A distributed beacon-based sports ball positioning system and method

Abstract

This invention relates to the field of beacon positioning technology, and more particularly to a moving ball positioning system and method based on distributed beacons. The system includes N distributed beacons deployed at known locations on a sports field; a mobile base station that receives wireless signals from the distributed beacons, converts them into ranging information, and constructs an N-ary distance equation system. The position of the mobile base station in the sports field coordinate system is obtained through analytical solution, completing self-calibration; an inertial measurement unit (IMU) is installed inside the moving ball, collecting motion data of the ball via event triggering and sending the data packets to the mobile base station; the mobile base station, based on the self-calibrated distributed beacons, acquires the ball position keyframes corresponding to the data packets, and generates continuous motion trajectories based on each ball position keyframe. This invention achieves a balance between rapid deployment, automatic calibration, high-precision positioning, and trajectory reconstruction with minimal data volume in the moving ball positioning system, adapting to various application scenarios and improving the system's versatility and practicality.

Description

Technical Field

[0001] This invention relates to the field of beacon positioning technology, and in particular to a moving ball positioning system and method based on distributed beacons. Background Technology

[0002] In fields such as sports training, event analysis, and sports science research, the positioning and trajectory reconstruction of ball sports are core technological requirements. Their accuracy and ease of deployment directly impact the accuracy of training effectiveness evaluation, event data statistics, and motion pattern analysis. Currently, ball sports positioning systems have become a research hotspot in related fields, with various positioning technologies and system solutions constantly emerging.

[0003] In existing technologies, there are two main types of positioning systems for sports balls. One type is based on fixed base stations. These systems typically require multiple base stations to be fixedly installed at predetermined locations on the sports field. Positioning is achieved by the base stations receiving signals carried by the ball. The positioning accuracy depends on the accuracy of the base station deployment. However, the fixed deployment process is cumbersome, requiring professional on-site installation and debugging, and cannot meet the needs of rapid switching and deployment across different sports fields. The other type is a positioning system combined with inertial measurement units (IMUs). This type of system collects motion data by placing an IMU inside the ball and then uses it in conjunction with base stations to reconstruct the trajectory. However, this type of system often requires manual calibration of the base station positions, a time-consuming and labor-intensive process. Furthermore, some systems need to continuously transmit large amounts of motion data to ensure the quality of trajectory reconstruction, resulting in significant data transmission pressure and making it difficult to ensure optimal trajectory reconstruction quality while reducing data transmission volume.

[0004] Furthermore, existing positioning systems struggle to balance deployment flexibility, calibration efficiency, and trajectory reconstruction quality. They either lack ease of deployment or require a large amount of data to achieve the desired positioning and trajectory reconstruction results, failing to meet the core requirements of rapid deployment, automatic calibration, high-precision positioning, and trajectory reconstruction with minimal data volume. Summary of the Invention

[0005] This invention provides a ball positioning system and method based on distributed beacons, which can effectively solve the problems in the background art.

[0006] To achieve the above objectives, the technical solution adopted by the present invention is as follows: A ball positioning system based on distributed beacons, comprising: N movable distributed beacons, N≥2, are deployed at known locations on the sports field; The mobile base station receives the wireless signal from the distributed beacon and converts it into ranging information. The ranging information is used to characterize the distance between the distributed beacon and the mobile base station. The mobile base station constructs an N-ary distance equation system based on the ranging information and obtains the position of the mobile base station in the coordinate system of the sports field by analytical solution, thus completing self-calibration. An inertial measurement unit is installed inside a ball to collect motion data of the ball in an event-triggered manner, and sends a data packet including the event type, trigger time and the corresponding motion data to the mobile base station. The mobile base station acquires the ball position keyframes corresponding to the data packets based on the self-calibrated distributed beacons, and generates continuous motion trajectories based on each ball position keyframe.

[0007] Furthermore, the events include a hitting event, a highest point event, and a landing event, each of which corresponds to a keyframe of the ball's position; The mobile base station generates the continuous motion trajectory between adjacent events based on the parabolic physical model between adjacent ball position keyframes.

[0008] Furthermore, the triggering condition for the ball-hitting event is: The acceleration modulus output by the inertial measurement unit exceeds a first preset threshold, and the duration for which the acceleration modulus exceeds the first preset threshold is less than a preset time threshold. The first preset threshold and the preset time threshold are preset according to the motion characteristics of the ball game.

[0009] Furthermore, the triggering condition for the highest point event is: The velocity output by the inertial measurement unit along the Z-axis of the coordinate system of the sports field crosses zero.

