An unmanned aerial vehicle monitoring system and a monitoring method thereof

Abstract

The application relates to the technical field of unmanned aerial vehicle monitoring, and discloses an unmanned aerial vehicle monitoring system and a monitoring method thereof, which comprise a target object signal acquisition module, a signal receiving, analyzing and matching module, a target object matching and early warning module, a target object path calibration module, a calibrated path matching and identifying module and a target object path early warning module; target signals in a target area are acquired by a hardware device and are analyzed and matched; when the matching is unsuccessful, early warning information is sent to a base station management platform according to a matching result; when the matching is successful, the flight path of the target object is calibrated; based on the calibrated flight path of the target object, path deviation analysis and flight time monitoring are carried out on the target object to obtain a flight abnormality index of the target object; and the flight path of the target object is abnormally judged, so that the accuracy of target object identification and the timeliness of early warning are improved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of unmanned aerial vehicle monitoring, more particularly to an unmanned aerial vehicle monitoring system and a monitoring method thereof. BACKGROUND

[0002] With the rapid development of society and the increasing demand of people for environmental monitoring, city management, disaster warning and the like, the traditional monitoring means has been difficult to meet the diversified demand, thus the unmanned aerial vehicle technology has been rapidly developed, the performance of unmanned aerial vehicle is continuously improved, and the application field is increasingly wide, the unmanned aerial vehicle has the advantages of rapid movement, wide coverage, no limitation by terrain and the like, so that it becomes a new darling in the monitoring field, through carrying various sensors and monitoring equipment, the unmanned aerial vehicle can realize comprehensive, real-time and efficient monitoring of the target area.

[0003] However, since the unmanned aerial vehicles are numerous and widely distributed, it is difficult for the regulatory department to effectively monitor and manage all the unmanned aerial vehicles, in addition, some unmanned aerial vehicle operators will take the way of hidden flight, night flight and the like to evade supervision, some unmanned aerial vehicle operators lack the understanding and recognition of relevant regulations, and there are black flight and private flight behaviors, which pose a threat to public safety.

[0004] Meanwhile, the unmanned aerial vehicle may be interfered by signals from the ground or the air in the flight process, resulting in distortion or loss of positioning signals, for example, electromagnetic interference, building shielding and the like, the positioning equipment of some unmanned aerial vehicles has limited precision, and it is difficult to meet the demand of high-precision positioning, thus the flight path of the unmanned aerial vehicle is not accurately positioned. SUMMARY

[0005] In order to overcome the above-mentioned defects of the prior art, the present application provides an unmanned aerial vehicle monitoring system to solve the problems in the above background.

[0006] The present application provides the following technical scheme: an unmanned aerial vehicle monitoring system, comprising: a target object signal acquisition module, a data receiving, analyzing and matching module, a target object matching and early warning module, a target object path calibration module, a calibrated path matching and identifying module and a target object path early warning module.

[0007] The target object signal acquisition module comprises an unmanned aerial vehicle database unit, a wireless signal monitoring unit and a target signal acquisition unit, the wifi broadcast signals in the target area are monitored through the hardware equipment, and the target signals in the target area are acquired;

[0008] The data receiving, analyzing and matching module receives the target signals captured in the target signal acquisition unit, and analyzes and matches the target signals with the data stored in the unmanned aerial vehicle database unit;

[0009] The target object matching early warning module receives the matching result in the data receiving analysis matching module, and sends early warning information to the base station management platform when the matching is unsuccessful.

[0010] The target object path calibration module receives the matching result in the data receiving analysis matching module, and calibrates the flight path of the target object when the matching is successful.

[0011] The calibrated path matching identification module analyzes the path deviation and flight time of the target object based on the flight path of the calibrated target object, and obtains the flight anomaly index of the target object.

[0012] The target object path early warning module judges the flight path of the target object based on the flight anomaly index of the target object, and sends early warning information to the base station management platform according to the judgment result.

