Low-altitude target monitoring, positioning and tracking method and system based on civil network

Abstract

The invention provides a low-altitude target monitoring, positioning and tracking method and system based on a civil network, and the method comprises the steps: enabling a plurality of terminal devices at different positions to point to and align at a low-altitude target, collecting target measurement data, and uploading the target measurement data to a background server through the civil network; performing abnormal point detection and elimination by adopting a Z-score detection and dynamic time window filtering method, judging a target batch and a target type according to uploaded data, states and time intervals, and storing the target batch and the target type in a database in an original data form; performing fusion processing on a plurality of pieces of uploaded data through a trajectory fusion algorithm to form a target trajectory, and monitoring, positioning and tracking a low-altitude target; and the target track is sent to a front-end server for target fusion result display, and track information of all the low-altitude targets is completely displayed. According to the invention, data are collected through the terminal equipment, low-altitude targets are monitored, positioned and tracked based on a civil network, low-altitude, slow and small targets are detected and found in time, the detection efficiency is improved, and the system equipment cost is reduced.

Description

Technical Field

[0001] This invention relates to the field of air target control technology, and more specifically, to a method and system for monitoring, locating and tracking low-altitude targets based on civilian networks. Background Technology

[0002] With the rapid development of low-altitude technology, more and more low-altitude targets such as drones are emerging. Due to their flexibility and convenience, drones are widely used in aerial photography, agricultural monitoring, and logistics delivery. However, the widespread use of drones has also brought about significant safety hazards. For example, drones and other low-altitude targets pose a considerable threat to key areas such as airports and high-speed rail stations.

[0003] Existing methods for detecting low-altitude targets such as drones primarily employ radar detection systems and electro-optical tracking systems (electro-optical sensors). However, due to the small radar cross-section of drones, the signal strength reflected back to the radar receiver is relatively weak, and strong clutter occurs in the near-field region, shortening the radar's detection range. This requires the radar to be at a closer distance to detect the drone, resulting in slower target detection and reduced efficiency. Furthermore, electro-optical sensors are significantly affected by natural conditions such as weather and lighting. Under changing lighting conditions or inclement weather, the detection performance of electro-optical sensors deteriorates significantly, affecting the accuracy and stability of detection.

[0004] Moreover, both radar detection systems and photoelectric tracking systems are costly. The cost of a single electronically scanned radar can reach tens of millions of yuan, and it needs to be deployed on multiple sides to achieve omnidirectional coverage, resulting in extremely high overall investment. Precision optical components require high-resolution cameras, infrared thermal imagers, and other equipment, with core components relying on imports or advanced manufacturing processes. This high cost also restricts the deployment of detection systems and affects the detection coverage for low-altitude targets such as drones. Summary of the Invention

[0005] Therefore, the purpose of this invention is to propose a method and system for monitoring, locating, and tracking low-altitude targets based on civilian networks. This method collects target measurement data via terminal devices such as mobile phones or tablets, uploads it to a backend server via a civilian communication network, and uses Z-score detection and dynamic time window filtering to detect and remove outliers in the uploaded data. It employs cross-location algorithms, track initiation algorithms, data association algorithms, and tracking filtering algorithms to perform a series of fusion processes on the target measurement data, including data preprocessing, track initiation, data association, and tracking filtering, forming a target track which is then sent to the front-end server for display. This enables the monitoring, location, and tracking of low-altitude targets, timely detection of low-altitude, slow-moving, and small targets such as UAVs, improves detection, monitoring, and tracking efficiency, and reduces system equipment deployment costs.

[0006] This invention provides a method for monitoring, locating, and tracking low-altitude targets based on civilian networks, comprising the following steps: S1. Point and align multiple terminal devices (mobile phones or tablets) at different locations with low-altitude flying objects, collect target measurement data when the terminal devices are aligned with the low-altitude flying objects using compass mode, and upload the target measurement data collected by the multiple terminal devices to a remote backend server through a civilian communication network. The method for collecting target measurement data when the terminal device is aligned with a low-altitude flying object using the compass mode includes the following steps: S11. A three-dimensional rectangular coordinate system is set with the center point of the terminal device as the origin, wherein the positive direction of the Y-axis is the same as the direction of the N pole of the Earth's magnetic field. S12. Obtain the angle α between the line connecting the center point of the terminal device and the center point of the low-altitude flying target and the direction of the geomagnetic N pole. S13. The slant distance between the center point of the terminal device and the center point of the low-altitude flying object is obtained by measurement (either visually or in combination with an optical ranging instrument); According to actual measurements, the visual distance error of the human eye for low-altitude flying targets can be controlled within 5-10 meters, and the approximate slant distance can be obtained, which meets the application requirements for detecting low-altitude flying targets with low risk levels. To improve detection accuracy, a portable optical rangefinder can be used for distance measurement.

[0007] S14. Based on the slant distance and the included angle α, and taking the center point of the terminal device as the origin of the three-dimensional rectangular coordinate system, calculate the position coordinates of the center point of the low-altitude flying target in the three-dimensional rectangular coordinate system. S15. Based on the position of the center point of the low-altitude flying object in the three-dimensional rectangular coordinate system and the direction of the geomagnetic N pole, calculate the attitude angle data of the terminal device when it is aligned with the low-altitude flying object. Existing methods for collecting information on low-altitude flying targets mainly rely on dedicated hardware systems such as radar sensors, which have poor versatility, high development costs, and long development cycles.

[0008] This invention utilizes ordinary civilian mobile phones or tablet computers and other terminal devices, based on the compass function module configured on the terminal devices, to conveniently collect information on low-altitude flying targets (the data can be collected by installing a terminal APP software on the terminal device, which is convenient for users to operate). It has good versatility, reduces the development cycle, and lowers the research and development and manufacturing costs.

[0009] User terminal devices collect target measurement data using multi-dimensional spatial and temporal data information, which can improve the three-dimensional spatial positioning capability of low-altitude flying targets (such as micro drones). By extracting features such as velocity distribution, heading angle oscillation, and acceleration changes through the back-end server, the device can distinguish between drone and bird flight patterns, reduce positioning errors, and enhance the target acquisition capability in complex environments.

[0010] Civilian communication networks have wide coverage, flexibility, stability, and high reliability, which can guarantee data transmission performance and solve the problems of small coverage, complex system architecture, cumbersome deployment process, and low versatility of existing radar or photoelectric sensors using dedicated transmission networks.

[0011] Preferably, the target measurement data can also be uploaded to a public network server. The public network server is suitable for scenarios that need to provide services to the outside world, such as remote device connection.

