhanced evolution of 5G, offers higher bandwidth, lower latency, and stronger connectivity. It is the core communications technology supporting the Industrial Internet's evolution towards ubiquitous connectivity, intelligent perception, and precise control. In the 5G-A Industrial Internet environment, the scale of interconnected industrial equipment, sensors, and personnel is growing exponentially, placing higher demands on positioning accuracy, real-time performance, and reliability. The unique characteristics of the 5G-A Industrial Internet environment, such as complex and high-interference environments, limited base station deployment, poor adaptability to dynamic scenarios, and the difficulty in balancing accuracy and robustness, present multiple technical challenges for positioning.

[0003] Existing technologies include single-base station positioning methods based on large antenna arrays and reflecting surfaces, and single-base station positioning methods assisted by inertial navigation, vision and other sensors. However, the first method relies on large antenna arrays or intelligent reflecting surfaces, has high hardware costs, low deployment flexibility, and is difficult to adaptively adjust in dynamic and complex environments; the second method is easily affected by lighting and texture, and the inertial navigation-assisted method cannot handle non-line-of-sight errors, resulting in low directional accuracy.

[0004] In view of the defects of the above-mentioned existing technologies, there is an urgent need for a positioning method that is low-cost, has high deployment flexibility, can be adaptively adjusted in dynamic and complex environments, and has high directional accuracy and is suitable for the complex environment of 5G-A industrial Internet. Summary of the Invention

[0005] In view of the above problems, the present application is proposed to provide a rotating single-station positioning method and device for a 5G-A industrial Internet environment that overcomes the above problems or at least partially solves the above problems, including: A rotating single-station positioning method for a 5G-Advanced industrial Internet environment is used to locate a target object using a single base station. The target object carries an inertial measurement positioning terminal and an ultra-wideband tag device and performs in-situ rotation. The method includes: Acquire the target base station coordinates, a heading angle sequence and a ranging sequence that are time-space synchronized during the rotation of the target object, and fit the heading angle sequence and the ranging sequence to obtain a sinusoidal function curve that describes the variation of the ranging value with the heading angle; Determining the orientation moment when the target object is facing the target base station according to the extreme point of the sine function curve; Determining a target heading angle and a target ranging value corresponding to the orientation moment according to the heading angle sequence and the ranging sequence respectively; The position coordinates of the target object are determined according to the target heading angle, the target ranging value, and the target base station coordinates.

[0006] Furthermore, the step of obtaining a temporally and spatially synchronized heading angle sequence and ranging sequence during the rotation of the target object includes: Obtaining an IMU data sequence collected by the inertial measurement and positioning terminal, and solving the IMU data sequence to obtain a continuous heading angle sequence; The heading angle sequence and the distance measurement sequence are subjected to spatiotemporal synchronization processing.

[0007] Furthermore, the step of obtaining a temporally and spatially synchronized heading angle sequence and ranging sequence during the rotation of the target object includes: Acquire two complete round-trip signal data between the ultra-wideband tag device and the target base station, and determine the one-way flight time of the signal between the ultra-wideband tag device and the target base station based on the two complete round-trip signal data; A relative distance between the ultra-wideband tag device and the target base station is generated according to the flight time and the speed of light.

[0008] Furthermore, the step of fitting the heading angle sequence and the ranging sequence to obtain a sinusoidal function curve describing the variation of the ranging value with the heading angle includes: Establishing an approximate sinusoidal model of the distance measurement value varying with the heading angle according to the distance measurement sequence and the heading angle sequence; The parameters of the approximate sinusoidal model are globally optimized, and when the convergence conditions are met, the optimal parameters and the corresponding sinusoidal function curve are output; wherein the parameters include the straight-line distance between the rotation center and the target base station, the rotation radius, and the orientation angle of the target object.

[0009] Furthermore, the steps of globally optimizing the parameters of the approximate sine model and outputting the optimal parameters and the corresponding sine function curve when the convergence condition is met include: Initializing parameters of the approximate sinusoidal model; Iterative optimization is performed based on dynamic adjustment of search weights to determine the fitness value of the current parameters in each iteration; When the fitness value reaches the convergence condition, the corresponding optimal parameters and the sine function curve are output.

[0010] Furthermore, the step of performing iterative optimization based on dynamically adjusting the search weight and determining the fitness value of the current parameter in each iteration includes: Determining the weight of a data point according to the heading angle corresponding to the data point in the ranging sequence; Determining a predicted distance value of the data point based on the current parameters and the approximate sine model; Determining a deviation between the predicted distance value and the measured distance value of the data point, and processing the deviation using a robust kernel function; The product of the processed deviations of all data points and the corresponding weights is accumulated and summed to generate the fitness value of the current parameter.

[0011] Furthermore, the calculation formula of the fitness is as follows:

[0012] Where, is the weight of the i-th data point, is a robust kernel function;

[0013] Where, is the weight of the non-line-of-sight data point, is the heading angle corresponding to the current data point,

[0014] is the starting angle of the non-line-of-sight interval, is the end angle of the non-line-of-sight interval;

[0015] Where, is the deviation value, is the error threshold.

[0016] A rotating single-station positioning device for a 5G-A industrial Internet environment is used to locate a target object using a single base station. The target object carries an inertial measurement positioning terminal and an ultra-wideband tag device and performs in-situ rotation. The device includes: a curve fitting module, configured to obtain the coordinates of the target base station, a heading angle sequence and a ranging sequence that are synchronized in time and space during the rotation of the target object, and to fit the heading angle sequence and the ranging sequence to obtain a sinusoidal function curve that describes how the ranging value changes with the heading angle; a time determination module, configured to determine the orientation time when the target object is facing the target base station according to the extreme value point of the sine function curve; a data determination module, configured to determine a target heading angle and a target ranging value corresponding to the orientation moment according to the heading angle sequence and the ranging sequence respectively; A position calculation module is used to determine the position coordinates of the target object according to the target heading angle, the target ranging value and the target base station coordinates.

[0017] A computer electronic device includes a processor, a memory, and a computer program stored in the memory and capable of running on the processor. When the computer program is executed by the processor, the steps of the rotating single-station positioning method for the 5G-A industrial Internet environment as described above are implemented.

[0018] A computer-readable storage medium stores a computer program, which, when executed by a processor, implements the steps of the rotating single-station positioning method for a 5G-A industrial Internet environment as described above.