[0013] Preferably, the target object signal acquisition module monitors the wifi broadcast signal in the target area through a hardware device, and obtains the specific content of the target signal in the target area as follows:

[0014] The unmanned aerial vehicle database unit is used to store the verified unmanned aerial vehicle information and form an unmanned aerial vehicle information sequence.

[0015] The wireless signal monitoring unit monitors the wifi broadcast signal in the target area through a hardware device, and the target area is 1-3km around the hardware device.

[0016] The target signal acquisition unit extracts the target field in the frame structure of the wifi broadcast signal, identifies the signal modulation mode, detects the synchronization sequence of the unmanned aerial vehicle, and obtains the target signal in the target area.

[0017] Preferably, the data receiving analysis matching module receives the target signal captured in the target signal acquisition unit, extracts the matching data in the target signal, the matching data includes the unmanned aerial vehicle model, the serial number, the position and the height information, matches the target signal with the data stored in the unmanned aerial vehicle database unit, if the target signal is contained in the data stored in the unmanned aerial vehicle database unit, the matching is successful, if the target signal is not in the data stored in the unmanned aerial vehicle database unit, the matching is unsuccessful.

[0018] Preferably, the target object matching early warning module receives the matching result in the data receiving analysis matching module, and sends early warning information to the base station management platform when the matching is unsuccessful.

[0019] Preferably, the target object path calibration module receives the target object path calibration instruction, and performs smooth analysis on the flight path of the target object, and the specific content is as follows:

[0020] The position coordinates of the flight path of the target object at different time points are marked, and the position coordinates of the target object at different time points are represented as (x t , y t , z t ), t = 1, 2, 3,..., T, wherein t represents the time number, and T represents the total amount of time points;

[0021] The position coordinates of the target object at different time points are analyzed, and the x-axis smooth index, the y-axis smooth index and the z-axis smooth index of the position coordinates of the target object at different time points are obtained.

[0022] Preferably, the expression of the x-axis smooth index is: Wherein λ xt represents the x-axis smooth index of the position coordinates of the target object at different time points, v t represents the flight speed of the target object at different time points, represents the average speed of the target object in the flight path, and θ xt represents the angle between the flight direction of the target object at different time points and the x-axis.

[0023] The expression of the y-axis smooth index is: Wherein λ yt represents the y-axis smooth index of the position coordinates of the target object at different time points, and θ yt represents the angle between the flight direction of the target object at different time points and the y-axis.

[0024] The expression of the z-axis smooth index is: Wherein λ zt represents the z-axis smooth index of the position coordinates of the target object at different time points.

[0025] The smooth coordinates (x t ', y t ', z t ') of the position coordinates of the target object at different time points after the smooth analysis are calculated, and the calculation formula is: (x t ', y t ', z t ') = (λ xt x t , λ yt y t , λ zt z t ).

[0026] Preferably, the specific contents of the path deviation analysis and flight time monitoring of the target object based on the calibrated flight path of the target object by the calibration path matching identification module are as follows:

[0027] Smooth coordinates of the target object at different time points (X t ′, Y t ′, Z t ′), and projection point coordinates of the target object at different time points (X t , Y t , Z t ).

[0028] The vertical distance of the target object at different time points is calculated according to the following formula: wherein D t represents the vertical distance of the target object at different time points.

[0029] The path deviation of the target object is analyzed according to the following formula: wherein L represents the average vertical distance of the target object in the flight path.

[0030] Preferably, the calculation formula of the flight anomaly index of the target object in the calibration path matching identification module is as follows: wherein Mn represents the flight anomaly index of the target object, L represents the average vertical distance of the target object in the flight path, L0 represents the preset vertical distance of the target object in the flight path, S represents the actual flight time of the target object in the flight path, S0 represents the preset flight time of the target object in the flight path, ω l represents the distance weight coefficient, and ω s represents the time weight coefficient.