[0010] Furthermore, the triggering condition for the landing event is: The acceleration magnitude output by the inertial measurement unit exceeds the second preset threshold. The second preset threshold is preset based on the motion characteristics of the ball game.

[0011] Furthermore, the triggering condition for the landing event also includes an auxiliary verification condition, wherein the auxiliary verification condition is that the height of the ball is less than a preset height, or the triggering time of the landing event falls within a preset time range; The height of the ball is estimated by the mobile base station based on the self-calibrated distributed beacon, the ranging information, and the motion data in the data packet; the preset height and the preset time range are preset according to the motion characteristics of the ball.

[0012] Furthermore, the wireless signal of the distributed beacon broadcast is a Bluetooth Low Energy signal; The mobile base station receives and measures the strength of the Bluetooth Low Energy signal, and converts the strength of the Bluetooth Low Energy signal into the ranging information.

[0013] Furthermore, the wireless signal of the distributed beacon broadcast is an ultra-wideband signal; The mobile base station receives and measures the arrival time or time difference of the ultra-wideband signal, and converts the arrival time or time difference of arrival into the ranging information.

[0014] Furthermore, it also includes a gyroscope, which is disposed inside the moving ball and works in conjunction with the inertial measurement unit; The gyroscope collects the angular velocity data of the moving ball in an event-triggered manner and sends the angular velocity data to the mobile base station; The mobile base station receives the angular velocity data and, in conjunction with the parabolic physical characteristics of the motion trajectory, corrects the motion trajectory by compensating for the rotational offset of the moving ball.

[0015] A method for locating a moving ball based on distributed beacons includes: Deploy N movable distributed beacons, where N≥2, and place each distributed beacon at a known location on the sports field, and control the distributed beacons to continuously broadcast signals; The signal is received by a mobile base station and converted into ranging information, which is used to characterize the distance between the distributed beacon and the mobile base station. Based on the ranging information, an N-ary distance equation system is constructed, and the position of the mobile base station in the coordinate system of the sports field is obtained by analytical solution, thus completing the self-calibration of the mobile base station. An inertial measurement unit installed inside a ball is used to collect motion data of the ball in an event-triggered manner, and a data packet including the event type, trigger time, and corresponding motion data is sent to the mobile base station. The mobile base station acquires the ball position keyframes corresponding to the data packets based on the self-calibrated distributed beacons, and generates continuous motion trajectories based on each ball position keyframe.

[0016] The technical solution of this invention can achieve the following technical effects: This invention, through the combined technical features and logic of mobile distributed beacons, automatic self-calibration of mobile base stations, event-triggered motion data acquisition, and keyframe trajectory generation, completely solves the technical problems of cumbersome deployment, time-consuming calibration, high data transmission pressure, and inability to balance data volume and trajectory reconstruction quality in existing technologies. It achieves a balance between rapid deployment, automatic calibration, high-precision positioning, and trajectory reconstruction with minimal data volume in sports ball positioning systems. It can be widely adapted to various ball sports such as tennis, badminton, table tennis, and baseball for training analysis, event data statistics, and sports law research, thereby improving the system's universality and practicality. Attached Figure Description

[0017] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments recorded in the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0018] Figure 1 This is a schematic diagram illustrating the application of a ball positioning system based on distributed beacons. Figure 2 This is a framework diagram of a ball positioning system based on distributed beacons. Figure 3 This is a schematic diagram illustrating how the motion trajectory is generated. Figure label: 1. Sports field; 2. Distributed beacon; 3. Mobile base station; 4. Inertial measurement unit. Detailed Implementation

[0019] The technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments.

[0020] Example 1 A ball positioning system based on distributed beacons, such as Figure 1 and 2 As shown, it includes: N movable distributed beacons 2, where N≥2, are deployed at known locations on the sports field 1. In this embodiment, the distributed beacons 2 do not require fixed installation or on-site debugging by professional personnel. They can adapt to the rapid switching and deployment needs of different sports fields 1, solving the defects of existing fixed base station positioning systems, such as cumbersome deployment process and poor site adaptability. As a specific implementation method, four distributed beacons 2 are exemplarily arranged at the four corners of the sports field 1 in the figure. Of course, this number is not a limitation on the scope of protection.

[0021] Mobile base station 3 receives the wireless signal from distributed beacon 2 and converts it into ranging information. The ranging information is used to characterize the distance between distributed beacon 2 and mobile base station 3. Based on the ranging information, mobile base station 3 constructs a set of N-ary distance equations and solves them analytically to obtain the position of mobile base station 3 in the coordinate system of sports field 1, thus completing self-calibration. In some embodiments of the present invention, the preferred hardware implementation of the mobile base station 3 is a common commercial smartphone; as a better option, it can be equipped with iOS 12+, Android 8+ and above operating systems; this form of mobile base station 3 does not require customized hardware development, and the built-in Bluetooth communication module, processor and storage unit of the mobile phone can meet all the functional requirements of the system, further reducing the system deployment cost and the threshold for use. In other alternative implementations, the mobile base station 3 can also be a mobile terminal device with wireless signal reception and data computing capabilities, such as a tablet computer or a portable industrial computer, whose core functional implementation logic is completely consistent with that of a smartphone.

