Unmanned aerial vehicle identification and positioning method and system, electronic equipment and storage medium

Abstract

The invention provides an unmanned aerial vehicle identification and positioning method and system, electronic equipment and a storage medium, and the method comprises the steps: all TDOA stations receive signals in a monitoring range; acquiring a target unmanned aerial vehicle signal and a remote controller signal of the target unmanned aerial vehicle based on the signal; acquiring initial positioning of the target unmanned aerial vehicle and identity characteristics of the target unmanned aerial vehicle based on the target unmanned aerial vehicle signal; acquiring initial positioning of the remote controller based on the remote controller signal; based on the initial positioning of the remote controller and the initial positioning of the target unmanned aerial vehicle, obtaining a video of the target unmanned aerial vehicle and a video of a pilot at the remote controller; identifying the type of the target unmanned aerial vehicle based on the video of the target unmanned aerial vehicle; recording a video of a flying hand at the remote controller; acquiring second positioning of the target unmanned aerial vehicle based on the video of the target unmanned aerial vehicle; and obtaining the target location of the target unmanned aerial vehicle based on the second location of the target unmanned aerial vehicle and the initial location of the target unmanned aerial vehicle. Therefore, the identification and positioning precision of the target unmanned aerial vehicle is improved.

Description

Technical Field

[0001] This invention relates to the field of identification and positioning technology, and in particular to a method and system for identifying and positioning unmanned aerial vehicles (UAVs), an electronic device, and a storage medium. Background Technology

[0002] Unmanned aerial vehicle (UAV) identification refers to the use of various sensors and technologies to detect, discover, and confirm aerial targets, determining whether they are UAVs and further acquiring their specific attributes, such as model, serial number, and operator information. UAV positioning, based on identification, involves accurately measuring the target's real-time three-dimensional coordinates (longitude, latitude, and altitude) and its motion parameters such as speed and heading. To promote the development of the low-altitude economy, UAV identification and positioning technologies have been widely applied in key areas such as airports, military facilities, and no-fly zones, significantly enhancing airspace safety and security capabilities.

[0003] However, relying solely on radio monitoring of drones has limitations in terms of accuracy in identifying and locating them. Summary of the Invention

[0004] This invention provides a method and system for identifying and locating unmanned aerial vehicles (UAVs), an electronic device, and a storage medium, thereby improving the accuracy of UAV identification and location.

[0005] According to a first aspect of the present invention, the technical solution of the present invention provides a method for identifying and locating unmanned aerial vehicles (UAVs), characterized in that it includes: Each TDOA station receives signals within its monitoring range, and the number of TDOA stations is greater than 3; Based on the aforementioned signals, the target drone signal and the remote controller signal of the target drone are obtained; Based on the target drone signal, the initial location and identity characteristics of the target drone are obtained, including the model and serial number of the target drone; Based on the remote control signal, the initial positioning of the remote control is obtained; Based on the initial location of the target drone and the initial location of the remote controller, at least two drones in the drone library are assigned to fly to the initial location of the target drone and the initial location of the remote controller, respectively. The target drone is recorded by a gimbal camera on a drone that flies to the initial location of the target drone; The drone, flying to the initial position of the remote controller, records the pilot's video at the remote controller via a gimbal camera. Based on the video recording of the target drone, the model of the target drone is identified to confirm the identity characteristics of the target drone, and the identity characteristics of the target drone are recorded. Record the video of the pilot. Based on the video recording of the target drone, the second location of the target drone is obtained; Based on the second positioning and the initial positioning of the target UAV, the target positioning of the target UAV is obtained.

[0006] Optionally, based on the signal, acquiring the target drone signal and the remote controller signal of the target drone includes: Based on the signal, the frequency range of the signal is obtained; Based on the frequency range, the signal is divided into the drone signal and the remote controller signal. The frequency range of the remote controller signal is 2400MHz-2483.5MHz, 5150MHz-5250MHz, and 5725MHz-5850MHz, and the frequency range of the remote controller signal is 902MHz-928MHz. Optionally, based on the target drone signal, the initial positioning of the target drone is obtained, including: Based on the target drone signal, the time when the target drone signal arrives at each of the TDOA stations is obtained; Based on the time when the target UAV signal arrives at each of the TDOA stations, the time difference when the target UAV signal arrives at each pair of different TDOA stations is obtained; The initial location of the drone is obtained based on the time difference between the arrival of the target drone signal at all the different TDOA stations.