[0031] Preferably, the target object path early warning module judges the flight path of the target object based on the flight anomaly index of the target object: if the flight anomaly index of the target object is greater than or equal to the preset abnormal response threshold, it is judged that the flight of the target object is abnormal, and the early warning information is sent to the base station management platform, otherwise, it is judged that the flight of the target object is normal.

[0032] An unmanned aerial vehicle monitoring method, comprising the following steps:

[0033] S01: monitoring the wifi broadcast signal in the target area through the hardware device to obtain the target signal in the target area;

[0034] S02: analyzing and matching the target signal with the data stored in the unmanned aerial vehicle database unit;

[0035] S03: sending early warning information to the base station management platform when the matching is unsuccessful according to the matching result;

[0036] S04: calibrating the flight path of the target object when the matching is successful according to the matching result;

[0037] S05: based on the flight path of the target object after calibration, path deviation analysis and flight time monitoring are performed on the target object to obtain the flight abnormality index of the target object;

[0038] S06: abnormality judgment is performed on the flight path of the target object, and warning information is sent to the base station management platform according to the judgment result.

[0039] The technical effects and advantages of the present application are:

[0040] The present application is provided with a target object signal acquisition module, a data receiving and analysis matching module, a target object matching and early warning module, a target object path calibration module, a calibrated path matching and identification module, and a target object path early warning module, which improves the accuracy of target object identification and the timeliness of early warning.

[0041] The target area is monitored by a hardware device to obtain the target signal in the target area and perform analysis and matching, and the base station management platform is sent warning information when the matching is unsuccessful according to the matching result. By monitoring and analyzing the WiFi signal, the system helps to identify potential security threats, reduces the work burden of the management personnel, and improves the management efficiency.

[0042] When the matching is successful, the flight path of the target object is calibrated, and based on the flight path of the target object after calibration, path deviation analysis and flight time monitoring are performed on the target object to obtain the flight abnormality index of the target object. The system can timely discover and warn potential path deviation or abnormal flight during flight, so as to avoid flight accidents. BRIEF DESCRIPTION OF DRAWINGS

[0043] Figure 1 It is a structural schematic diagram of a kind of unmanned plane monitoring system.

[0044] Figure 2 It is a flowchart of a kind of unmanned plane monitoring method. DETAILED DESCRIPTION

[0045] The technical solutions in the present application will be described clearly and completely in the drawings in the present application, and the forms of each structure described in the following embodiments are only examples. The unmanned plane monitoring system and the monitoring method thereof involved in the present application are not limited to each structure described in the following embodiments. All other embodiments obtained by those skilled in the art without creative labor belong to the scope of protection of the present application.

[0046] As Figure 1As shown, the unmanned aerial vehicle monitoring system provided by the present application comprises a target object signal acquisition module, a signal receiving and analysis matching module, a target object matching early warning module, a target object path calibration module, a calibrated path matching identification module and a target object path early warning module.

[0047] The target object signal acquisition module comprises an unmanned aerial vehicle database unit, a wireless signal monitoring unit and a target signal acquisition unit, which monitors the wifi broadcast signal in the target area through a hardware device and acquires the target signal in the target area.

[0048] The data receiving and analysis matching module receives the target signal captured in the target signal acquisition unit and analyzes and matches the target signal with the data stored in the unmanned aerial vehicle database unit.

[0049] The target object matching early warning module receives the matching result in the data receiving and analysis matching module and sends early warning information to the base station management platform when the matching is unsuccessful.

[0050] The target object path calibration module receives the matching result in the data receiving and analysis matching module and calibrates the flight path of the target object when the matching is successful.

[0051] The calibrated path matching identification module analyzes the path deviation and flight time of the target object based on the calibrated flight path of the target object, acquires the flight abnormality index of the target object.

[0052] The target object path early warning module makes an abnormality judgment on the flight path of the target object based on the flight abnormality index of the target object and sends early warning information to the base station management platform according to the judgment result.