[0022] It also includes an inertial measurement unit 4, which is installed inside the ball and collects the ball's motion data in an event-triggered manner, and sends a data packet including the event type, trigger time and corresponding motion data to the mobile base station 3. Specifically, in the implementation process, the inertial measurement unit 4 only collects and transmits data when the event is triggered, avoiding the problem of excessive transmission pressure caused by continuously collecting and transmitting a large amount of motion data.

[0023] Based on the self-calibrated distributed beacon 2, mobile base station 3 obtains the ball position key frames corresponding to the data packets, and generates continuous motion trajectories based on each ball position key frame. This compresses the amount of data transmission while ensuring the accuracy of motion trajectory reconstruction, thus solving the core defect of existing systems that are difficult to ensure optimal trajectory reconstruction quality while reducing the amount of data transmission.

[0024] In this invention, the mobile base station 3 constructs an N-variable distance equation system based on the known locations of N distributed beacons 2. Taking the deployment of four distributed beacons 2 in the sports field 1 as an example, a corresponding four-variable distance equation system is obtained. The solution to this four-variable distance equation system can be obtained analytically using a conventional difference elimination linearization method, yielding the three-dimensional coordinates of the mobile base station 3 in the coordinate system of the sports field 1. This completes self-calibration and provides a unified coordinate reference for subsequent ball position calculations.

[0025] The above analytical solution process is existing technology and will not be repeated here. The above analytical solution can also be applied to the case of N≥4. However, when N=2 or 3, further constraints are required. For example, when N=2, the height of mobile base station 3 is known; when N=3, mobile base station 3 is located on the site plane.

[0026] Based on the above implementation method, the mobile base station 3 does not need to send control commands to the distributed beacon 2. It can complete ranging and self-calibration by simply receiving broadcast wireless signals, which simplifies the deployment process. The mobile base station 3 is the receiver of data packets for the inertial measurement unit 4. The two realize bidirectional communication. The mobile base station 3 can send configuration commands such as sampling rate adjustment and event trigger threshold adjustment to the inertial measurement unit 4 according to the self-calibration status and trajectory generation requirements, so as to realize the dynamic adaptation of the system.

[0027] In this invention, the ball sports referred to include, but are not limited to, tennis, badminton, table tennis, and baseball. This invention, through the combined technical features and logic of a mobile distributed beacon 2, a mobile base station 3 for automatic self-calibration, event-triggered motion data acquisition, and keyframe trajectory generation, completely solves the technical problems of cumbersome deployment, time-consuming calibration, high data transmission pressure, and the inability to balance data volume and trajectory reconstruction quality in existing technologies. It achieves a balance between rapid deployment, automatic calibration, high-precision positioning, and trajectory reconstruction with minimal data volume in the ball sports positioning system. It is widely adaptable to application scenarios such as training analysis, event data statistics, and sports pattern research in various ball sports such as tennis, badminton, table tennis, and baseball, improving the system's universality and practicality.

[0028] As a preferred embodiment of the above, such as Figure 3 As shown, the events include the hitting event, the highest point event, and the landing event, with each event corresponding to a keyframe of the ball's position. The mobile base station generates continuous motion trajectories between adjacent events based on the parabolic physical model between adjacent ball position keyframes.

[0029] In this preferred embodiment, the ball position keyframe serves as the reference node for generating continuous motion trajectories. In some embodiments of the invention, each ball position keyframe includes standardized fields: an event type identifier, a trigger timestamp, and three-dimensional spatial coordinates in the sports field coordinate system as motion data, along with corresponding motion state parameters at that moment, ensuring parameter consistency throughout the trajectory generation process. Specifically, the correspondence is as follows: the ball-hitting keyframe generated after a hitting event is the starting reference frame for a single hitting trajectory; the highest point keyframe generated after a highest point event is the vertex reference frame for the parabolic trajectory, serving as the reversal node for the vertical movement of the ball; and the landing keyframe generated after a landing event is the ending reference frame for a single hitting trajectory. The mobile base station sorts the ball position keyframes corresponding to the three types of events according to their trigger times, forming an ordered keyframe sequence.