[0007] Optionally, based on the remote control signal, obtaining the initial positioning of the remote control includes: Based on the remote control signal, the time when the remote control signal arrives at each of the TDOA stations is obtained; Based on the time when the remote control signal arrives at each of the TDOA stations, the time difference when the remote control signal arrives at each pair of different TDOA stations is obtained; The initial positioning of the remote controller is obtained based on the time difference between the arrival times of the remote controller signal at all the different TDOA stations.

[0008] Optional, including: A detection and positioning result information frame is generated based on the initial positioning of the target UAV and the initial positioning of the remote controller; The detection and positioning result information frame is sent to the backend server; The backend server generates an allocation signal based on the detection and positioning result information frame. The backend server sends the allocation signal to the drone library to control the drone library to allocate at least two drones to fly to the initial position of the target drone and the initial position of the remote controller.

[0009] Optionally, based on the video recording of the target drone, the model of the target drone is identified, including: The video recording of the target drone is processed to remove noise from the video recording and acquire drone images; The drone images are analyzed using a deep learning model to identify the model of the target drone.

[0010] Optionally, the method further includes: Obtain the registration information of the drone pilot; Based on the pilot's registration information and the pilot's video recording, determine whether the pilot is flying illegally. If the drone pilot is registered in the video recording, then the drone pilot is flying legally; If the drone pilot is not registered in the video recording, then the drone pilot is flying illegally.

[0011] According to a second aspect of the present invention, the technical solution of the present invention provides a drone identification and positioning system for implementing the above-mentioned drone identification and positioning method, comprising: The monitoring module includes a TDOA submodule and a first data processing submodule. The TDOA submodule includes three or more TDOA stations, each of which receives signals within its monitoring range and sends the signals to the first data processing submodule. The first data processing submodule receives the signals and, based on the signals, acquires the target drone signal and the remote controller signal. The first data processing submodule is also used to acquire the initial location and identity characteristics of the target drone based on the target drone signal, the identity characteristics including the drone's model and serial number. The first data processing submodule also acquires the initial location of the remote controller based on the remote controller signal. Furthermore, the first data processing submodule sends the initial location of the target drone, the target drone's identity characteristics, and the initial location of the remote controller to a backend server and a second data processing submodule. The backend server is used to send an allocation signal to the drone library based on the initial location of the target drone, the identity characteristics of the target drone, and the initial location of the remote controller after receiving the initial location of the target drone and the initial location of the remote controller. The drone library is used to receive the allocation signal and, based on the allocation signal, allocate at least two drones in the drone library to fly to the initial position of the target drone and the initial position of the remote controller, respectively. The drone library includes several drones, each equipped with a gimbal camera. The gimbal camera on the drone flying to the initial position of the target drone records video of the target drone, and the gimbal camera on the drone flying to the initial position of the remote controller records video of the pilot at the remote controller. The video of the target drone and the video of the pilot at the remote controller are then uploaded to the second data processing submodule. The second data processing submodule is used to identify the model of the target drone based on the video recording of the target drone, so as to confirm the identity characteristics of the target drone and record the identity characteristics of the target drone; to record the video recording of the pilot; to obtain the second location of the target drone based on the video recording of the target drone; and to obtain the target location of the target drone based on the second location and the initial location of the target drone.

[0012] According to a third aspect of the invention, the invention also provides an electronic device, including a memory and a processor. The memory is used to store code; The processor is used to execute the code in the memory to implement the UAV identification and positioning method described in any of the above-mentioned methods.

[0013] According to a fourth aspect of the invention, the invention also provides a storage medium having a program stored thereon, the program being executed by a processor of the unmanned aerial vehicle identification and positioning method described in any of the preceding claims.