[0053] In this embodiment, it needs to be specifically pointed out that the target object signal acquisition module monitors the wifi broadcast signal in the target area through a hardware device and acquires the specific content of the target signal in the target area as follows:

[0054] The unmanned aerial vehicle database unit is used for storing the verified unmanned aerial vehicle information and forming an unmanned aerial vehicle information sequence.

[0055] The wireless signal monitoring unit monitors the wifi broadcast signal in the target area through a hardware device, and the target area is 1-3km around the hardware device.

[0056] The target signal acquisition unit extracts the target field in the frame structure of the wifi broadcast signal, identifies the signal modulation mode and detects the synchronization sequence of the unmanned aerial vehicle, and acquires the target signal in the target area.

[0057] In this embodiment, it needs to be specifically pointed out that the data receiving analysis matching module receives the target signal captured in the target signal acquisition unit, extracts the matching data in the target signal, the matching data includes the unmanned aerial vehicle model, serial number, position and height information, matches the target signal with the data stored in the unmanned aerial vehicle database unit, if the target signal is contained in the data stored in the unmanned aerial vehicle database unit, the matching is successful, if the target signal is not in the data stored in the unmanned aerial vehicle database unit, the matching is unsuccessful.

[0058] In this embodiment, it needs to be specifically pointed out that the target object matching early warning module receives the matching result in the data receiving analysis matching module, sends the target object path calibration instruction when the matching is successful, and sends the early warning information to the base station management platform when the matching is unsuccessful.

[0059] In this embodiment, it needs to be specifically pointed out that the target object path calibration module will change the flight path when the target object encounters an obstacle in the flight process, so that the path calibration of the target object will appear inaccurate, and the smooth trajectory of the target object can be obtained by smooth analysis of the original trajectory of the target object, which can be more prepared to match and identify the calibrated path, receive the target object path calibration instruction, and smooth analysis is performed on the flight path of the target object. The specific content is as follows:

[0060] The position coordinates of the flight path of the target object at different time points are marked, and the position coordinates of the target object at different time points are represented as (x t , y t , z t ), t=1, 2, 3,..., T, wherein t represents the time number, T represents the total amount of time points, x t represents the calibration position of the target object at different time points in the x-axis coordinate, y t represents the calibration position of the target object at different time points in the y-axis coordinate, and z t represents the calibration position of the target object at different time points in the z-axis coordinate.

[0061] The position coordinates of the target object at different time points are smooth analyzed, and the x-axis smooth index, y-axis smooth index and z-axis smooth index of the position coordinates of the target object at different time points are obtained.

[0062] In this embodiment, it needs to be specifically pointed out that the expression of the x-axis smooth index is: Wherein λ xt represents the x-axis smooth index of the position coordinates of the target object at different time points, v t represents the flight speed of the target object at different time points, represents the average speed of the target object in the flight path, and θxt represents the angle between the flight direction of the target object at different time points and the x-axis;

[0063] The expression of the y-axis smoothing index is: where λ yt represents the y-axis smoothing index of the position coordinates of the target object at different time points, represents the average speed of the target object in the flight path, θ yt represents the angle between the flight direction of the target object at different time points and the y-axis;

[0064] When θ yt = 60°, When θ yt = 90°, When θ yt = 120°,

[0065] When θ xt = 60°, When θ xt = 90°, When θ xt = 120°,

[0066] The expression of the z-axis smoothing index is: where λ zt represents the z-axis smoothing index of the position coordinates of the target object at different time points, λ xt represents the x-axis smoothing index of the position coordinates of the target object at different time points, λ yt represents the y-axis smoothing index of the position coordinates of the target object at different time points;

[0067] The smoothed coordinates (x t ', y t ', z t ') of the position coordinates of the target object at different time points after smoothing analysis are calculated, and the calculation formula is: (x t ', y t ', z t ') = (λ xt x t , λ yt y t , λ zt z t ).