[0030] After the mobile base station completes the construction of the ordered keyframe sequence, based on the three spatial coordinate points corresponding to the hitting keyframe, the highest point keyframe, and the landing keyframe, it uses the spatial analytical geometry principle of determining a unique parabola through three points, combined with the projectile motion law of moving balls, to generate the continuous motion trajectory of a single hitting process. In some embodiments of the present invention, the specific implementation process is as follows: A1: Determine the flight plane. The mobile base station extracts the three-dimensional spatial coordinates P1(x1,y1,z1) corresponding to the hitting keyframe, the three-dimensional spatial coordinates P2(x2,y2,z2) corresponding to the highest point keyframe, and the three-dimensional spatial coordinates P3(x3,y3,z3) corresponding to the landing keyframe. Based on these three non-collinear spatial coordinate points, the spatial plane in which the ball is located during its flight phase is uniquely determined, thus locking the spatial distribution range of the trajectory. Among these, P1, P2, and P3 are non-collinear, eliminating any ambiguity in the trajectory solution.

[0031] A2: Construct the parabolic equation. Within the defined space flight plane, using the keyframe P1 (the point of impact) as the trajectory starting point, the keyframe P2 (the highest point) as the parabola vertex, and the keyframe P3 (the landing point) as the trajectory ending point, a standard parabolic physical model is constructed by combining the classic projectile motion laws. Among them, P2, as the vertex of the parabola, satisfies the motion characteristic of zero velocity in the vertical direction, which can directly lock the opening direction and extreme point of the parabola, and a unique parabolic equation can be obtained without additional iterative fitting.

[0032] In this embodiment, only three keyframes of the ball's position triggered by events are needed to uniquely determine and generate a complete motion trajectory. There is no need to continuously collect and transmit a large amount of continuous motion data. While minimizing the amount of data transmission, the smoothness of the trajectory and the accuracy of reconstruction are guaranteed. The calculation logic is simple and the amount of computation is extremely low. It can be executed stably and quickly on mobile terminal devices with low computing power, which fully meets the core requirements of the present invention for rapid deployment and lightweight implementation.

[0033] In optional implementations, mobile base stations can select multiple methods to complete trajectory adaptation processing based on the actual application needs of visualization display and trajectory data analysis, thereby meeting the usage requirements of different downstream scenarios: As an optional approach, the mobile base station, based on the aforementioned determined parabolic equation, can perform equal-interval time interpolation within the trigger time interval between the keyframe of the ball's impact and the keyframe of its landing, according to a preset time interpolation interval. This allows for the calculation of the three-dimensional spatial coordinates of the moving ball in the sports field coordinate system at each interpolation moment, generating a sequence of discrete trajectory points with equal time intervals. This method provides a concrete implementation for refined trajectory visualization and data analysis, suitable for scenarios such as frame-by-frame playback of matches, annotation of key points in the trajectory, and refined statistics of ball-hitting parameters. It can directly calculate and visualize derived data such as instantaneous velocity, flight duration, and landing deviation based on discrete trajectory points without requiring additional coordinate transformation processing.

[0034] As an alternative approach, the mobile base station directly renders and generates a continuous and smooth parabolic trajectory from the keyframe of the shot to the keyframe of the landing, based on the uniquely determined parabolic equation mentioned above, within the visualization interface corresponding to the sports field coordinate system. This is done without the need for time interpolation or discrete point calculations. This method is a specific implementation of lightweight continuous trajectory visualization, suitable for scenarios such as fast preview of sports trajectories, real-time trajectory display on low-computing-power mobile terminals, and lightweight display of daily training data. Relying on the continuous differentiability of the standard parabolic equation, the rendered trajectory is smooth without jagged edges or inflection points, exhibiting absolute smoothness. At the same time, the computational load is extremely low, enabling millisecond-level trajectory rendering and display on various mobile terminal devices.

[0035] Of course, the above options are only some of the feasible methods and are not intended to limit the scope of protection.

[0036] As a preferred embodiment of the above, the triggering condition for the ball-hitting event is: the acceleration modulus value output by the inertial measurement unit exceeds a first preset threshold, and the duration of the acceleration modulus value exceeding the first preset threshold is less than a preset time threshold; the first preset threshold and the preset time threshold are preset according to the motion characteristics of the ball.

[0037] In this preferred embodiment, the ball-hitting event is triggered and determined by the inertial measurement unit based on the acceleration signal. The first preset threshold and the preset time threshold are specifically preset according to the impact intensity, movement speed and other motion characteristics of different sports balls such as tennis, badminton and table tennis, so as to ensure the accuracy of the detection at the moment of hitting the ball and avoid false triggering caused by normal movement vibration. In this preferred embodiment, the inertial measurement unit can specifically adopt a three-axis MEMS accelerometer, so as to output the three-axis acceleration data of the ball in three-dimensional space in real time and calculate the acceleration magnitude. Through the determination of dual conditions, the instantaneous high impact signal generated at the moment of hitting the ball can be accurately identified, thereby improving the reliability of event detection.