[0019] This application has the following advantages: In an embodiment of the present application, compared with the problems of high hardware cost, low deployment flexibility, difficulty in adaptive adjustment in dynamic and complex environments, and low orientation accuracy in the prior art, the present application provides a solution to a rotating single-base station positioning method based on an intelligent optimization algorithm integrating ultra-wideband (UWB) and inertial navigation (IMU), specifically: obtaining the coordinates of the target base station, a heading angle sequence and a ranging sequence that are synchronized in time and space during the rotation of the target object, and fitting the heading angle sequence and the ranging sequence to obtain a sinusoidal function curve for describing the variation of the ranging value with the heading angle; determining the orientation moment when the target object is facing the target base station based on the extreme point of the sinusoidal function curve; determining the target heading angle and target ranging value corresponding to the orientation moment based on the heading angle sequence and the ranging sequence respectively; and determining the position coordinates of the target object based on the target heading angle, the target ranging value, and the target base station coordinates. By combining the dynamic ranging sequence generated during the target's rotation with the IMU's heading angle information from a single base station, a self-contained positioning model is constructed. This breaks through the traditional multi-base station system's heavy reliance on fixed infrastructure, enabling reliable initial positioning with a minimal number of base stations or single-point deployments. This provides reliable location information for complex rescue scenarios in a cost-effective and simple manner. Using a fitted sinusoidal function curve as an anti-interference positioning strategy, the system addresses the interference issues that complex metal structures, equipment obstruction, and multipath reflections can cause on the rotational positioning accuracy in industrial Internet environments, improving both positioning and orientation accuracy and anti-interference capabilities. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] In order to more clearly illustrate the technical solution of the present application, the following is a brief introduction to the drawings required for the description of the present application. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without any creative work.

[0021] Figure 1This is a rotation flow diagram of a rotation single-station positioning method for a 5G-A industrial Internet environment provided by an embodiment of the present application; Figure 2 This is a flowchart of the steps of a rotating single-station positioning method for a 5G-A industrial Internet environment provided by an embodiment of the present application; Figure 3 This is a flowchart of a rotating single-station positioning method for a 5G-A industrial Internet environment provided by an embodiment of the present application; Figure 4 This is a schematic diagram of a bilateral two-way ranging process of a rotating single-station positioning method for a 5G-A industrial Internet environment provided by an embodiment of the present application; Figure 5 This is a distance measurement data set diagram collected in an underground sheltered space provided by an embodiment of the present application; Figure 6 This is a continuous heading angle sequence diagram collected in an underground sheltered space provided by an embodiment of the present application; Figure 7 This is a diagram showing the fitting results of the ranging sequence and heading angle sequence provided in one embodiment of the present application; Figure 8 This is an example of a pilot pattern for 1 / 3 devices provided in an embodiment of the present application; Figure 9 This is a comparison chart of positioning results in a mixed line-of-sight environment provided by an embodiment of the present application; Figure 10 This is a structural block diagram of a rotating single-station positioning device for a 5G-A industrial Internet environment provided by an embodiment of the present application; Figure 11 It is a structural diagram of a computer device provided by one embodiment of the present invention. DETAILED DESCRIPTION

[0022] To make the objectives, features, and advantages of this application more readily apparent, the present application is further described below in conjunction with the accompanying drawings and specific embodiments. It is apparent that the embodiments described are only a portion of the embodiments of this application, not all of them. All other embodiments derived by persons of ordinary skill in the art based on the embodiments in this application without inventive effort are also within the scope of protection of this application.

[0023] The inventors found out through analysis of prior art 1 and prior art 2 that: Existing technology 1: A single-base station positioning method based on a large antenna array and a reflecting surface uses a large antenna array combined with geometric elements such as a reflecting surface to locate a single base station. This method generally arranges the antenna array according to certain geometric rules, or uses spatial geometric rules to estimate the direction of arrival, thereby completing the positioning function.

[0024] However, for this type of approach, millimeter-wave antennas must support high gain, narrow beams, and dynamic beamforming capabilities. This places stringent demands on the phase consistency of antenna units and the accuracy of array calibration. Especially in the complex environments of the 5G-Advanced Industrial Internet, signal penetration loss and multipath interference can further amplify antenna performance defects, leading to failure in reflector control or channel parameter estimation errors. Furthermore, intelligent reflectors require a dense arrangement of a large number of tunable electromagnetic units, which not only imposes high hardware costs but also makes it difficult to balance reflector size, unit density, and response speed. Large-scale deployments face multiple challenges in power consumption, heat dissipation, and reliability. Furthermore, the system's positioning accuracy is highly dependent on the topological layout of the reflector and base station. The spatial position and angular orientation of the reflector must be pre-planned based on the environmental structure. Real-time adaptive adjustment is difficult in dynamic scenarios or unknown obscured areas, limiting the technology's ability to generalize across scenarios. These factors hinder the solution's cost controllability and deployment flexibility in industrial applications, making it difficult to meet the demand for low-cost, rapidly deployable, and universal positioning.

[0025] Existing technology 2: Single-base station positioning methods assisted by sensors such as inertial navigation and vision. The core of this method is to estimate the angle of arrival and distance by leveraging the complementary characteristics of multi-source heterogeneous sensors. This method typically uses the ranging or angle measurement information of a single base station (such as a UWB or millimeter wave base station) as the global position constraint benchmark, while combining inertial navigation or vision sensors to infer short-term, high-frequency relative displacement and attitude changes or compensate for multipath and non-line-of-sight errors.

[0026] However, the visual positioning module of the second existing method is highly dependent on ambient lighting conditions and texture features. In the complex environment of the 5G-Advanced Industrial Internet, the grayscale images of the monocular camera are prone to exposure anomalies, feature point loss, or matching errors, affecting positioning accuracy. Furthermore, the method is expensive and unsuitable for use in blind environments. The second existing method cannot handle non-line-of-sight and multipath anomaly observations. Furthermore, the template matching method is essentially a single-dimensional matching method in the time dimension, which does not utilize geometric spatial position information and has poor orientation accuracy.

[0027] In order to realize personnel positioning in complex shielded spaces with low cost, simple operation and only using a single base station, the inventors designed a single base station rotation positioning method that combines inertial navigation and UWB, such as Figure 1 As shown, the target object is the test person, who needs to wear a positioning terminal with an integrated inertial measurement unit and hold an ultra-wideband tag device to rotate in place.

[0028] It should be noted that the target object can also be a device that can perform rotational motion. The positioning terminal integrated with an inertial measurement unit is mainly composed of a three-axis accelerometer, a three-axis gyroscope and a magnetometer. By measuring the angular velocity and acceleration of the carrier in three-dimensional space, combined with the initial position information, the strapdown inertial navigation algorithm is used to infer the current position and attitude. The ultra-wideband tag device is a wireless positioning terminal based on pulse radio technology, which mainly includes a UWB radio frequency module, a baseband processing unit and an antenna system. In this application, it transmits nanosecond narrow pulse signals to perform bilateral two-way ranging with the target base station, and accurately measures the signal flight time to calculate the distance.