[0012] S2. After the background server receives the target measurement data, it uses Z-score detection and dynamic time window filtering to detect and remove outliers in the target measurement data. Based on the uploaded data, status and time interval, it determines the target batch and type of the discovered low-altitude flying objects and stores the target batch and type in the database in the original data form. Handheld terminal devices inevitably experience positional deviations in tracking the trajectory of low-altitude flying objects due to shaking. The backend server data receiving system uses Z-score detection and dynamic time window filtering methods to detect and remove outliers in the uploaded data.

[0013] Specifically, by using basic parameters such as the position (latitude / longitude), speed, and heading angle of low-altitude aircraft, target types such as fixed-wing UAVs, multi-rotor aircraft, or birds can be distinguished.

[0014] Preferably, the location data of the ground terminal equipment can be obtained by combining satellite navigation (such as Beidou / GPS) in order to establish a dynamic tracking trajectory of the target; Target batches and types are stored in the database in the form of raw data. The raw data includes multi-dimensional information such as timestamps and device status, which facilitates integration with external monitoring data such as radar and photoelectric sensors, further improving the accuracy of target identification and threat assessment.

[0015] S3. The data uploaded by multiple terminal devices are fused and processed by the trajectory fusion algorithm. The target trajectory of low-altitude flying objects is formed according to the fusion processing result, and the low-altitude flying object target is monitored, located and tracked. Preferably, when new target measurement data is acquired, the fusion process is repeated on the new target measurement data to obtain updated and newly confirmed target tracks.

[0016] This invention uses a low-cost low-altitude target monitoring, positioning, and tracking system to quickly locate low-altitude flying targets and generate flight paths. It solves the problems of site requirements and resource consumption for deploying specialized detection equipment such as radar and photoelectric sensors, and breaks through the technical bottleneck of high development costs for low-altitude target detection.

[0017] S4. Send the target trajectory to the front-end server for target fusion result display, and display the trajectory information of all low-altitude flying objects in a complete manner.

[0018] Specifically, the situational awareness software on the front-end server displays the complete flight paths of all low-altitude flying objects on the map. This dynamic display of flight path information allows for real-time monitoring of parameters such as the position, speed, and altitude of low-altitude aircraft, enabling rapid identification of abnormal behaviors such as intrusions into no-fly zones.

[0019] Furthermore, step S2, which employs Z-score detection and dynamic time window filtering to detect and remove outliers from the uploaded data, includes the following steps: S21. Let the low-altitude flying object target k be at time... The state is: three-dimensional coordinates ( , , ); three-dimensional velocity ( ), velocity vector magnitude ; The attitude angle of the low-altitude flying object is: Pitch: (The angle of rotation about the y-axis, typically ranging from -90° to 90°) Yaw angle: (The angle of rotation around the z-axis, ranging from [0°, 360°]); Roll angle: (The angle of rotation about the x-axis, usually ranging from -90° to 90°) time With time -1 The time interval is: ; The reasonable constraints for calculating the attitude and velocity of low-altitude flying targets include: S211. Calculate the attitude angle change rate constraint. During normal flight, the rate of change of attitude angles (angular velocity) has a physical upper limit. Let the maximum allowable angular velocity be... (Unit: rad / s); Calculate the rate of change of pitch angle: = ; If | |> If the pitch angle changes abnormally; if | |≤ If so, the pitch angle change is normal; Calculate the rate of change of yaw angle: = ; If | |> If the yaw angle changes abnormally; if | |≤ If so, the yaw angle change is normal; Calculate the rate of change of roll angle: = ; If | |> If the roll angle changes abnormally; if | |≤ If so, the roll angle change is normal; S212. Calculate the rationality constraints of the speed, which include: speed modulus constraints and acceleration constraints; The calculation method for the velocity modulus constraint is as follows: Let the maximum flight speed be... ,like > If <0, the speed is abnormal; if ≤ If so, the speed is normal; The formula for calculating the acceleration constraint is: acceleration = ; like > If the acceleration is abnormal; ≤ If so, the acceleration is normal; S22. The three-dimensional coordinates of the low-altitude flying target k are dynamically updated using a sliding window. , , The mean and standard deviation of the coordinate components of the three-dimensional coordinates of low-altitude flying objects are used to determine Z-score anomalies. The expression for dynamically updating the mean is: = ; Where n is the window size, and x represents the monitored variables being analyzed: velocity, acceleration, and yaw angle; x iThis represents the value of the monitored variable at the ith data point from the (k-n+1)th to the ith data point within the sliding window. The mean of the monitored variable at time ith is obtained by summing and averaging the variable values ​​of these n consecutive data points. ; The formula for calculating the dynamically updated standard deviation is: = ; Where n is the window size, and x represents the monitored variables being analyzed: velocity, acceleration, and yaw angle; x i This represents the value of the monitored variable at the ith data point within the sliding window, from the (k-n+1)th data point to the ith data point. This value is used to calculate the mean of the monitored variable at the current time k. And thus participate in the standard deviation The calculation is used to reflect the dispersion of the data and to provide a basis for subsequent anomaly detection; Detect outliers in 3D coordinates when the absolute value of the Z-score of a certain coordinate component exceeds a preset threshold (e.g., a preset threshold). In statistics, "3" If the probability of a value exceeding three standard deviations is less than 0.3%, then the coordinate is considered an outlier. > or > or > ); If a coordinate is abnormal and is accompanied by a sudden change in the rate of change of attitude angle or an excessive speed, then the coordinate is further determined to be an invalid value. The detection points containing the outliers and invalid values ​​are removed.

[0020] Dynamic time window filtering is a method that dynamically adjusts the analysis window based on time, and can process time series data in data streams or real-time data.

[0021] Preferably, the size of the dynamic time window can be automatically adjusted according to the characteristics of the data (such as rate of change, volatility, etc.) to adapt to real-time changes in the data.

[0022] Z-score detection is based on the principle of normal distribution. In a normal distribution, data usually clusters around the mean, and the further a data point is from the mean, the lower its probability of occurrence. The Z-score detection method determines whether a data point is an outlier by calculating the degree of deviation of each data point from the mean.

[0023] Preferably, Z-score can be used to detect outliers in static datasets, and dynamic time window filtering methods can be used to handle abnormal changes in real-time data streams, thereby improving the efficiency and accuracy of target measurement data acquisition.