[0038] As a preferred embodiment of the above, the triggering condition for the highest point event is: the velocity output by the inertial measurement unit along the Z-axis of the motion field coordinate system crosses zero.

[0039] In this preferred embodiment, the highest point event is determined based on the vertical motion state of the ball. The inertial measurement unit can also be a three-axis MEMS accelerometer. By integrating the acceleration along the Z-axis of the coordinate system of the sports field, the real-time velocity in the Z-axis direction is obtained. The highest point corresponds to the reversal point where the ball's rising phase ends and the falling phase begins. This is consistent with the physical laws of projectile motion and can accurately identify the position of the highest point of the trajectory, providing a key vertex reference for the subsequent construction of the parabolic trajectory.

[0040] As a preferred embodiment of the above, the triggering condition for the landing event is: the acceleration modulus output by the inertial measurement unit exceeds a second preset threshold; the second preset threshold is preset according to the motion characteristics of the ball.

[0041] In this preferred embodiment, the landing event is triggered by acceleration impact characteristics; the inertial measurement unit can also be a three-axis MEMS accelerometer, which has high range and high impact resistance, and can accurately collect the impact acceleration signal at the moment of contact with the ground; the second preset threshold is specifically preset according to the impact size of different sports balls, the hardness of the field and other motion characteristics, so as to accurately identify the impact signal generated when the sports ball contacts the field, and realize the real-time triggering of the landing event.

[0042] In some embodiments of the present invention, to further improve the detection accuracy of landing events and avoid false alarms and mis-triggers, in addition to the acceleration modulus determination, the triggering condition for the landing event also includes auxiliary verification conditions. The auxiliary verification conditions are that the height of the moving ball is less than a preset height, or the triggering time is within a preset time range. The height of the moving ball is estimated by the mobile base station based on the motion data in the self-calibrated distributed beacon, ranging information, and data packets. The preset height and preset time range are preset according to the motion characteristics of the moving ball. In this preferred embodiment, the motion characteristics include the flight trajectory and flight duration of different moving balls.

[0043] During implementation, by combining acceleration impact with altitude and time conditions for verification, the detection accuracy of landing events can be significantly improved, eliminating the uncertainty of single sensor triggering.

[0044] As a specific implementation example, after the mobile base station completes self-calibration, it has determined its three-dimensional coordinates in the sports field coordinate system. The mobile base station can obtain the preliminary absolute three-dimensional position of the sports ball in the sports field coordinate system through wireless positioning calculation based on the known coordinates of the distributed beacons and the real-time ranging information between the sports ball and each distributed beacon. The vertical height component in the preliminary absolute three-dimensional position can be directly extracted to participate in subsequent auxiliary verification and judgment.

[0045] However, in order to obtain higher accuracy, the mobile base station performs integral calculations based on the triaxial acceleration data collected by the inertial measurement unit in the data packet to obtain the real-time relative displacement of the moving ball, and then fuses and corrects the real-time relative displacement with the preliminary absolute three-dimensional position to finally obtain a more accurate vertical height value of the moving ball relative to the plane of the sports field.

[0046] In the above embodiments, the trigger time corresponding to the landing event refers to the current time point at which the landing event is detected and triggered; the preset time range is a reasonable landing time interval estimated based on the normal flight law of the ball, the time of the hitting event, and the trajectory of the projectile. Only when the trigger time of the landing event falls within this preset time range is the auxiliary verification condition met, so as to exclude the impact false triggering of unreasonable landing times and further improve the reliability of landing event detection.

[0047] As a preferred embodiment of the above, the wireless signal for distributed beacon broadcasting is a Bluetooth Low Energy (BLE) signal; the mobile base station receives and measures the strength of the BLE signal and converts the strength of the BLE signal into ranging information. BLE signals are characterized by low power consumption, low hardware cost, strong adaptability, and convenient deployment, which can meet the requirements of this system for rapid deployment, lightweight operation, and long-term stable operation.

[0048] As a further optimization scheme, the mobile base station combines the conversion of ranging information with the path loss index n. The path loss index n is estimated online by the mobile base station through geometric consistency verification, and the value range of the path loss index n is 1.5 ≤ n ≤ 4.0. The path loss index n is used to adapt to the signal propagation attenuation characteristics under different deployment environments. Through online adaptive estimation and correction, the impact of environmental changes on ranging accuracy can be effectively reduced, and the stability and accuracy of mobile base station self-calibration can be improved.