[0068] In this embodiment, it needs to be specifically pointed out that the specific content of the path deviation analysis and the flight time monitoring of the target object based on the calibrated flight path of the target object by the calibration path matching identification module is as follows:

[0069] Smoothed coordinates (x) of the target object at different time points t ′,y t ′,z t The coordinates of the projection points of the target object at different time points are (X'), t Y t Z t );

[0070] The coordinates of the projection points of the target object at different time points are (X... t Y t Z t The specific calculation method is as follows: the original coordinates (x0, y0, z0) of the target object are (0, 0, 0), the endpoint coordinates (x, y, z) of the target object are (10, 10, 0), and the smoothed coordinates (x, y, z) of the target object at time t are... t ′,y t ′,z t (5, 6, 0) is given by (′).

[0071] Calculate the direction vector v at time t t =(x t -x0, y t ′-y0,z t ′-z0)=(10,10,0), calculate vector w t =(x-x0,y-y0,z-z0)=(5,6,0);

[0072] The projection scale of the target object at time t is calculated using the following formula:

[0073] The coordinates of the projection points of the target object at different time points are (X t Y t Z t )=(x0+ε t (x-x0), y0+ε t (y-y0), z0+ε t (z-z0))=(0+0.55×10, 0+0.55×10, 0);

[0074] The formula for calculating the vertical distance of a target object at different time points is as follows: Where D t This represents the vertical distance of the target object at different points in time.

[0075] The path deviation analysis for the target object is performed using the following formula: Where L represents the average vertical distance of the target object in the flight path.

[0076] In the embodiment, it needs to be specifically pointed out that the calculation formula of the flight abnormality index of the target object in the calibration path matching identification module is: Wherein, Mn represents the flight abnormality index of the target object, L represents the average vertical distance of the target object in the flight path, L0 represents the preset vertical distance of the target object in the flight path, S represents the actual flight time of the target object in the flight path, S0 represents the preset flight time of the target object in the flight path, ω l L represents the distance weight coefficient, and ω s S represents the time weight coefficient.

[0077] In the embodiment, it needs to be specifically pointed out that the target object path early warning module judges the flight of the target object based on the flight abnormality index of the target object: if the flight abnormality index of the target object is greater than or equal to the preset abnormal response threshold, it is judged that the flight of the target object is abnormal, and the early warning information is sent to the base station management platform, otherwise, if the flight abnormality index of the target object is less than the preset abnormal response threshold, it is judged that the flight of the target object is normal.

[0078] As Figure 2 shown, in the embodiment, the method for using a kind of unmanned plane monitoring system and monitoring method thereof includes the following steps:

[0079] S01: the wifi broadcast signal in the target area is monitored by hardware equipment, and the target signal in the target area is acquired;

[0080] S02: the target signal is analyzed and matched with the data stored in the unmanned plane database unit;

[0081] S03: when matching unsuccessfully, early warning information is sent to the base station management platform according to the matching result;

[0082] S04: when matching successfully, the flight path of the target object is calibrated according to the matching result;

[0083] S05: based on the calibrated flight path of the target object, the flight path deviation analysis and flight time monitoring of the target object are carried out to obtain the flight abnormality index of the target object;

[0084] S06: the flight path of the target object is judged to be abnormal, and early warning information is sent to the base station management platform according to the judgment result.

[0085] In the embodiment, it needs to be specifically pointed out that the difference between the embodiment and the prior art is mainly that the embodiment is provided with a target object signal acquisition module, a signal receiving and analysis matching module, a target object matching early warning module, a target object path calibration module, a calibrated path matching identification module and a target object path early warning module, thereby improving the accuracy of target object identification and the timeliness of early warning.

[0086] The target area is monitored by the hardware device, the target signal in the target area is acquired and analyzed, the early warning information is sent to the base station management platform when the matching is unsuccessful, the potential security threat is identified by monitoring and analyzing the WiFi signal, the work burden of the management personnel is reduced, and the management efficiency is improved.