[0029] The core concept of the present invention is: (1) Different from the limitations of existing single-base station positioning that relies on static geometric solutions, this invention constructs a dynamic positioning scenario through active rotation equipment, innovatively temporally and spatially correlating the periodic ranging sequence generated when a person rotates a handheld UWB tag with the IMU attitude and heading angle. Based on the sinusoidal variation of ranging values ​​induced by rotational motion, the core idea of ​​using dynamic trajectory fitting to replace static point-to-point positioning is proposed. By jointly analyzing the continuous ranging data and heading angle sequence during the rotation process, the dependence of single-base station positioning on geometric constraints is overcome, significantly improving the positioning reliability in complex shielding scenarios.

[0030] (2) To address the problems of outliers in ranging and accumulated attitude errors caused by environmental interference, a multi-dimensional feature matching framework is proposed that integrates an improved snake optimization algorithm. By introducing a dynamic inertia weight adjustment mechanism and an adaptive search strategy, the algorithm's ability to identify and eliminate outliers such as non-line-of-sight (NLOS) and multipath distortion is enhanced. At the same time, the heading angle confidence weight is combined with the matching process to achieve robust direction and distance joint solution in high-noise environments. This strategy effectively suppresses the negative impact of environmental interference on positioning accuracy through the dual optimization of intelligent algorithms and outlier processing. The directional accuracy is improved by more than 15 degrees compared to traditional methods, showing significant advantages in mixed line-of-sight scenarios.

[0031] Reference Figure 2 and Figure 3 , showing a rotating single-station positioning method for a 5G-A industrial Internet environment provided by an embodiment of the present application; The method comprises: S210: Acquire target base station coordinates, a heading angle sequence and a ranging sequence that are time-space synchronized during the rotation of the target object, and fit the heading angle sequence and the ranging sequence to obtain a sinusoidal function curve describing how the ranging value changes with the heading angle. S220: Determine the orientation moment when the target object is facing the target base station according to the extreme point of the sine function curve; S230, determining a target heading angle and a target ranging value corresponding to the orientation moment according to the heading angle sequence and the ranging sequence respectively; S240: Determine the position coordinates of the target object according to the target heading angle, the target ranging value, and the target base station coordinates.

[0032] In the embodiments of the present application, a self-contained positioning model is constructed by combining the dynamic ranging sequence generated during the rotation of the target object with the IMU heading angle information through a single base station. This breaks through the high dependence of traditional multi-base station systems on fixed infrastructure, and can achieve reliable initial positioning under conditions of extremely small number of base stations or single-point deployment, providing reliable location information for complex rescue scenarios in a low-cost and simple manner. By using the fitted sine function curve as an anti-interference positioning strategy, the problem of interference with the rotation positioning accuracy caused by complex metal structures, equipment obstruction, and multipath reflection in the industrial Internet environment is solved, thereby improving the positioning and orientation accuracy and anti-interference performance.

[0033] Below, a rotating single-station positioning method for a 5G-A industrial Internet environment in this exemplary embodiment will be further explained.

[0034] As described in step S210, the target base station coordinates, the spatiotemporally synchronized heading angle sequence and the ranging sequence during the rotation of the target object are obtained, and the heading angle sequence and the ranging sequence are fitted to obtain a sinusoidal function curve for describing the variation of the ranging value with the heading angle.

[0035] It should be noted that the target base station coordinates are the pre-known positions of the UWB base station in the global coordinate system, which are the reference points for positioning solutions and can be obtained through pre-measurement or system configuration.

[0036] In an embodiment of the present invention, the specific process of "obtaining a temporally and spatially synchronized heading angle sequence and ranging sequence during the rotation of the target object" in step S210 may be further explained in conjunction with the following description.

[0037] As described in the following steps, an IMU data sequence collected by the inertial measurement and positioning terminal is obtained, and the IMU data sequence is solved to obtain a continuous heading angle sequence; the heading angle sequence and the ranging sequence are subjected to spatiotemporal synchronization.

[0038] Specifically, testers are required to simultaneously wear a positioning terminal with an integrated inertial measurement unit (IMU) and hold an ultra-wideband (UWB) tag device to perform rotational motion in place. During the rotation process, the system simultaneously performs two core operations: first, the IMU collects raw data such as three-axis acceleration and angular velocity in real time, and uses the strapdown inertial navigation algorithm to calculate and generate a continuous heading angle sequence; second, the UWB module continuously receives ranging signals sent by the base station, records the dynamically changing distance measurements during the rotation process, and adds a timestamp to achieve spatiotemporal synchronization with the IMU data. This step establishes the dynamic relationship between direction and distance through active rotation, providing a basic data set for subsequent optimization processing.

[0039] In an embodiment of the present invention, the specific process of obtaining the ranging sequence in step S210 may be further explained in combination with the following description.

[0040] As described in the following steps, two complete round-trip signal data between the ultra-wideband tag device and the target base station are obtained, and the one-way flight time of the signal between the ultra-wideband tag device and the target base station is determined based on the two complete round-trip signal data; the relative distance between the ultra-wideband tag device and the target base station is generated based on the flight time and the speed of light.

[0041] As an example, the tester holds a UWB tag and continuously performs bilateral two-way ranging with a distant UWB base station (target base station) during rotation. The clock synchronization error is eliminated through two complete signal round trips to achieve high-precision one-way flight time calculation. The signal propagation time and device processing time are recorded through timestamps, and the processing time error is eliminated through redundant equations, retaining only the one-way propagation time to ensure that the ranging accuracy is not affected by device clock drift.

[0042] In a specific implementation, the bilateral two-way ranging process is as follows: Figure 4 During bilateral two-way ranging, the UWB base station and the UWB tag record the time of each data transmission and reception, generating a total of 6 timestamps. Based on two complete signal round trip processes, the coordinated timestamp exchange between devices is used to construct redundant equations to achieve algebraic elimination of error terms. The signal flight time calculation method is:

[0043] Where, T prop is the flight time of the signal from the UWB tag to the UWB base station; T round1 and T round2 Indicates the time difference of the UWB tag receiving the signal; T reply1 and T reply2 Indicates the time difference of the UWB base station receiving the signal.

[0044] Based on this, we can obtain the ranging data sequence required for positioning and orientation. The relative distance is calculated as follows:

[0045] Where, The speed of light.