[0049] As a specific implementation example, the online estimation steps for the path loss exponent n are as follows: S1: Obtain the known locations of distributed beacons pre-deployed on the sports field, where the actual geometric distance between any two distributed beacons is a fixed known value; S2: The mobile base station converts the received signal strength into multiple sets of corresponding ranging results based on different path loss indices n; S3: The mobile base station converts each set of ranging results into an estimated distance between distributed beacons; S4: The mobile base station aims to minimize the sum of squared deviations between the estimated distance and the actual geometric distance, and iterates through the search to obtain the optimal path loss exponent n.

[0050] In the above exemplary methods, the actual distance between beacons is fixed and noise-free, unaffected by wireless signal fluctuations, and can accurately identify environmental changes. The mobile base station can simultaneously estimate the path loss index n during the self-calibration process without adding operation steps or increasing costs. It can be adapted to various deployment environments such as open outdoor areas, indoor venues, and semi-obstructed areas, and automatically matches the optimal path loss index n, significantly improving ranging accuracy and self-calibration precision.

[0051] As a preferred embodiment of the above, the mobile base station maintains a state history buffer to store the filtering state information within the most recent time window. When the mobile base station receives observation data with transmission delay, it performs a lag update on the delayed observation data based on the state history buffer and propagates the correction amount forward to the current time to compensate for the impact of data delay on positioning results and trajectory estimation, thereby improving the positioning continuity and accuracy of the system in asynchronous transmission scenarios.

[0052] In another implementation, the signal broadcast by the distributed beacon is an ultra-wideband signal; the mobile base station receives and measures the arrival time or time difference of the ultra-wideband signal, and converts the arrival time or time difference of arrival into ranging information.

[0053] As a further optimization, the mobile base station combines the ranging information conversion with clock offset compensation parameters. Specifically, the clock offset compensation parameters are obtained online by the mobile base station based on ultra-wideband synchronization timing and multi-beacon geometric consistency checks, and the specific steps are as follows: D1: Obtain the known locations of distributed beacons on the sports field, with the true geometric distance between any two distributed beacons being a fixed known true value; D2: The mobile base station measures the arrival time or time difference of each beacon based on the ultra-wideband signal, and performs timing correction by combining different clock offset compensation parameters to obtain multiple sets of corrected ranging results. D3: The mobile base station converts each set of calibrated ranging results into an estimated distance between distributed beacons; D4: The mobile base station aims to minimize the sum of squared deviations between the estimated distance and the actual geometric distance. It then iterates through the search to obtain the optimal clock offset compensation parameters under the current environment, thus completing the online estimation.

[0054] The clock offset compensation parameters estimated through the above steps can effectively compensate for ranging deviations caused by ultra-wideband hardware clock differences, signal transmission delays, and timing drift, thereby improving ranging stability and positioning accuracy. This implementation method can improve positioning accuracy and is suitable for scenarios with higher positioning accuracy requirements, but the hardware cost increases accordingly.

[0055] In the above embodiments, during the process of determining the flight plane using the three-dimensional spatial coordinates P1(x1,y1,z1) corresponding to the hitting keyframe, the three-dimensional spatial coordinates P2(x2,y2,z2) corresponding to the highest point keyframe, and the three-dimensional spatial coordinates P3(x3,y3,z3) corresponding to the landing keyframe, the measured three-dimensional coordinate points P1, P2, and P3 corresponding to the three keyframes of hitting, highest point, and landing may have slight coplanar deviations due to factors such as Magnus aerodynamic lateral offset caused by the high-speed rotation of the ball, measurement noise of the inertial measurement unit, and coordinate errors of the mobile base station self-calibration. These points cannot strictly fall within the same spatial plane, thus affecting the uniqueness and reconstruction accuracy of the parabolic trajectory.

[0056] To address this issue, as a preferred approach, a gyroscope is also included, which is installed inside the moving ball and works in conjunction with the inertial measurement unit. The gyroscope collects the angular velocity data of the moving ball in an event-triggered manner and sends the angular velocity data to the mobile base station. The mobile base station receives the angular velocity data and, combined with the parabolic physical characteristics of the motion trajectory, corrects the motion trajectory by compensating for the rotational offset of the moving ball.

[0057] In this preferred embodiment, after receiving angular velocity data, the mobile base station combines the inherent parabolic physical characteristics of the motion trajectory, calculates the rotation state of the ball during flight based on the angular velocity data, determines the lateral offset of the ball's rotation caused by the Magnus effect, and compensates and corrects the coordinates of the three key frames based on this offset so that the three points return to coplanarity.