[0024] Furthermore, the method in step S3 of fusing uploaded data from multiple terminal devices using a trajectory fusion algorithm and forming the target trajectory of a low-altitude flying object based on the fusion processing result includes: By cross-locating multiple acquisition locations, the target measurement data of the terminal devices at multiple different locations are fused and processed sequentially using cross-location algorithm, track initiation algorithm, data association algorithm and tracking filtering algorithm to obtain the final target track (tracking trajectory). The steps of fusion processing include cross-localization (data preprocessing), track initiation, data association, and tracking filtering. Fusion processing, through the collaboration of spatial and temporal multi-dimensional data and the empowerment of intelligent algorithms, dynamically associates the spatiotemporal attributes of low-altitude flying targets, solves the data fragmentation problem in complex electromagnetic environments, reduces the false judgment rate, and significantly improves target positioning accuracy, environmental adaptability, and dynamic tracking efficiency. The method for fusing target measurement data using the cross-location algorithm includes: Suppose there are two data collection locations: data collection location 1 and data collection location 2. The equation for constructing the cross-location is: ; ; ; (1) In equation (1), ( , , ) are the coordinates of the acquisition location 1, ( , , () represents the coordinates of location 2. It is the azimuth angle between the acquisition location 1 and the target. It is the pitch angle between acquisition position 1 and the target. It is the azimuth angle between the acquisition location 2 and the target. It is the pitch angle between acquisition position 2 and the target. r 1 represents the distance between data acquisition location 1 and the target. r 2 is the distance between the acquisition location 2 and the target; , , ), ( , , ), , , , , r 1. r Both of these are known parameters; , , ) represents the coordinates of the target location, which are unknown parameters that need to be solved; Solving equation (1) yields the target position of the low-altitude flying object. x , y , z )for: ; ; ; ; Based on the target location ( x , y , z This enables the positioning of low-altitude flying objects.

[0025] The cross-positioning algorithm used in this invention integrates local coordinate system data (such as azimuth angle, pitch angle and other pose information, distance information) from multiple acquisition locations of terminal devices through multi-source data fusion and dynamic resource optimization. It dynamically optimizes the target pose in the global coordinate system, achieving centimeter-level positioning accuracy improvement. This effectively solves the problem of error accumulation from a single acquisition device, effectively improves positioning reliability in complex scenarios, and provides strong technical support for low-altitude target monitoring and tracking.

[0026] Furthermore, the method for fusing target measurement data using the aforementioned track initiation algorithm includes: S31. Perform trajectory processing on low-altitude targets to form stable trajectories; S32, When a new number is received Location of a low-altitude target Then, regarding the first The flight path is initiated for each low-altitude target, and a temporary flight path file is established, a batch number is assigned, and the first flight path is set. The status of the target trajectory is The covariance matrix is The target track is then marked with a confirmation flag C_flg. If the target track is updated H times consecutively (the number of H times can be customized as needed), that is, when the C_flg of the target track is incremented to equal H, the target track is confirmed in the track file, and it is considered that the target track is not a temporary track, but a confirmed track. S33. Construct the state transition equation for low-altitude target surveillance, positioning, and tracking, with the following expression: (2) The observation equation for low-altitude target surveillance, positioning, and tracking is constructed as follows: (3) In equations (2) and (3), Here is the state transition matrix. For the measurement matrix, and These are process noise and observation noise, respectively. When there are multiple targets in the air, measurements of all targets are obtained. Afterwards, among them, for time, For the first The first measurement; calculate the first... One-step prediction value for a flight path and ,in for At any time, according to Calculate the residual ; S34. If the current time is k, and there are M measurements and N target tracks, M*N residuals will be received. This generates an M*N residual matrix; S35. Perform Hungarian assignment on the residual matrix, and assign and pair each measurement value i with each target track j to obtain the assignment result; S36. Assigning measurement values i and target track j Pairing (e.g., the first pairing) i The first measurement value and the first j Kalman filtering is performed on the target tracks to obtain the target tracks. j The current moment k The state and covariance matrix indicate that the target trajectory has been completed. j Update.

[0027] Specifically, the state transition equation describes the change of the target state over time, while the observation equation establishes the relationship between the target state and the observed values. The state transition equation and the observation equation are core elements of Kalman filtering. The state transition equation helps the tracking system predict the future trend of the state, and analyzing the state transition equation reveals the dynamic characteristics of low-altitude flying targets. The observation equation determines the accuracy of the estimation of the target's true state.

[0028] The trajectory initiation algorithm used in this invention, through rule-driven and multi-source collaboration, demonstrates outstanding performance in terms of real-time performance, accuracy, and scene adaptability, thereby improving the monitoring and tracking efficiency of low-altitude flying targets.

[0029] Furthermore, step S36 also includes: If a target track j is not assigned a measurement value i, the target track cannot be updated. A pre-deletion flag D_flg is set for the target track. If the target track is not updated for L consecutive times (the number of times L can be customized as needed), that is, when the target track's D_flg is incremented to L, the target track is deleted from the track file.

[0030] Specifically, when a target track is not assigned a measurement value, the target status needs to be continuously predicted based on the current track to maintain track continuity within a set time. If the target track fails to be assigned a measurement value more than a preset threshold number of times and cannot be updated, the track can be deleted as an invalid track.

[0031] Furthermore, step S36 also includes: For measurement value i that has not been assigned to target track j, track initiation is performed, a temporary track file is created, and the status of the target track is set to [value to be specified]. The covariance matrix is The target track is marked with a confirmation flag C_flg. If the target track is updated H times consecutively, that is, when the C_flg of the target track is incremented to H, the target track is confirmed in the track file, and it is considered that the target track is not a temporary track, but a confirmed track.

[0032] In low-altitude flight scenarios, dynamic changes in obstacles, weather clutter, or temporary no-fly zones may cause incompatibility between measured values ​​and target tracks, resulting in unassigned data. In such cases, track initiation can quickly establish the initial track of the new target, shorten the system's reaction time, avoid continuous tracking of false alarms, and reduce the computational resource consumption for subsequent track maintenance.

[0033] Furthermore, the target measurement data in step S1, which involves collecting target measurement data using compass mode when the terminal device is aligned with a low-altitude flying object, includes: The current user's latitude and longitude information, the terminal device's azimuth angle information, the terminal device's level elevation angle information, and the time information.

[0034] This invention also provides a low-altitude target surveillance, positioning, and tracking system based on a civilian network, used to implement the low-altitude target surveillance, positioning, and tracking method based on a civilian network as described above, comprising: Data acquisition module: used to point and align multiple terminal devices at different locations with low-altitude flying objects, collect target measurement data when the terminal devices are aligned with the low-altitude flying objects using compass mode, and upload the target measurement data collected by multiple terminal devices to a remote backend server through a civilian communication network. The data receiving and storage module is used to detect and remove outliers in the target measurement data after the target measurement data is received by the background server using Z-score detection and dynamic time window filtering methods. Based on the uploaded data, status and time interval, it determines the target batch and type of the discovered low-altitude flying objects and stores the target batch and type in the database in the original data form. Fusion processing module: Used to fuse data uploaded from multiple terminal devices through trajectory fusion algorithm, form target tracks of low-altitude flying objects based on the fusion processing results, and monitor, locate and track low-altitude flying objects; Track display module: used to send the target track to the front-end server for target fusion result display, and to fully display the track information of all low-altitude flying objects.