[0046] After the above steps, the ranging sequence in the rotation process can be collected to complete the construction of the ranging data set. After actual testing, the ranging data set collected in the underground sheltered space is as follows: Figure 5 As shown in the figure, it can be seen from the data that there are a lot of data distortions caused by non-line-of-sight effects and multipath effects in the measured blind environment. Therefore, it is difficult to directly determine the facing angle. Therefore, curve fitting is needed first to increase the recognition accuracy.

[0047] In one embodiment of the present invention, the specific process of obtaining the heading angle sequence in step S210 may be further explained in conjunction with the following description.

[0048] Specifically, to estimate relative angles, this embodiment uses the heading angle information output by the inertial navigation system in conjunction with the UWB ranging sequence to uniformly determine the relative angle. Specifically, the tester, wearing the inertial navigation system and holding the UWB tag, rotates in place for several cycles while the UWB base station performs ranging. This allows the collection of UWB data and heading angle data calculated by the inertial navigation system over multiple rotation cycles.

[0049] As an example, quaternions are a mathematical tool for describing rotations in three-dimensional space. They can be represented as a four-dimensional vector consisting of a real component and three imaginary components, reflecting the attitude of a target object. Quaternions are used to calculate heading angles because they enable continuous attitude updates during rotations with minimal computational effort.

[0050] The specific process is:

[0051] Where, Represents the rotation matrix from the body coordinate system to the navigation coordinate system; 、 、 Roll , pitch angle and heading angle , and then the attitude information is corrected. At this time, the transformation from the original quaternion information to the attitude matrix information occurs. The process is:

[0052]

[0053]

[0054] Where C32 represents the element in the third row and second column, which represents the cosine of the projection of the body's y-axis direction on the reference system's z-axis direction; C33 represents the third row and third column element, which represents the cosine of the projection of the body's z-axis direction on the reference system's z-axis direction; C31 represents the element in the first column of the third row, which represents the cosine of the projection of the body's x-axis direction on the z-axis direction of the reference system; C21 represents the element in the second row and first column, which represents the cosine of the projection of the body's x-axis direction on the reference system's y-axis direction; C11 represents the element in the first row and first column, which represents the cosine of the projection of the body's x-axis direction on the reference system's x-axis direction.

[0055] The above is the continuous calculation process of attitude information. After field testing, the collected continuous heading angle sequence results are as follows: Figure 6 shown.

[0056] In one embodiment of the present invention, the specific process of "fitting the heading angle sequence and the ranging sequence to obtain a sinusoidal function curve describing how the ranging value varies with the heading angle" in step S210 may be further described in conjunction with the following description.

[0057] As described in the following steps, an approximate sinusoidal model is established based on the ranging sequence and the heading angle sequence, in which the ranging value varies with the heading angle. The parameters of the approximate sinusoidal model are globally optimized, and when the convergence condition is met, the optimal parameters and the corresponding sinusoidal function curve are output. The parameters include the straight-line distance between the rotation center and the target base station, the rotation radius, and the orientation angle of the target object.

[0058] Specifically, an improved snake optimization algorithm is used to robustly fit the original ranging sequence to address distortion interference caused by non-line-of-sight (NLOS) propagation and multipath effects in UWB ranging data due to occlusion by humans and obstacles. This algorithm, combined with dynamic inertia weight adjustment and an adaptive search strategy, uses global optimization to identify and eliminate anomalous ranging points while fitting valid ranging values ​​to a sinusoidal function curve that conforms to the laws of rotational motion. This process focuses on addressing signal distortion in harsh environments. Mathematical modeling reveals the periodic characteristics of ranging values ​​as they change with rotation angle, accurately capturing the physical pointing state of the device when it is facing the base station (i.e., the peaks and troughs of the sinusoidal curve).

[0059] In one embodiment of the present invention, the specific process of the step of "globally optimizing the parameters of the approximate sine model, and outputting the optimal parameters and the corresponding sine function curve when the convergence conditions are met" can be further explained in combination with the following description.

[0060] As described in the following steps, the parameters of the approximate sine model are initialized; iterative optimization is performed based on the dynamic adjustment of the search weight to determine the fitness value of the current parameter in each iteration; when the fitness value reaches the convergence condition, the corresponding optimal parameters and the sine function curve are output.

[0061] As an example, initialization can use a random generation method, that is, randomly selecting parameter combinations within a preset range to ensure the diversity of the initial population and lay the foundation for global optimization. This method uses an improved snake optimization algorithm to tune directional accuracy. During the iterative process, the algorithm's inertia weight is dynamically changed according to the number of iterations. When the change in fitness value after N consecutive iterations is less than a threshold, the corresponding parameters are the optimal parameters. Substituting them into an approximate sine model, a fitted sine function curve can be generated. This curve reflects the periodic law of the change in ranging value with heading angle, and its extreme points correspond to the moments when the target object is facing / facing away from the base station.

[0062] In a specific implementation, this embodiment is based on the abnormal ranging fitting driven by the improved optimization algorithm. During the rotation data collection process, we assume that the initial orientation angle of the person is , the straight-line distance between the rotation center and the base station is , the handheld rotation radius is r, then the distance formula is as follows:

[0063] So when >> When , the distance formula can be approximated as the superposition of sine, cosine and offset; when the person faces away from the base station, the maximum value of the ranging will appear. When the person turns from facing away to facing the front, the ranging value will decrease again until it becomes the minimum when facing the front. Therefore, the obtained ranging sequence and angle sequence can be fitted into a sine function curve. If the exhaustive method is used, a lot of computing resources will be consumed, and the least squares method will inevitably fall into the local optimal solution. Therefore, the improved snake optimization algorithm is used for intelligent parameter search.

[0064] In one embodiment of the present invention, the specific process of the step of "performing iterative optimization based on dynamically adjusting the search weight and determining the fitness value of the current parameter in each iteration" can be further explained in combination with the following description.

[0065] As described in the following steps, the weight of the data point is determined based on the heading angle corresponding to the data point in the ranging sequence; the predicted distance value of the data point is determined based on the current parameters and the approximate sine model; the deviation between the predicted distance value and the measured ranging value of the data point is determined, and the deviation is processed using a robust kernel function; the product of the processed deviations of all data points and the corresponding weights is accumulated and summed to generate a fitness value for the current parameters.

[0066] For example, when the target object is facing the base station (line-of-sight), the ranging value is more reliable and has a higher weight. When it is facing away from the base station (non-line-of-sight), the ranging value is easily affected by occlusion and has a lower weight. By presetting the non-line-of-sight interval, data points falling within it are given a low weight, while data points in other intervals are given a high weight, thereby suppressing the impact of NLOS errors on the fitting.