[0058] In the implementation process, as a specific correction method, the steps include: B1: Based on the three-axis angular velocity data collected by the gyroscope, the mobile base station calculates the rotation direction, rotation rate, and rotation attitude of the moving ball during flight. Combining the size, mass, and aerodynamic parameters of the moving ball, it calculates the lateral force generated by the Magnus effect and further obtains the cumulative lateral offset vector throughout the flight. B2: The mobile base station applies the cumulative lateral offset vector in reverse to the measured three-dimensional coordinates of the key frame of the hit, the key frame of the highest point, and the key frame of the landing, to compensate for the spatial position of each point, eliminate the position offset caused by rotation, and obtain three sets of standard coordinates after compensation. Since rotational offset is the main factor causing the three points to be non-coplanar, the three sets of coordinates after compensation can be returned to the same spatial plane corresponding to the ideal projectile motion, thus achieving strict coplanarity of the three points.

[0059] B3: Based on the three standard coordinates that are coplanar after compensation, the mobile base station constructs a standard parabolic physical model according to the principle that three points determine a unique parabola, and generates a smooth, continuous and unbiased motion trajectory.

[0060] Of course, in other embodiments of the present invention, without adding a gyroscope, a lightweight and low-computing-power least-squares optimal fitting plane method can also be used to eliminate coplanar deviation. Specific steps include: C1: The mobile base station extracts the three-dimensional spatial coordinates P1(x1,y1,z1), P2(x2,y2,z2), and P3(x3,y3,z3) corresponding to the key frame of hitting the ball, the key frame of the highest point, and the key frame of landing. Using the coordinates of the three key frames as input, the least squares method is used to fit the optimal spatial plane, so as to minimize the sum of the squares of the vertical distances from the three key frames to the optimal plane, thereby eliminating the coplanar deviation. C2: The mobile base station projects the measured 3D coordinates of the three key frames vertically onto the optimal spatial plane to obtain three sets of strictly coplanar standard coordinates P1'(x1',y1',z1'), P2'(x2',y2',z2'), and P3'(x3',y3',z3') after projection, so that the three key frames satisfy the coplanar condition required for projectile motion; C3: Based on three sets of standard coordinates after projection and coplanarity, the mobile base station constructs a standard parabolic physical model according to the principle that three points determine a unique parabola, generates a smooth, continuous, and unbiased motion trajectory, and completes trajectory correction.

[0061] Example 2 A method for locating a moving ball based on distributed beacons includes: Deploy N movable distributed beacons, where N≥2, place the N distributed beacons at known locations on the sports field, and control the distributed beacons to continuously broadcast signals; The mobile base station receives signals and converts them into ranging information, which is used to characterize the distance between the distributed beacon and the mobile base station. Based on the ranging information, an N-ary distance equation system is constructed, and the position of the mobile base station in the coordinate system of the sports field is obtained by analytical solution, thus completing the self-calibration of the mobile base station. The motion data of the ball is collected by an inertial measurement unit installed inside the ball in an event-triggered manner, and the data packet including the event type, trigger time and corresponding motion data is sent to the mobile base station. The mobile base station acquires the ball position keyframes corresponding to the data packets based on the self-calibrated distributed beacons, and generates continuous motion trajectories based on each ball position keyframe.

[0062] The technical effects achieved in this embodiment are the same as those in Embodiment 1 above, and will not be repeated here.

[0063] After the ball is equipped with an inertial measurement unit, it is used as a smart ball. In actual use, there may be M smart balls involved, where M≥1.

[0064] Specifically, when M ≥ 2, meaning multiple smart spheres are operating simultaneously, to avoid mutual interference between their wireless signals and to ensure the stability and accuracy of wireless channel transmission, the multiple smart spheres preferably share the wireless channel using time-division multiplexing. Preferably, the time slot allocation for time-division multiplexing is based on one of the following two feasible algorithms: First, there is the MAC address hashing algorithm, which uses hashing to assign a unique and fixed communication time slot to each smart ball, thus achieving orderly allocation of time slots. Second, there is the random backoff algorithm, which uses random backoff time to compete for communication time slots when multiple smart balls detect that the channel is idle, thus avoiding time slot conflicts.

[0065] The mobile base station identifies the time slot identifier carried in the data transmitted by each smart ball, distinguishes the communication time slots and corresponding data of different smart balls, thereby realizing the simultaneous positioning, event detection and trajectory reconstruction of multiple smart balls, ensuring the stability and positioning accuracy of the system when multiple balls work together.