[0035] The data acquisition module of this invention can be made into an application (App) and installed on a terminal device (such as a mobile phone or tablet computer).

[0036] The present invention also provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of the low-altitude target surveillance, positioning and tracking method based on civilian networks as described above.

[0037] The present invention also provides a computer device, the computer device including a memory, a processor and a computer program stored in the memory and executable on the processor, wherein when the processor executes the program, it implements the steps of the low-altitude target monitoring, positioning and tracking method based on civilian networks as described above.

[0038] Compared with the prior art, the beneficial effects of the present invention are as follows: The low-altitude target monitoring, positioning, and tracking method and system based on civilian networks provided by this invention collects data through terminal devices such as mobile phones or tablets. Based on civilian communication networks, the system monitors, positions, and tracks low-altitude targets on a backend server. After acquiring the information from the data acquisition end, the system employs a series of fusion processing steps, including data preprocessing, track initiation, data association, and tracking filtering, using cross-positioning algorithms, track initiation algorithms, data association algorithms, and tracking filtering algorithms. This results in a target track that is then sent to the frontend server for display. This method enables timely detection of low-altitude, slow-moving, and small targets such as drones, improving detection efficiency and reducing system equipment costs. Attached Figure Description

[0039] Various other advantages and benefits will become apparent to those skilled in the art upon reading the following detailed description of preferred embodiments. The accompanying drawings are for illustrative purposes only and are not intended to limit the invention.

[0040] In the attached diagram: Figure 1 This is a diagram of the data acquisition terminal software interface installed and deployed on a mobile phone and tablet computer according to an embodiment of the present invention; Figure 2 This is a schematic diagram of cross-positioning according to an embodiment of the present invention; Figure 3 This is a flowchart of the low-altitude target tracking process according to an embodiment of the present invention; Figure 4 This is a civil aircraft trajectory diagram displayed on the software according to an embodiment of the present invention; Figure 5 This is a flowchart of the low-altitude target surveillance, positioning, and tracking method based on civilian networks according to the present invention; Figure 6 This is a schematic diagram of the configuration of a computer device according to an embodiment of the present invention. Detailed Implementation

[0041] Exemplary embodiments will now be described in detail, examples of which are illustrated in the accompanying drawings. When the following description relates to the drawings, unless otherwise indicated, the same numerals in different drawings denote the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with this disclosure. Rather, they are merely examples of apparatuses and products consistent with some aspects of this disclosure as detailed in the appended claims.

[0042] The terminology used in this disclosure is for the purpose of describing particular embodiments only and is not intended to be limiting of the disclosure. The singular forms “a,” “the,” and “the” as used in this disclosure and the appended claims are also intended to include the plural forms unless the context clearly indicates otherwise. It should also be understood that the term “and / or” as used herein refers to and includes any and all possible combinations of one or more of the associated listed items.

[0043] It should be understood that although the terms first, second, third, etc., may be used in this disclosure to describe various information, such information should not be limited to these terms. These terms are used only to distinguish information of the same type from one another. For example, without departing from the scope of this disclosure, first information may also be referred to as second information, and similarly, second information may also be referred to as first information. Depending on the context, the word "if" as used herein may be interpreted as "when," "when," or "in response to determination."

[0044] The embodiments of the present invention will be further described in detail below with reference to the accompanying drawings.

[0045] This invention provides a method for low-altitude target surveillance, positioning, and tracking based on civilian networks. See [link to relevant documentation]. Figure 5 As shown, it includes the following steps: S1. Point and align multiple terminal devices at different locations with low-altitude flying objects, collect target measurement data when the terminal devices are aligned with the low-altitude flying objects using compass mode, and upload the target measurement data collected by the multiple terminal devices to a remote backend server through a civilian communication network. The target measurement data includes: the current latitude and longitude of the user, the azimuth angle of the terminal device, the pitch angle of the terminal device's level, and the time information.

[0046] The method for collecting target measurement data when a terminal device is aligned with a low-altitude flying object using the compass mode includes the following steps: S11. A three-dimensional rectangular coordinate system is set with the center point of the terminal device as the origin, wherein the positive direction of the Y-axis is the same as the direction of the N pole of the Earth's magnetic field. S12. Obtain the angle α between the line connecting the center point of the terminal device and the center point of the low-altitude flying target and the direction of the geomagnetic N pole. S13. The slant distance between the center point of the terminal device and the center point of the low-altitude flying object target is determined by visual inspection. S14. Based on the slant distance and the included angle α, and taking the center point of the terminal device as the origin of the three-dimensional rectangular coordinate system, calculate the position coordinates of the center point of the low-altitude flying target in the three-dimensional rectangular coordinate system. S15. Based on the position of the center point of the low-altitude flying object in the three-dimensional rectangular coordinate system and the direction of the geomagnetic N pole, calculate the attitude angle data of the terminal device when it is aligned with the low-altitude flying object. S2. After the background server receives the target measurement data, it uses Z-score detection and dynamic time window filtering to detect and remove outliers in the target measurement data. Based on the uploaded data, status and time interval, it determines the target batch and type of the discovered low-altitude flying objects and stores the target batch and type in the database in the original data form. The outlier detection and removal process for the uploaded data using Z-score detection and dynamic time window filtering includes the following steps: S21. Let the low-altitude flying object target k be at time... The state is: three-dimensional coordinates ( , , ); three-dimensional velocity ( ), velocity vector magnitude ; The attitude angle of the low-altitude flying object is: Pitch: (The angle of rotation around the y-axis, ranging from -90° to 90°) Yaw angle: (The angle of rotation around the z-axis, ranging from [0°, 360°]); Roll angle: (The angle of rotation around the x-axis, ranging from -90° to 90°) time With time -1 The time interval is: ; The reasonable constraints for calculating the attitude and velocity of low-altitude flying targets include: S211. Calculate the attitude angle change rate constraint, assuming the maximum allowable angular velocity is... (Unit: rad / s); Calculate the rate of change of pitch angle: = ; If | |> If the pitch angle changes abnormally; if | |≤ If so, the pitch angle change is normal; Calculate the rate of change of yaw angle: = ; If | |> If the yaw angle changes abnormally; if | |≤ If so, the yaw angle change is normal; Calculate the rate of change of roll angle: = ; If | |> If the roll angle changes abnormally; if | |≤ If so, the roll angle change is normal; S212. Calculate the rationality constraints of the speed, which include: speed modulus constraints and acceleration constraints; The calculation method for the velocity modulus constraint is as follows: Let the maximum flight speed be... ,like > If <0, the speed is abnormal; if ≤ If so, the speed is normal; The formula for calculating the acceleration constraint is: acceleration = ; like > If the acceleration is abnormal; ≤ If so, the acceleration is normal; S22. The three-dimensional coordinates of the low-altitude flying target k are dynamically updated using a sliding window. , , The mean and standard deviation of the coordinate components of the three-dimensional coordinates of low-altitude flying objects are used to determine Z-score anomalies. The expression for dynamically updating the mean is: = ; Where n is the window size, and x represents the monitored variables being analyzed: velocity, acceleration, and yaw angle; x i This represents the value of the monitored variable at the ith data point from the (k-n+1)th to the ith data point within the sliding window. The mean of the monitored variable at time ith is obtained by summing and averaging the variable values ​​of these n consecutive data points. ; The formula for calculating the dynamically updated standard deviation is: = ; Where n is the window size, and x represents the monitored variables being analyzed: velocity, acceleration, and yaw angle; x i This represents the value of the monitored variable at the ith data point within the sliding window, from the (k-n+1)th data point to the ith data point. This value is used to calculate the mean of the monitored variable at the current time k. And thus participate in the standard deviation The calculation is used to reflect the dispersion of the data and to provide a basis for subsequent anomaly detection; To identify outliers in the 3D coordinates, when the absolute value of the Z-score of a certain coordinate component exceeds a preset threshold (in this embodiment, the preset threshold is...). In statistics, "3" If the probability of a value exceeding three standard deviations is less than 0.3%, then the coordinate is considered an outlier. > or > or > ); If a coordinate is abnormal and is accompanied by a sudden change in the rate of change of attitude angle or an excessive speed, then the coordinate is further determined to be an invalid value. The detection points containing the outliers and invalid values ​​are removed.