[0067] The approximate sinusoidal model is constructed based on the geometric characteristics of rotational motion. Current parameters include the straight-line distance from the rotation center to the base station, the rotation radius, and the initial heading angle. For each data point's heading angle, the model substitutes these current parameters to calculate a predicted distance value, which reflects the ideal relationship between the measured distance and the heading angle.

[0068] Deviation is the difference between the measured distance and the predicted distance, reflecting the degree of deviation between the model and the actual data. Due to multipath reflections, sudden interference, and other factors in industrial environments, some data points may experience significant deviations. Directly applying squared error would amplify these deviations. The robust kernel function uses segmented processing, squaring small deviations to preserve their corrective effect on the model; and linearizing large deviations to mitigate outlier interference and ensure fitting stability.

[0069] The current parameters are evaluated by combining the weighted deviations of all data points. The fitness value is a key indicator of model fit; smaller values ​​indicate a closer fit between the sinusoidal model corresponding to the current parameters and the measured data. During the calculation process, deviations in the non-line-of-sight interval are weighted down, and deviations from outliers are compressed by a robust kernel function. The final summation reflects the overall fit trend while suppressing local interference, providing a reliable objective function for subsequent parameter optimization.

[0070] In a specific implementation, when selecting the fitness function, if the abnormal outliers and the non-line-of-sight distortion values ​​when facing away are not treated differently, the fitting accuracy will be unsatisfactory. Therefore, the fitness function selected in this embodiment is:

[0071] Where, is the weight of the i-th data point, is a robust kernel function;

[0072] Where, is the weight of the non-line-of-sight data point, is the heading angle corresponding to the current data point,

[0073] is the starting angle of the non-line-of-sight interval, is the end angle of the non-line-of-sight interval;

[0074] Where, is the deviation value, is the error threshold.

[0075] By introducing a robust kernel function with variable weight restrictions, the influence of relative outliers on the orientation accuracy is reduced, and the influence of the non-line-of-sight effect on the orientation accuracy caused by the person facing away from the base station can also be reduced, which reflects the difference between the predicted value and the measured value. By fitting the distance measurement sequence and the heading angle sequence to optimize their parameters, the angle value and distance value at the time of facing are found. The fitting experimental results are as follows Figure 7 shown.

[0076] As described in step S220, the orientation moment when the target object faces the target base station is determined according to the extreme point of the sine function curve.

[0077] Specifically, when the target object rotates in place, the ranging value changes sinusoidally with the heading angle. When the target object is facing the base station, the heading angle directly points to the base station, and the ranging value is most accurate, which can avoid multipath interference and NLOS errors. This embodiment determines the facing moment of the target person through the fitted sine function curve. Since the ranging value changes sinusoidally with the heading angle, the minimum point of the curve corresponds to the moment when the target object is facing the base station, and the occlusion between the UWB tag and the base station is minimal; the maximum point corresponds to the moment when it is facing away from the base station, and the occlusion is maximum. Therefore, the orientation moment can be determined by identifying the minimum point.

[0078] As described in step S230, the target heading angle and target ranging value corresponding to the orientation moment are determined according to the heading angle sequence and the ranging sequence respectively.

[0079] As an example, the orientation moment is associated with the raw data sequence to extract key parameters for positioning. The heading angle sequence is generated by the IMU using quaternion calculations and contains the angle information corresponding to each timestamp; the ranging sequence is generated by UWB bilateral ranging and contains the distance information corresponding to each timestamp. Because the two sequences are spatiotemporally synchronized via timestamps, at the orientation moment, the corresponding angle value can be directly indexed from the heading angle sequence, and the corresponding distance value can be directly indexed from the ranging sequence.

[0080] In one specific implementation, after determining the moment of orientation facing the base station based on the minimum point of the fitted sinusoidal curve, the IMU heading angle calculation corresponding to that moment is simultaneously extracted as the final heading estimate, and the corresponding UWB ranging value is used as the undistorted distance measurement. Once the coordinate point corresponding to the minimum value of the fitted curve is obtained, it is paired with the collected heading angle sequence according to time to complete the orientation operation. Template matching is a matching algorithm designed by previous researchers. To determine the relative position of a person, this method generates a unique template sequence based on the mathematical relationship between the person and the UWB base station (this relationship is determined by the model itself). This template sequence is then compared with the ranging sequence, and this comparison is performed horizontally in one dimension. During the matching process, the sum of the differences between the two curves at multiple times is continuously calculated until the position with the minimum sum is found. Finally, the heading angle value corresponding to the minimum value in the template sequence is determined as the target angle value for the person facing the base station. This method is essentially a single-dimensional matching process with low accuracy; the method used in this paper is a matching process based on multidimensional features.

[0081] Analysis shows that the improved snake optimization algorithm's fitted curve best matches the true reference curve. Specifically, the improved snake optimization algorithm's fitting angle deviation is 5.96 degrees, the genetic algorithm's fitting angle deviation is 14.32 degrees, and the template matching method's fitting angle deviation is 21.14 degrees. Compared to the genetic algorithm-optimized fitting method, the proposed algorithm achieves an 8.36-degree improvement in orientation accuracy, and 15.18 degrees compared to the template matching method. It also improves computational efficiency, avoids the waste of computing resources caused by the exhaustive method, and saves time.

[0082] As described in step S240 , the position coordinates of the target object are determined according to the target heading angle, the target ranging value, and the target base station coordinates.

[0083] Specifically, the target heading angle and target ranging value are the core inputs for positioning solutions. The target heading angle reflects the direction of the target relative to the base station, and the target ranging value reflects the straight-line distance between the target and the base station. The two, combined with the base station coordinates, can be used to calculate the target position through geometric relationships. Timestamp matching is used to achieve spatiotemporal alignment of the heading angle and ranging data. Combined with the known coordinates of the base station, the single-base station positioning solution is completed and the target's position coordinates are output. Through the cross-sensor data fusion strategy, the geometric constraints of single-base station positioning are broken through, and a deterministic mapping relationship between direction and distance is established while eliminating environmental interference, ultimately achieving reliable positioning services in complex scenarios. By using the relative direction and relative distance determined by the above steps, an accurate estimate of the position is achieved.

[0084] In a specific implementation, based on the principle of conversion from polar coordinates to rectangular coordinates, the base station coordinates are used as the origin, the target heading angle is the polar angle, and the target distance value is the polar diameter to calculate the relative coordinates of the target object.