[0066] Those skilled in the art should understand that this invention is not limited to the above embodiments. The embodiments and descriptions in the specification are merely illustrative of the principles of the invention. Various changes and modifications can be made to this invention without departing from its spirit and scope, and all such changes and modifications fall within the scope of the invention as claimed. The scope of protection of this invention is defined by the appended claims and their equivalents.

Claims

1. A ball positioning system based on distributed beacons, characterized in that... ,include: N movable distributed beacons, N≥2, are deployed at known locations on the sports field; The mobile base station receives the wireless signal from the distributed beacon and converts it into ranging information. The ranging information is used to characterize the distance between the distributed beacon and the mobile base station. The mobile base station constructs an N-ary distance equation system based on the ranging information and obtains the position of the mobile base station in the coordinate system of the sports field by analytical solution, thus completing self-calibration. An inertial measurement unit is installed inside a ball to collect motion data of the ball in an event-triggered manner, and sends a data packet including the event type, trigger time and the corresponding motion data to the mobile base station. The mobile base station acquires the ball position keyframes corresponding to the data packets based on the self-calibrated distributed beacons, and generates continuous motion trajectories based on each ball position keyframe.

2. The ball positioning system based on distributed beacons according to claim 1, characterized in that, The events include the ball-hitting event, the highest point event, and the landing event, and each of the events corresponds to a keyframe of the ball's position. The mobile base station generates the continuous motion trajectory between adjacent events based on the parabolic physical model between adjacent ball position keyframes.

3. The ball positioning system based on distributed beacons according to claim 2, characterized in that, The triggering condition for the ball-hitting event is: The acceleration modulus output by the inertial measurement unit exceeds a first preset threshold, and the duration for which the acceleration modulus exceeds the first preset threshold is less than a preset time threshold. The first preset threshold and the preset time threshold are preset according to the motion characteristics of the ball game.

4. The ball positioning system based on distributed beacons according to claim 2, characterized in that, The triggering condition for the highest point event is: The velocity output by the inertial measurement unit along the Z-axis of the coordinate system of the sports field crosses zero.

5. The ball positioning system based on distributed beacons according to claim 2, characterized in that, The triggering condition for the landing event is: The acceleration magnitude output by the inertial measurement unit exceeds the second preset threshold. The second preset threshold is preset based on the motion characteristics of the ball game.

6. The ball positioning system based on distributed beacons according to claim 5, characterized in that, The triggering conditions for the landing event also include auxiliary verification conditions, wherein the auxiliary verification conditions are that the height of the ball is less than a preset height, or that the triggering time of the landing event falls within a preset time range; The height of the ball is estimated by the mobile base station based on the self-calibrated distributed beacon, the ranging information, and the motion data in the data packet; the preset height and the preset time range are preset according to the motion characteristics of the ball.

7. The ball positioning system based on distributed beacons according to claim 1, characterized in that, The wireless signal used for the distributed beacon broadcast is a Bluetooth Low Energy signal; The mobile base station receives and measures the strength of the Bluetooth Low Energy signal, and converts the strength of the Bluetooth Low Energy signal into the ranging information.

8. The ball positioning system based on distributed beacons according to claim 1, characterized in that, The wireless signal used in the distributed beacon broadcast is an ultra-wideband signal; The mobile base station receives and measures the arrival time or time difference of the ultra-wideband signal, and converts the arrival time or time difference of arrival into the ranging information.

9. The ball positioning system based on distributed beacons according to claim 1, characterized in that, It also includes a gyroscope, which is located inside the moving ball and works in conjunction with the inertial measurement unit; The gyroscope collects the angular velocity data of the moving ball in an event-triggered manner and sends the angular velocity data to the mobile base station; The mobile base station receives the angular velocity data and, in conjunction with the parabolic physical characteristics of the motion trajectory, corrects the motion trajectory by compensating for the rotational offset of the moving ball.

10. A method for locating a moving ball based on distributed beacons, characterized in that, include: Deploy N movable distributed beacons, where N≥2, and place each distributed beacon at a known location on the sports field, and control the distributed beacons to continuously broadcast signals; The signal is received by a mobile base station and converted into ranging information, which is used to characterize the distance between the distributed beacon and the mobile base station. Based on the ranging information, an N-ary distance equation system is constructed, and the position of the mobile base station in the coordinate system of the sports field is obtained by analytical solution, thus completing the self-calibration of the mobile base station. An inertial measurement unit installed inside a ball is used to collect motion data of the ball in an event-triggered manner, and a data packet including the event type, trigger time, and corresponding motion data is sent to the mobile base station. The mobile base station acquires the ball position keyframes corresponding to the data packets based on the self-calibrated distributed beacons, and generates continuous motion trajectories based on each ball position keyframe.

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