[0047] Dynamic time window filtering processes time-series data in data streams or real-time data by dynamically adjusting the analysis window based on time. The size of the dynamic time window is adjusted according to the characteristics of the data (rate of change, volatility, etc.) to adapt to real-time changes in the data.

[0048] Z-score detection is based on the principle of normal distribution. In a normal distribution, data usually clusters around the mean, and the further a data point is from the mean, the lower its probability of occurrence. The Z-score detection method determines whether a data point is an outlier by calculating the degree of deviation of each data point from the mean.

[0049] Z-score is used to detect outliers in static datasets, and dynamic time window filtering is used to handle abnormal changes in real-time data streams, thereby improving the efficiency and accuracy of target measurement data acquisition.

[0050] The backend server data receiving system uses Z-score detection and dynamic time window filtering to detect and remove anomalies in the uploaded data. Due to shaking, the handheld terminal device inevitably has positional deviations in tracking the trajectory of low-altitude flying objects.

[0051] By using basic parameters such as the position (latitude / longitude), speed, and heading angle of low-altitude aircraft, target types such as fixed-wing UAVs, multi-rotor aircraft, or birds can be distinguished.

[0052] It can be combined with satellite navigation (such as Beidou / GPS) to obtain the azimuth data of ground terminal equipment, which facilitates the establishment of dynamic tracking trajectory of the target; Target batches and types are stored in the database in the form of raw data. The raw data includes multi-dimensional information such as timestamps and device status, which facilitates integration with external monitoring data such as radar and photoelectric sensors, further improving the accuracy of target identification and threat assessment.

[0053] S3. The data uploaded by multiple terminal devices are fused and processed by the trajectory fusion algorithm. The target trajectory of low-altitude flying objects is formed according to the fusion processing result, and the low-altitude flying object target is monitored, located and tracked. Methods for fusing uploaded data from multiple terminal devices using trajectory fusion algorithms to form target trajectories for low-altitude flying objects based on the fusion results include: By cross-locating multiple acquisition locations, the target measurement data of the terminal devices at multiple different locations are fused and processed sequentially using cross-location algorithm, track initiation algorithm, data association algorithm and tracking filtering algorithm to obtain the final target track (tracking trajectory). The steps of fusion processing include cross-localization (data preprocessing), track initiation, data association, and tracking filtering. Fusion processing, through the collaboration of spatial and temporal multi-dimensional data and the empowerment of intelligent algorithms, dynamically associates the spatiotemporal attributes of low-altitude flying targets, solves the data fragmentation problem in complex electromagnetic environments, reduces the false judgment rate, and significantly improves target positioning accuracy, environmental adaptability, and dynamic tracking efficiency. The method for fusing target measurement data using the cross-location algorithm includes: Suppose there are two data collection locations: data collection location 1 and data collection location 2. The equation for constructing the cross-location is: ; ; ; (1) In equation (1), ( , , ) are the coordinates of the acquisition location 1, ( , , () represents the coordinates of location 2. It is the azimuth angle between the acquisition location 1 and the target. It is the pitch angle between acquisition position 1 and the target. It is the azimuth angle between the acquisition location 2 and the target. It is the pitch angle between acquisition position 2 and the target. r 1 represents the distance between data acquisition location 1 and the target. r 2 is the distance between the acquisition location 2 and the target; , , ), ( , , ), , , , , r 1. r Both of these are known parameters; , , ) represents the coordinates of the target location, which are unknown parameters that need to be solved; Solving equation (1) yields the target position of the low-altitude flying object. x , y , z )for: ; ; ; ; Based on the target location ( x , y , z This enables the positioning of low-altitude flying objects.

[0054] The cross-positioning algorithm used in this embodiment integrates local coordinate system data (such as azimuth angle, pitch angle, and other pose information, distance information, etc.) from multiple acquisition locations of terminal devices through multi-source data fusion and dynamic resource optimization. Figure 2 As shown in the figure, the target pose in the global coordinate system is dynamically optimized to improve the positioning accuracy to the centimeter level, which solves the problem of error accumulation of a single acquisition device and improves the positioning reliability in complex scenarios.