[0085] In order to verify the performance superiority of the present invention when the number of available base stations is reduced and the non-line-of-sight effect is serious, field test experiments were carried out under line-of-sight and mixed line-of-sight conditions. In this scenario, the coordinates of base station 1 broadcast are (5.1m, 0m), and the coordinates of base station 2 are (22m, 7m). At this time, the tag starts working. After receiving the information broadcast by the base station, the tag transfers the information and performs bilateral two-way ranging with the other two base stations. After obtaining all the required information, the method of the present invention can be used to perform three-sided solution on the position information, and finally save the calculated coordinate information. In the rotation positioning process based on the improved snake optimization algorithm designed by the present invention, we carry the inertial navigation and handheld tags to rotate in place for several weeks, transfer the two collected sequences, run the snake optimization algorithm for fitting orientation and positioning, and thus obtain the position coordinate information we need. This is the specific workflow. First, we conducted experiments in an unobstructed complex environment of the 5G-A industrial Internet. The experimental results are as follows: Figure 8 As shown in Table 1, it is an example of a pilot pattern under the condition of 1 / 3 devices.

[0086] Table 1 RMSE comparison under line-of-sight conditions

[0087] From the above data, we can see that in the harsh environment of 5G-A Industrial Internet, the positioning accuracy of the two algorithms is lower than the results of the previous simulation analysis. And the accuracy of the rotation positioning algorithm based on the improved snake optimization algorithm is only 1.44cm higher than the three-sided positioning method. In order to better verify the performance and applicable scenarios of the algorithm, this embodiment continued to conduct experiments under mixed conditions of line-of-sight and non-line-of-sight. The results are as follows Figure 9 and as shown in Table 2.

[0088] Table 2 RMSE comparison under mixed viewing distance conditions

[0089] From the above data, it can be seen that because this embodiment adds non-line-of-sight obstruction to the straight-line propagation path between the two base stations and the tag, the results of the three-sided positioning method will be offset in one direction. Because the actual position of the person is between the two base stations, some errors will be offset, showing a more reliable positioning result than a single base station obstruction. Therefore, due to multiple factors such as the limited placement of base stations and the decrease in the number of available line-of-sight base stations, the positioning accuracy of the three-sided positioning method in this scenario is relatively low, only reaching the meter level. However, the rotation positioning method based on improved snake optimization proposed in this invention is significantly better than the former in mixed line-of-sight scenarios, with improvements of 80.5% and 88.1% respectively. It can meet the needs of more accurate emergency positioning in such scenarios, and provide a more accurate initial position for the fusion positioning system, enhancing system performance.

[0090] The advantages of the present invention are: (1) In the complex environment of the 5G-A industrial Internet, the positioning system often fails due to the limited deployment and insufficient number of base stations. To solve this problem, a single base station architecture can be adopted. In combination with the active rotation of personnel, the dynamic ranging sequence generated during the rotation and the IMU heading angle information are used to build a self-contained positioning model. This solution breaks through the traditional multi-base station system's high dependence on fixed infrastructure and can achieve reliable initial positioning under the conditions of a very small number of base stations or single-point deployment, providing reliable location information for complex rescue scenarios in a low-cost and simple manner.

[0091] (2) Considering the interference problem of complex metal structures, equipment occlusion and multipath reflection on the rotation positioning accuracy in the industrial Internet environment, this paper designs an anti-interference positioning strategy based on the improved snake optimization algorithm. The algorithm enhances the sensitivity to abnormal ranging points by dynamically adjusting the search weight and iteration step size, and by introducing a fitness function with robust kernel restrictions, it constructs a multi-dimensional matching constraint based on the heading angle change trend, and fits the ranging sequence into a periodic azimuth and distance mapping curve. Compared with the single-dimensional template matching algorithm in the existing technology, it significantly improves the positioning and orientation accuracy and anti-interference performance. At the same time, it optimizes the spatiotemporal correlation between the heading angle and the ranging value, further improving the orientation accuracy and avoiding falling into the local optimal solution.

[0092] As for the device embodiment, since it is basically similar to the method embodiment, the description is relatively simple, and the relevant parts can be referred to the partial description of the method embodiment.

[0093] Reference Figure 10 , shows a rotating single-station positioning device for a 5G-A industrial Internet environment provided by an embodiment of the present application, which is used to locate a target object through a single base station. The target object carries an inertial measurement positioning terminal and an ultra-wideband tag device to perform in-situ rotational motion; the device includes; Specifically include: The curve fitting module 1010 is used to obtain the coordinates of the target base station, the heading angle sequence and the ranging sequence that are synchronized in time and space during the rotation of the target object, and fit the heading angle sequence and the ranging sequence to obtain a sinusoidal function curve that describes the variation of the ranging value with the heading angle; A time determination module 1020 is configured to determine the orientation time when the target object faces the target base station according to the extreme value point of the sine function curve; A data determination module 1030 is configured to determine a target heading angle and a target ranging value corresponding to the orientation moment according to the heading angle sequence and the ranging sequence, respectively; The position calculation module 1040 is configured to determine the position coordinates of the target object according to the target heading angle, the target ranging value, and the target base station coordinates.

[0094] In one embodiment of the present invention, the curve fitting module 1010 includes: The data acquisition submodule is used to obtain the IMU data sequence collected by the inertial measurement and positioning terminal, and to solve the IMU data sequence to obtain a continuous heading angle sequence; The data synchronization submodule is used to perform spatiotemporal synchronization processing on the heading angle sequence and the ranging sequence.

[0095] In one embodiment of the present invention, the curve fitting module 1010 includes: A UWB information transmission submodule is configured to obtain two complete round-trip signal data between the ultra-wideband tag device and the target base station, and determine the one-way flight time of the signal between the ultra-wideband tag device and the target base station based on the two complete round-trip signal data; The UWB distance measurement submodule is configured to generate a relative distance between the ultra-wideband tag device and the target base station according to the flight time and the speed of light.

[0096] In one embodiment of the present invention, the curve fitting module 1010 includes: A model building submodule, configured to build an approximate sinusoidal model of the distance measurement value varying with the heading angle based on the distance measurement sequence and the heading angle sequence; The parameter optimization submodule is used to globally optimize the parameters of the approximate sinusoidal model, and when the convergence conditions are met, output the optimal parameters and the corresponding sinusoidal function curve; wherein the parameters include the straight-line distance between the rotation center and the target base station, the rotation radius, and the orientation angle of the target object.

[0097] In one embodiment of the present invention, the parameter optimization submodule includes: An initialization unit, used for initializing the parameters of the approximate sine model; An iterative optimization unit, configured to perform iterative optimization based on dynamically adjusting search weights and determine the fitness value of the current parameter in each iteration; The convergence unit is used to output the corresponding optimal parameters and the sine function curve when the fitness value reaches the convergence condition.