[0087] When the matching is successful, the flight path of the target object is calibrated, the flight path deviation analysis and the flight time monitoring are performed based on the calibrated flight path of the target object, the flight abnormal index of the target object is acquired, the abnormality of the flight path of the target object is judged, the system can discover and early warn the potential path deviation or abnormal flight in the flight process, thereby avoiding the flight accident.

[0088] Finally, the above is only the preferred embodiment of the present application, and is not used to limit the present application, any modification, equivalent replacement, improvement, etc. within the spirit and principle of the present application should be included in the protection scope of the present application.

[0089] The above is only the specific embodiment of the present application, but the protection scope of the present application is not limited to this, any person skilled in the art can easily think of the change or replacement within the technical range disclosed by the present application, which should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be subject to the protection scope of the claims.

Claims

1. A drone monitoring system, characterized in that, include: The system includes a target object signal acquisition module, a data receiving, analysis and matching module, a target object matching and early warning module, a target object path calibration module, a calibration path matching and identification module, and a target object path early warning module. The target signal acquisition module includes a UAV database unit, a wireless signal monitoring unit, and a target signal acquisition unit. It monitors the Wi-Fi broadcast signal in the target area through hardware devices and acquires the target signal in the target area. The data receiving, analysis and matching module receives the target signal captured by the target signal acquisition unit and analyzes and matches the target signal with the data stored in the UAV database unit. The target object matching early warning module receives and analyzes the matching results in the data receiving and matching module, and sends early warning information to the base station management platform when the matching fails. The target object path identification module receives and analyzes the matching results from the data receiving and matching module, and identifies the flight path of the target object when the matching is successful. Upon receiving the target object path calibration command, perform a smoothing analysis on the target object's flight path, as detailed below: The flight path of the target object is marked with position coordinates at different time points, and the position coordinates of the target object at different time points are represented as , t = 1, 2, 3,..., T, wherein t represents a time number, and T represents the total amount of time points. Smoothing analysis is performed on the position coordinates of the target object at different time points, and the smoothing index of the x-axis, y-axis and z-axis of the position coordinates of the target object at different time points are obtained respectively; The expression for the x-axis smoothing exponent is: ,in This represents the x-axis smoothing exponent of the target object's position coordinates at different time points. This indicates the flight speed of the target object at different points in time. This represents the average speed of the target object along its flight path. This indicates the angle between the target object's flight direction and the x-axis at different points in time; The expression for the y-axis smoothing exponent is: ,in This represents the y-axis smoothing exponent of the target object's position coordinates at different time points. This indicates the angle between the target object's flight direction and the y-axis at different points in time; The expression for the z-axis smoothing exponent is: ,in The z-axis smoothing exponent represents the position coordinates of the target object at different time points; Smoothed coordinates after calculating the position coordinates of the target object at different time points and performing smoothing analysis The calculation formula is: ; The calibration path matching and identification module performs path deviation analysis and flight time monitoring on the calibrated target object to obtain the target object's flight anomaly index. The target object path early warning module determines the anomaly of the target object's flight path based on the target object's flight anomaly index and sends early warning information to the base station management platform based on the determination result.

2. The UAV monitoring system according to claim 1, characterized in that: The target signal acquisition module monitors the Wi-Fi broadcast signal within the target area using hardware devices, and obtains the specific content of the target signal within the target area as follows: Drone database unit: used to store verified drone information and form drone information sequences; Wireless signal monitoring unit: Monitors Wi-Fi broadcast signals within a target area via hardware devices, where the target area is within 1-3 km of the hardware devices; Target signal acquisition unit: Extracts the target field from the Wi-Fi broadcast signal frame structure, identifies the signal modulation method and detects the synchronization sequence of the UAV, and acquires the target signal within the target area.