[0055] The method for fusing target measurement data using the aforementioned track initiation algorithm includes: S31. Perform trajectory processing on low-altitude targets to form stable trajectories; S32, When a new number is received Location of a low-altitude target Then, regarding the first The flight path is initiated for each low-altitude target, and a temporary flight path file is established, a batch number is assigned, and the first flight path is set. The status of the target trajectory is The covariance matrix is The target track is then marked with a confirmation flag C_flg. If the target track is updated H times consecutively (the number of H times can be customized as needed), that is, when the C_flg of the target track is incremented to equal H, the target track is confirmed in the track file, and it is considered that the target track is not a temporary track, but a confirmed track. S33. Construct the state transition equation for low-altitude target surveillance, positioning, and tracking, with the following expression: (2) The observation equation for low-altitude target surveillance, positioning, and tracking is constructed as follows: (3) In equations (2) and (3), Here is the state transition matrix. For the measurement matrix, and These are process noise and observation noise, respectively. When there are multiple targets in the air, measurements of all targets are obtained. Afterwards, among them, for time, For the first The first measurement; calculate the first... One-step prediction value for a flight path and ,in for At any time, according to Calculate the residual ; S34. If the current time is k, and there are M measurements and N target tracks, M*N residuals will be received. This generates an M*N residual matrix; S35. Perform Hungarian assignment on the residual matrix, and assign and pair each measurement value i with each target track j to obtain the assignment result; S36. Assigning measurement values i and target track j Pairing (e.g., the first) i The first measurement value and the first j Kalman filtering is performed on the target tracks to obtain the target tracks. j The current moment k The state and covariance matrix indicate that the target trajectory has been completed. j Update.

[0056] The state transition equation describes the change of the target state over time, while the observation equation establishes the relationship between the target state and the observed values. These two equations are core elements of Kalman filtering. The state transition equation helps the tracking system predict the future trend of the target state, and analyzing it reveals the dynamic characteristics of low-altitude flying targets. The observation equation determines the accuracy of the estimation of the target's true state.

[0057] If a target track j is not assigned a measurement value i, the target track cannot be updated. A pre-deletion flag D_flg is set for the target track. If the target track is not updated for L consecutive times (the number of times L can be customized as needed), that is, when the target track's D_flg is incremented to L, the target track is deleted from the track file.

[0058] When a target track is not assigned a measurement value, the target status must be continuously predicted based on the current track to maintain track continuity within a set time. If a target track fails to be assigned a measurement value more than a preset threshold number of times and cannot be updated, the track can be deleted as an invalid track.

[0059] For measurement value i that has not been assigned to target track j, track initiation is performed, a temporary track file is created, and the status of the target track is set to [value to be specified]. The covariance matrix is The target track is marked with a confirmation flag C_flg. If the target track is updated H times consecutively, that is, when the C_flg of the target track is incremented to H, the target track is confirmed in the track file, and it is considered that the target track is not a temporary track, but a confirmed track.

[0060] In low-altitude flight scenarios, dynamic changes in obstacles, weather clutter, or temporary no-fly zones may cause incompatibility between measured values ​​and target tracks, resulting in unassigned data. In such cases, track initiation can quickly establish the initial track of the new target, shorten the system's reaction time, avoid continuous tracking of false alarms, and reduce the computational resource consumption for subsequent track maintenance.

[0061] When new target measurement data is acquired, the fusion process is repeated on the new target measurement data to obtain the updated and newly confirmed target tracks.

[0062] This embodiment uses a low-cost low-altitude target surveillance, positioning and tracking system to quickly locate low-altitude flying targets and form flight paths. It solves the site requirements and resource consumption of deploying special detection equipment such as radar and photoelectric sensors, and breaks through the technical bottleneck of high development cost of low-altitude target detection.

[0063] S4. Send the target trajectory to the front-end server for target fusion result display, and display the trajectory information of all low-altitude flying objects in a complete manner.

[0064] The situational awareness software on the front-end server displays the complete flight paths of all low-altitude flying objects on the map. This dynamic display of flight path information allows for real-time monitoring of parameters such as the position, speed, and altitude of low-altitude aircraft, enabling rapid identification of abnormal behaviors such as intrusions into no-fly zones.

[0065] Figure 3 The low-altitude target tracking process of this embodiment is illustrated.

[0066] This invention also provides a low-altitude target surveillance, positioning, and tracking system based on a civilian network, used to implement the low-altitude target surveillance, positioning, and tracking method based on a civilian network as described above, including: Data acquisition module: used to point and align multiple terminal devices at different locations with low-altitude flying objects, collect target measurement data when the terminal devices are aligned with the low-altitude flying objects using compass mode, and upload the target measurement data collected by multiple terminal devices to a remote backend server through a civilian communication network. The data receiving and storage module is used to detect and remove outliers in the target measurement data after the target measurement data is received by the background server using Z-score detection and dynamic time window filtering methods. Based on the uploaded data, status and time interval, it determines the target batch and type of the discovered low-altitude flying objects and stores the target batch and type in the database in the original data form. Fusion processing module: Used to fuse data uploaded from multiple terminal devices through trajectory fusion algorithm, form target tracks of low-altitude flying objects based on the fusion processing results, and monitor, locate and track low-altitude flying objects; Track display module: used to send the target track to the front-end server for target fusion result display, and to fully display the track information of all low-altitude flying objects.

[0067] In this embodiment of the invention, the data acquisition module's functionality is made into an application (App) and installed on terminal devices such as mobile phones or tablets, for example... Figure 1 As shown.

[0068] In a practical application, the algorithm of this invention was verified near an airport. Low-altitude target data was collected via a mobile phone or tablet computer, and the low-altitude targets were monitored, located, and tracked through a civilian communication network, ultimately forming the flight path of the low-altitude targets. Figure 4 The software displays the trajectory of a civil aircraft.

[0069] This invention also provides a computer device. Figure 6 This is a schematic diagram of the structure of a computer device provided in an embodiment of the present invention; see the accompanying drawings. Figure 6 As shown, the computer device includes: an input device 23, an output device 24, a memory 22, and a processor 21; the memory 22 is used to store one or more programs; when the one or more programs are executed by the one or more processors 21, the one or more processors 21 implement the low-altitude target surveillance, positioning, and tracking method based on a civilian network as provided in the above embodiment; wherein the input device 23, the output device 24, the memory 22, and the processor 21 can be connected via a bus or other means. Figure 6 Taking the example of a connection between China and Israel via a bus.

[0070] The memory 22, as a read / write storage medium for a computing device, can be used to store software programs and computer-executable programs, such as the program instructions corresponding to the low-altitude target monitoring, positioning, and tracking method based on a civilian network as described in this embodiment of the invention. The memory 22 may primarily include a program storage area and a data storage area. The program storage area may store the operating system and at least one application program required for a given function. The data storage area may store data created based on the use of the device. Furthermore, the memory 22 may include high-speed random access memory and non-volatile memory, such as at least one disk storage device, flash memory device, or other non-volatile solid-state storage device. In some instances, the memory 22 may further include memory remotely located relative to the processor 21, and these remote memories can be connected to the device via a network. Examples of such networks include, but are not limited to, the Internet, corporate intranets, local area networks, mobile communication networks, and combinations thereof.