[0098] In one embodiment of the present invention, the iterative optimization unit includes: a weight calculation subunit, configured to determine the weight of a data point in the ranging sequence according to the heading angle corresponding to the data point; a distance prediction subunit, configured to determine a predicted distance value of the data point based on the current parameters and the approximate sine model; a deviation calculation subunit, configured to determine a deviation between the predicted distance value and the measured distance value of the data point, and process the deviation using a robust kernel function; The fitness calculation subunit is used to accumulate and sum the products of the processed deviations of all data points and the corresponding weights to generate the fitness value of the current parameter.

[0099] In one embodiment of the present invention, the fitness calculation subunit includes:

[0100] Where, is the weight of the i-th data point, is a robust kernel function;

[0101] Where, is the weight of the non-line-of-sight data point, is the heading angle corresponding to the current data point,

[0102] is the starting angle of the non-line-of-sight interval, is the end angle of the non-line-of-sight interval;

[0103] Where, is the deviation value, is the error threshold.

[0104] Reference Figure 11 , showing a computer device of a rotating single-station positioning method for a 5G-A industrial Internet environment of the present invention, which may specifically include the following: The computer device 12 is a general-purpose computing device. The components of the computer device 12 may include, but are not limited to, one or more processors or processing units 16, a system memory 28, and a bus 18 connecting different system components (including the system memory 28 and the processing unit 16).

[0105] The bus 18 represents one or more of several types of bus 18 structures, including a memory bus 18 or memory controller, a peripheral bus 18, an accelerated graphics port, a processor, or a local bus 18 that utilizes any of a variety of bus 18 architectures. Examples of such architectures include, but are not limited to, an Industry Standard Architecture (ISA) bus 18, a Micro Channel Architecture (MAC) bus 18, an Enhanced ISA bus 18, an Audio Video Electronics Standards Association (VESA) local bus 18, and a Peripheral Component Interconnect (PCI) bus 18.

[0106] The computer device 12 typically includes a variety of computer system readable media. These media can be any available media that can be accessed by the computer device 12, including volatile and non-volatile media, removable and non-removable media.

[0107] System memory 28 may include computer system readable media in the form of volatile memory, such as random access memory (RAM) 30 and / or cache memory 32. Computer device 12 may further include other removable / non-removable, volatile / non-volatile computer system storage media. By way of example only, storage system 34 may be configured to read from and write to non-removable, non-volatile magnetic media (commonly referred to as a "hard drive"). Although Figure 11 Although not shown, a magnetic disk drive for reading and writing to a removable non-volatile magnetic disk (e.g., a "floppy disk"), as well as an optical disk drive for reading and writing to a removable non-volatile optical disk (e.g., a CD-ROM, DVD-ROM, or other optical media) can be provided. In these cases, each drive can be connected to bus 18 via one or more data media interfaces. The memory may include at least one program product having a set (e.g., at least one) of program modules 42 configured to perform the functions of various embodiments of the present invention.

[0108] A program / utility 40 having a set (at least one) of program modules 42 may be stored, for example, in a memory. Such program modules 42 include, but are not limited to, an operating system, one or more application programs, other program modules 42, and program data. Each or some combination of these examples may include an implementation of a network environment. Program modules 42 generally perform the functions and / or methods of the embodiments described herein.

[0109] The computer device 12 may also communicate with one or more external devices 14 (e.g., a keyboard, a pointing device, a display 24, a camera, etc.), one or more devices that enable a user to interact with the computer device 12, and / or any device that enables the computer device 12 to communicate with one or more other computing devices (e.g., a network card, a modem, etc.). Such communication may occur through an input / output (I / O) interface 22. Furthermore, the computer device 12 may also communicate with one or more networks (e.g., a local area network (LAN)), a wide area network (WAN), and / or a public network (e.g., the Internet) through a network adapter 20. Figure 11 As shown, the network adapter 20 communicates with the other modules of the computer device 12 via the bus 18. Figure 11 Not shown, other hardware and / or software modules may be used in conjunction with the computer device 12, including but not limited to microcode, device drivers, redundant processing units 16, external disk drive arrays, RAID systems, tape drives, and data backup storage systems 34.

[0110] The processing unit 16 executes various functional applications and data processing by running programs stored in the system memory 28, such as implementing a rotating single-station positioning method for a 5G-A industrial Internet environment provided by an embodiment of the present invention.

[0111] That is, when the processing unit 16 executes the program, the following steps are implemented: obtaining the coordinates of the target base station, a heading angle sequence and a ranging sequence that are time-space synchronized during the rotation of the target object, and fitting the heading angle sequence and the ranging sequence to obtain a sinusoidal function curve that describes the variation of the ranging value with the heading angle; determining the orientation moment when the target object is facing the target base station based on the extreme points of the sinusoidal function curve; determining the target heading angle and target ranging value corresponding to the orientation moment based on the heading angle sequence and the ranging sequence, respectively; and determining the position coordinates of the target object based on the target heading angle, the target ranging value, and the target base station coordinates.

[0112] In an embodiment of the present invention, the present invention further provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements a rotating single-station positioning method for a 5G-A industrial Internet environment as provided in all embodiments of the present application: That is, when the program is executed by the processor, the following is achieved: obtaining the coordinates of the target base station, a heading angle sequence and a ranging sequence that are time-space synchronized during the rotation of the target object, and fitting the heading angle sequence and the ranging sequence to obtain a sinusoidal function curve for describing the variation of the ranging value with the heading angle; determining the orientation moment when the target object is facing the target base station based on the extreme points of the sinusoidal function curve; determining the target heading angle and target ranging value corresponding to the orientation moment based on the heading angle sequence and the ranging sequence, respectively; and determining the position coordinates of the target object based on the target heading angle, the target ranging value, and the target base station coordinates.

[0113] Any combination of one or more computer-readable media may be employed. A computer-readable medium may be a computer-readable signal medium or a computer-readable storage medium. A computer-readable storage medium may be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination thereof. More specific examples (a non-exhaustive list) of computer-readable storage media include: an electrical connection having one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination thereof. In this document, a computer-readable storage medium may be any tangible medium containing or storing a program for use by or in connection with an instruction execution system, apparatus, or device.

[0114] A computer-readable signal medium may include a data signal propagated in baseband or as part of a carrier wave, which carries computer-readable program code. Such a propagated data signal may take a variety of forms, including, but not limited to, electromagnetic signals, optical signals, or any suitable combination thereof. A computer-readable signal medium may also be any computer-readable medium other than a computer-readable storage medium that can transmit, propagate, or transport a program for use by or in conjunction with an instruction execution system, apparatus, or device.