3. The UAV monitoring system according to claim 1, characterized in that: The data receiving, analysis and matching module receives the target signal captured by the target signal acquisition unit, extracts matching data from the target signal, and the matching data includes the UAV model, serial number, location and altitude information. The target signal is then matched with the data stored in the UAV database unit. If the target signal is included in the data stored in the UAV database unit, the match is successful; otherwise, the match is unsuccessful.

4. The UAV monitoring system according to claim 1, characterized in that: The target object matching early warning module receives and analyzes the matching results in the data receiving and matching module. When the matching is successful, it issues a target object path marking instruction, and when the matching is unsuccessful, it sends an early warning message to the base station management platform.

5. The UAV monitoring system according to claim 1, characterized in that: The calibration path matching and identification module performs path deviation analysis and flight time monitoring of the target object based on the calibrated flight path of the target object, as follows: Smooth coordinates of the target object at different time points The coordinates of the projection points of the target object at different time points are: ; The formula for calculating the vertical distance of a target object at different time points is as follows: ,in This represents the vertical distance of the target object at different points in time. The path deviation analysis for the target object is performed using the following formula: , where L represents the average vertical distance of the target object in the flight path.

6. The UAV monitoring system according to claim 5, characterized in that: The formula for calculating the flight anomaly index of the target object in the calibration path matching and identification module is as follows: ,in Indicates the flight anomaly index of the target object. This represents the average vertical distance of the target object along its flight path. This indicates the preset vertical distance of the target object in the flight path. This indicates the actual flight time of the target object within its flight path. This indicates the preset flight time of the target object within its flight path. This represents the distance weighting coefficient. This represents the time weighting coefficient.

7. The UAV monitoring system according to claim 1, characterized in that: The target object path early warning module determines the abnormality of the target object's flight path based on the target object's flight abnormality index: if the target object's flight abnormality index is greater than or equal to a preset abnormal response threshold, the target object's flight is determined to be abnormal, and an early warning message is sent to the base station management platform; otherwise, the target object's flight is determined to be normal.

8. A method for monitoring unmanned aerial vehicles (UAVs), used with an UAV monitoring system according to any one of claims 1-7, characterized in that: Includes the following steps: S01: Monitor the Wi-Fi broadcast signal within the target area using hardware devices to obtain the target signal within the target area; S02: Analyze and match the target signal with the data stored in the UAV database unit; S03: Send an early warning message to the base station management platform when the matching fails based on the matching results; S04: Based on the matching results, the flight path of the target object is marked when the matching is successful; Upon receiving the target object path calibration command, perform a smoothing analysis on the target object's flight path, as detailed below: The flight path of the target object is marked with position coordinates at different time points, and the position coordinates of the target object at different time points are represented as follows: t = 1, 2, 3, ..., T, where t represents the time number and T represents the total number of time points; Smoothing analysis is performed on the position coordinates of the target object at different time points, and the smoothing index of the x-axis, y-axis and z-axis of the position coordinates of the target object at different time points are obtained respectively; The expression for the x-axis smoothing exponent is: ,in This represents the x-axis smoothing exponent of the target object's position coordinates at different time points. This indicates the flight speed of the target object at different points in time. This represents the average speed of the target object along its flight path. This indicates the angle between the target object's flight direction and the x-axis at different points in time; The expression for the y-axis smoothing exponent is: ,in This represents the y-axis smoothing exponent of the target object's position coordinates at different time points. This indicates the angle between the target object's flight direction and the y-axis at different points in time; The expression for the z-axis smoothing exponent is: ,in The z-axis smoothing exponent represents the position coordinates of the target object at different time points; Smoothed coordinates after calculating the position coordinates of the target object at different time points and performing smoothing analysis The calculation formula is: ; S05: Based on the calibrated flight path of the target object, perform path deviation analysis and flight time monitoring to obtain the flight anomaly index of the target object; S06: Detect anomalies in the flight path of the target object and send early warning information to the base station management platform based on the detection results.

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