[0071] Input device 23 can be used to receive input digital or character information, and generate key signal inputs related to user settings and function control of the device; output device 24 may include display devices such as a display screen.

[0072] The processor 21 executes various functional applications and data processing of the device by running software programs, instructions and modules stored in the memory 22, thereby realizing the above-mentioned low-altitude target monitoring, positioning and tracking method based on civilian networks.

[0073] The computer equipment provided above can be used to execute the low-altitude target surveillance, positioning and tracking method based on civilian networks provided in the above embodiments, and has corresponding functions and beneficial effects.

[0074] This invention also provides a storage medium containing computer-executable instructions, which, when executed by a computer processor, are used to perform the low-altitude target surveillance, positioning, and tracking method based on a civilian network as provided in the above embodiments. The storage medium can be any type of memory device or storage device, including: mounting media such as CD-ROM, floppy disk, or magnetic tape; computer system memory or random access memory such as DRAM, DDRRAM, SRAM, EDORAM, Rambus RAM, etc.; non-volatile memory such as flash memory, magnetic media (e.g., hard disk or optical storage); registers or other similar types of memory components; the storage medium may also include other types of memory or combinations thereof; furthermore, the storage medium may reside in a first computer system in which the program is executed, or it may reside in a different second computer system connected to the first computer system via a network (such as the Internet); the second computer system can provide program instructions to the first computer for execution. The storage medium includes two or more storage media that can reside in different locations (e.g., in different computer systems connected via a network). The storage medium can store program instructions (e.g., specifically implemented as a computer program) executable by one or more processors.

[0075] Of course, the computer-executable instructions provided in the embodiments of the present invention are not limited to the low-altitude target surveillance, positioning and tracking method based on civilian networks as described in the above embodiments, but can also perform related operations in the low-altitude target surveillance, positioning and tracking method based on civilian networks provided in any embodiment of the present invention.

[0076] The technical solution of the present invention has been described above with reference to the preferred embodiments shown in the accompanying drawings. However, it will be readily understood by those skilled in the art that the scope of protection of the present invention is obviously not limited to these specific embodiments. Without departing from the principles of the present invention, those skilled in the art can make equivalent changes or substitutions to the relevant technical features, and the technical solutions after these changes or substitutions will all fall within the scope of protection of the present invention.

[0077] The above description is merely a preferred embodiment of the present invention and is not intended to limit the invention. Various modifications and variations can be made to the present invention by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A method for monitoring, locating, and tracking low-altitude targets based on civilian networks, characterized in that: Includes the following steps: S1. Point and align multiple terminal devices at different locations with low-altitude flying objects, collect target measurement data when the terminal devices are aligned with the low-altitude flying objects using compass mode, and upload the target measurement data collected by the multiple terminal devices to a remote backend server through a civilian communication network. The method for collecting target measurement data when the terminal device is aligned with a low-altitude flying object using the compass mode includes the following steps: S11. A three-dimensional rectangular coordinate system is set with the center point of the terminal device as the origin, wherein the positive direction of the Y-axis is the same as the direction of the N pole of the Earth's magnetic field. S12. Obtain the angle α between the line connecting the center point of the terminal device and the center point of the low-altitude flying target and the direction of the geomagnetic N pole. S13. The slant distance between the center point of the terminal device and the center point of the low-altitude flying object target is obtained by measurement; S14. Based on the slant distance and the included angle α, and taking the center point of the terminal device as the origin of the three-dimensional rectangular coordinate system, calculate the position coordinates of the center point of the low-altitude flying target in the three-dimensional rectangular coordinate system. S15. Based on the position of the center point of the low-altitude flying object in the three-dimensional rectangular coordinate system and the direction of the geomagnetic N pole, calculate the attitude angle data of the terminal device when it is aligned with the low-altitude flying object. S2. After the background server receives the target measurement data, it uses Z-score detection and dynamic time window filtering to detect and remove outliers in the target measurement data. Based on the uploaded data, status and time interval, it determines the target batch and type of the discovered low-altitude flying objects and stores the target batch and type in the database in the original data form. S3. The data uploaded by multiple terminal devices are fused and processed by the trajectory fusion algorithm. The target trajectory of low-altitude flying objects is formed according to the fusion processing result, and the low-altitude flying object target is monitored, located and tracked. S4. Send the target trajectory to the front-end server for target fusion result display, and display the trajectory information of all low-altitude flying objects in a complete manner.

2. The low-altitude target surveillance, positioning, and tracking method based on civilian networks according to claim 1, characterized in that, The S2 step of using Z-score detection and dynamic time window filtering to detect and remove outliers in the uploaded data includes the following steps: S21. Let the low-altitude flying object target k be at time... The state is: three-dimensional coordinates ( , , ); three-dimensional velocity ( ), velocity vector magnitude ; The attitude angle of the low-altitude flying object is: Pitch angle: , It is the angle of rotation about the y-axis. The range is [-90°, 90°]; Yaw angle: , It is the angle of rotation about the z-axis. The range is [0°, 360°]; Roll angle: , It is the angle of rotation about the x-axis. The range is [-90°, 90°]; time With time -1 The time interval is: ; The reasonable constraints for calculating the attitude and velocity of low-altitude flying targets include: S211. Calculate the attitude angle change rate constraint, assuming the maximum allowable angular velocity is... ; Calculate the rate of change of pitch angle: = ; If | |> If the pitch angle changes abnormally; if | |≤ If so, the pitch angle change is normal; Calculate the rate of change of yaw angle: = ; If | |> If the yaw angle changes abnormally; if | |≤ If so, the yaw angle change is normal; Calculate the rate of change of roll angle: = ; If | |> If the roll angle changes abnormally; if | |≤ If so, the roll angle change is normal; S212. Calculate the rationality constraints of the speed, which include: speed modulus constraints and acceleration constraints; The calculation method for the velocity modulus constraint is as follows: Let the maximum flight speed be... ,like > If <0, the speed is abnormal; if ≤ If so, the speed is normal; The formula for calculating the acceleration constraint is: acceleration = ; like > If the acceleration is abnormal; ≤ If so, the acceleration is normal; S22. The three-dimensional coordinates of the low-altitude flying target k are dynamically updated using a sliding window. , , The mean and standard deviation of the coordinate components of the three-dimensional coordinates of low-altitude flying objects are used to determine Z-score anomalies. The expression for dynamically updating the mean is: = ； Where n is the window size, and x represents the monitored variables being analyzed: velocity, acceleration, and yaw angle; x i This represents the value of the monitored variable at the ith data point from the (k-n+1)th to the ith data point within the sliding window. The mean of the monitored variable at time ith is obtained by summing and averaging the variable values ​​of these n consecutive data points. ; The formula for calculating the dynamically updated standard deviation is: = ； Where n is the window size, and x represents the monitored variables being analyzed: velocity, acceleration, and yaw angle; x i This represents the value of the monitored variable at the ith data point within the sliding window, from the (k-n+1)th data point to the ith data point. This value is used to calculate the mean of the monitored variable at the current time k. And thus participate in the standard deviation The calculation is used to reflect the dispersion of the data and to provide a basis for subsequent anomaly detection; Detect outliers in 3D coordinates when the absolute value of the Z-score of a certain coordinate component exceeds a preset threshold; If a coordinate is abnormal and is accompanied by a sudden change in the rate of change of attitude angle or an excessive speed, then the coordinate is further determined to be an invalid value. The detection points containing the outliers and invalid values ​​are removed.