[0115] The computer program code for performing the operations of the present invention can be written in one or more programming languages ​​or a combination thereof, including object-oriented programming languages ​​such as Java, Smalltalk, C++, and conventional procedural programming languages ​​such as "C" or similar programming languages. The program code can be executed entirely on the user's computer, partially on the user's computer, as a stand-alone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In the case of a remote computer, the remote computer can be connected to the user's computer via any type of network, including a local area network (LAN) or a wide area network (WAN), or can be connected to an external computer (for example, via the Internet using an Internet service provider). The various embodiments in this specification are described in a progressive manner, and each embodiment focuses on the differences from other embodiments. The same and similar parts between the various embodiments can be referenced.

[0116] Although preferred embodiments of the present invention have been described, those skilled in the art may make additional changes and modifications to these embodiments once they become aware of the basic inventive concepts. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments and all changes and modifications that fall within the scope of the embodiments of the present invention.

[0117] Finally, it should be noted that, in this document, relational terms such as first and second, etc., are used only to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any actual relationship or order between these entities or operations. Moreover, the terms "comprises," "comprising," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or terminal device that includes a series of elements includes not only those elements, but also other elements not explicitly listed, or elements inherent to such process, method, article, or terminal device. In the absence of further limitations, an element defined by the phrase "comprising a ..." does not exclude the presence of additional identical elements in the process, method, article, or terminal device that includes the element.

[0118] The above is a detailed introduction to the rotating single-station positioning method and device for the 5G-A industrial Internet environment provided by this application. This article uses specific examples to illustrate the principles and implementation methods of this application. The description of the above embodiments is only used to help understand the method of this application and its core idea; at the same time, for general technical personnel in this field, based on the ideas of this application, there will be changes in the specific implementation methods and application scope. In summary, the content of this specification should not be understood as a limitation on this application.

Claims

1. A rotating single-station positioning method for a 5G-A industrial Internet environment, which is used to locate a target object using a single base station. The target object carries an inertial measurement positioning terminal and an ultra-wideband tag device to perform in-situ rotational motion; characterized in that: The method comprises: Acquire the target base station coordinates, a heading angle sequence and a ranging sequence that are time-space synchronized during the rotation of the target object, and fit the heading angle sequence and the ranging sequence to obtain a sinusoidal function curve that describes the variation of the ranging value with the heading angle; Determining the orientation moment when the target object is facing the target base station according to the extreme point of the sine function curve; Determining a target heading angle and a target ranging value corresponding to the orientation moment according to the heading angle sequence and the ranging sequence respectively; The position coordinates of the target object are determined according to the target heading angle, the target ranging value, and the target base station coordinates.

2. The method according to claim 1, characterized in that The step of obtaining a temporally and spatially synchronized heading angle sequence and ranging sequence during the rotation of the target object comprises: Obtaining an IMU data sequence collected by the inertial measurement and positioning terminal, and solving the IMU data sequence to obtain a continuous heading angle sequence; The heading angle sequence and the distance measurement sequence are subjected to spatiotemporal synchronization processing.

3. The method according to claim 1, characterized in that The step of obtaining a temporally and spatially synchronized heading angle sequence and ranging sequence during the rotation of the target object comprises: Acquire two complete round-trip signal data between the ultra-wideband tag device and the target base station, and determine the one-way flight time of the signal between the ultra-wideband tag device and the target base station based on the two complete round-trip signal data; A relative distance between the ultra-wideband tag device and the target base station is generated according to the flight time and the speed of light.

4. The method according to claim 1, wherein The step of fitting the heading angle sequence and the ranging sequence to obtain a sinusoidal function curve describing how the ranging value varies with the heading angle comprises: Establishing an approximate sinusoidal model of the distance measurement value varying with the heading angle according to the distance measurement sequence and the heading angle sequence; The parameters of the approximate sinusoidal model are globally optimized, and when the convergence conditions are met, the optimal parameters and the corresponding sinusoidal function curve are output; wherein the parameters include the straight-line distance between the rotation center and the target base station, the rotation radius, and the orientation angle of the target object.

5. The method according to claim 4, characterized in that The step of globally optimizing the parameters of the approximate sine model and outputting the optimal parameters and the corresponding sine function curve when the convergence condition is met includes: Initializing parameters of the approximate sinusoidal model; Iterative optimization is performed based on dynamic adjustment of search weights to determine the fitness value of the current parameters in each iteration; When the fitness value reaches the convergence condition, the corresponding optimal parameters and the sine function curve are output.

6. The method according to claim 5, characterized in that The steps of performing iterative optimization based on dynamically adjusting the search weight and determining the fitness value of the current parameter in each iteration include: Determining the weight of a data point according to the heading angle corresponding to the data point in the ranging sequence; Determining a predicted distance value of the data point based on the current parameters and the approximate sine model; Determining a deviation between the predicted distance value and the measured distance value of the data point, and processing the deviation using a robust kernel function; The product of the processed deviations of all data points and the corresponding weights is accumulated and summed to generate the fitness value of the current parameter.

7. The method according to claim 6, characterized in that The calculation formula of the fitness is as follows: Where, is the weight of the i-th data point, is a robust kernel function; Where, is the weight of the non-line-of-sight data point, is the heading angle corresponding to the current data point, is the starting angle of the non-line-of-sight interval, is the end angle of the non-line-of-sight interval; Where, is the deviation value, is the error threshold.

8. A rotating single-station positioning device for a 5G-A industrial Internet environment, used to locate a target object using a single base station. The target object carries an inertial measurement positioning terminal and an ultra-wideband tag device to perform in-situ rotational motion; characterized in that: The device comprises: a curve fitting module, configured to obtain the coordinates of the target base station, a heading angle sequence and a ranging sequence that are synchronized in time and space during the rotation of the target object, and to fit the heading angle sequence and the ranging sequence to obtain a sinusoidal function curve that describes how the ranging value changes with the heading angle; a time determination module, configured to determine the orientation time when the target object is facing the target base station according to the extreme value point of the sine function curve; a data determination module, configured to determine a target heading angle and a target ranging value corresponding to the orientation moment according to the heading angle sequence and the ranging sequence respectively; A position calculation module is used to determine the position coordinates of the target object according to the target heading angle, the target ranging value and the target base station coordinates.

9. A computer electronic device, characterized in that: The method comprises a processor, a memory, and a computer program stored in the memory and capable of running on the processor, wherein the computer program implements the method according to any one of claims 1 to 7 when executed by the processor.

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

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