3. The low-altitude target surveillance, positioning, and tracking method based on civilian networks according to claim 2, characterized in that, The method for fusing uploaded data from multiple terminal devices using a trajectory fusion algorithm in step S3, and forming the target trajectory of a low-altitude flying object based on the fusion processing result, includes: By cross-locating multiple acquisition locations, the target measurement data from multiple terminal devices at different locations are fused and processed sequentially using cross-location algorithm, track initiation algorithm, data association algorithm, and tracking filtering algorithm to obtain the final target track. The method for fusing target measurement data using the cross-location algorithm includes: Suppose there are two data collection locations: data collection location 1 and data collection location 2. The equation for constructing the cross-location is: ； ； ； （1） In equation (1), ( , , ) are the coordinates of the acquisition location 1, ( , , () represents the coordinates of location 2. It is the azimuth angle between the acquisition location 1 and the target. It is the pitch angle between acquisition position 1 and the target. It is the azimuth angle between the acquisition location 2 and the target. It is the pitch angle between acquisition position 2 and the target. r 1 represents the distance between data acquisition location 1 and the target. r 2 is the distance between the acquisition location 2 and the target; , , ), ( , , ), , , , , r 1. r Both of these are known parameters; , , ) represents the coordinates of the target location, which are unknown parameters that need to be solved; Solving equation (1) yields the target position of the low-altitude flying object. x , y , z )for: ； ； ； ； Based on the target location ( x , y , z This enables the positioning of low-altitude flying objects.

4. The low-altitude target surveillance, positioning, and tracking method based on civilian networks according to claim 2, characterized in that, The method for fusing target measurement data using the aforementioned track initiation algorithm includes: S31. Perform trajectory processing on low-altitude targets to form stable trajectories; S32, When a new number is received Location of a low-altitude target Then, regarding the first The flight path is initiated for each low-altitude target, and a temporary flight path file is established, a batch number is assigned, and the first flight path is set. The status of the target trajectory is The covariance matrix is The target track is marked with a confirmation flag C_flg; if the target track is updated H times consecutively, that is, when the C_flg of the target track is incremented to H, the target track is confirmed in the track file, and it is considered that the target track is not a temporary track, but a confirmed track. S33. Construct the state transition equation for low-altitude target surveillance, positioning, and tracking, with the following expression: (2) The observation equation for low-altitude target surveillance, positioning, and tracking is constructed as follows: (3) In equations (2) and (3), Here is the state transition matrix. For the measurement matrix, and These are process noise and observation noise, respectively. When there are multiple targets in the air, measurements of all targets are obtained. Afterwards, among them, for time, For the first The first measurement; calculate the first... One-step prediction value for a flight path and ,in for At any time, according to Calculate the residual ; S34. If the current time is k, and there are M measurements and N target tracks, M*N residuals will be received. This generates an M*N residual matrix; S35. Perform Hungarian assignment on the residual matrix, and assign and pair each measurement value i with each target track j to obtain the assignment result; S36. Assigning measurement values i and target track j The paired targets are then subjected to Kalman filtering to obtain the target trajectory. j The current moment k The state and covariance matrix are used to complete the target trajectory. j Update.

5. The low-altitude target surveillance, positioning, and tracking method based on civilian networks according to claim 4, characterized in that, The S36 step further includes: If a target track j is not assigned a measurement value i, the target track cannot be updated. A pre-deletion flag D_flg is set for the target track. If the target track is not updated for L consecutive times, that is, when the target track's D_flg is incremented to L, the target track is deleted from the track file.

6. The low-altitude target surveillance, positioning, and tracking method based on civilian networks according to claim 4, characterized in that, The S36 step further includes: For measurement value i that has not been assigned to target track j, track initiation is performed, a temporary track file is created, and the status of the target track is set to [value to be specified]. The covariance matrix is The target track is marked with a confirmation flag C_flg. If the target track is updated H times consecutively, that is, when the C_flg of the target track is incremented to H, the target track is confirmed in the track file, and it is considered that the target track is not a temporary track, but a confirmed track.

7. The low-altitude target surveillance, positioning, and tracking method based on civilian networks according to claim 1, characterized in that, The target measurement data in step S1, which involves collecting target measurement data when the terminal device is aligned with a low-altitude flying object using compass mode, includes: The current user's latitude and longitude information, the terminal device's azimuth angle information, the terminal device's level elevation angle information, and the time information.

8. A low-altitude target surveillance, positioning, and tracking system based on a civilian network, used to implement the low-altitude target surveillance, positioning, and tracking method based on a civilian network as described in any one of claims 1-7, characterized in that, include: Data acquisition module: used to point and align multiple terminal devices at different locations with low-altitude flying objects, collect target measurement data when the terminal devices are aligned with the low-altitude flying objects using compass mode, and upload the target measurement data collected by multiple terminal devices to a remote backend server through a civilian communication network. The data receiving and storage module is used to detect and remove outliers in the target measurement data after the target measurement data is received by the background server using Z-score detection and dynamic time window filtering methods. Based on the uploaded data, status and time interval, it determines the target batch and type of the discovered low-altitude flying objects and stores the target batch and type in the database in the original data form. Fusion processing module: Used to fuse data uploaded from multiple terminal devices through trajectory fusion algorithm, form target tracks of low-altitude flying objects based on the fusion processing results, and monitor, locate and track low-altitude flying objects; Track display module: used to send the target track to the front-end server for target fusion result display, and to fully display the track information of all low-altitude flying objects.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the program is executed by the processor, it implements the steps of the low-altitude target surveillance, positioning and tracking method based on civilian networks as described in any one of claims 1-7.

10. A computer device, the computer device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the program, it implements the steps of the low-altitude target surveillance, positioning and tracking method based on civilian networks as described in any one of claims 1-7.

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