[0014] Compared with the prior art, the technical solution of the embodiments of the present invention has the following beneficial effects: In the UAV identification and positioning method, system, electronic device, and storage medium of this invention, each TDOA station receives signals within its monitoring range; based on these signals, the target UAV signal and the remote controller signal are acquired; based on the target UAV signal, the initial positioning and identity characteristics of the target UAV are acquired, including the target UAV's model and serial number; based on the remote controller signal, the initial positioning of the remote controller is acquired; thus, a rough initial positioning and initial identification of the target UAV and the remote controller are achieved. Furthermore, based on the initial positioning of the target UAV and the remote controller, at least two UAVs from the UAV library are assigned to fly to the initial positioning of the target UAV and the initial positioning of the remote controller, respectively; the gimbal camera on the UAV flying to the initial positioning of the target UAV records video of the target UAV; the gimbal camera on the UAV flying to the initial positioning of the remote controller records video of the pilot at the remote controller. Thus, video recordings of the target UAV and the pilot at the remote controller are obtained. Based on this, on the one hand, by identifying the target drone's model based on its video recording, the target drone's identity is confirmed and its characteristics are recorded. Therefore, using the target drone's video recording to confirm its identity improves the accuracy of target drone identification, and the target drone's identity characteristics are stored. On the other hand, the pilot's video is recorded, thus facilitating subsequent evidence collection. Furthermore, by obtaining the target drone's target location based on its second and initial positioning, the target drone's positioning accuracy is improved through multi-source data fusion. Attached Figure Description

[0015] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0016] Figure 1 This is a flowchart illustrating the method for identifying and locating drones in an embodiment of the present invention; Figure 2 This is a schematic diagram of the structure of the drone identification and positioning system in an embodiment of the present invention. Detailed Implementation

[0017] As in the background technology, relying solely on radio monitoring of drones has limitations in terms of accuracy in identifying and locating them.

[0018] In view of this, the present invention provides a method for identifying and locating unmanned aerial vehicles (UAVs). Based on signals, it acquires the target UAV signal and the remote controller signal; based on the target UAV signal, it acquires the initial location and identity characteristics of the target UAV, including its model and serial number; based on the remote controller signal, it acquires the initial location and serial number of the remote controller; based on the initial location of the target UAV and the initial location of the remote controller, it assigns at least two UAVs from the UAV library to fly to the initial locations of the target UAV and the remote controller, respectively; it records video of the target UAV using a gimbal camera on the UAV flying to the initial location of the target UAV; it records video of the pilot at the remote controller using a gimbal camera on the UAV flying to the initial location of the remote controller; based on the video recording of the target UAV, it identifies the UAV model to confirm the identity characteristics of the target UAV and records the identity characteristics; it records the video of the pilot; based on the video recording of the target UAV, it acquires a second location of the target UAV; based on the second location and the initial location of the target UAV, it acquires the target location of the target UAV. This achieves improved accuracy in identifying and locating target UAVs by utilizing multi-source data.

[0019] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the scope of protection of the present invention.

[0020] The terms “first,” “second,” “third,” “fourth,” etc. (if present) in the specification, claims, and accompanying drawings of this invention are used to distinguish similar objects and are not necessarily used to describe a particular order or sequence. It should be understood that such data can be interchanged where appropriate so that embodiments of the invention described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms “comprising” and “having,” and any variations thereof, are intended to cover a non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0021] The technical solution of the present invention will be described in detail below with reference to specific embodiments. These specific embodiments can be combined with each other, and the same or similar concepts or processes may not be described again in some embodiments.

[0022] To make the above-mentioned objectives, features and beneficial effects of the present invention more apparent and understandable, specific embodiments of the present invention will be described in detail below with reference to the accompanying drawings.

[0023] Please refer to Figure 1 This invention provides a method for identifying and locating unmanned aerial vehicles (UAVs), including: S100: Each TDOA station receives signals within the monitoring range, and the number of TDOA stations is greater than 3; S200: Based on signals, acquires the target drone signal and the remote controller signal of the target drone; S300: Based on the target drone signal, obtain the initial location and identification characteristics of the target drone, including the model and serial number of the target drone; S400: Obtain the initial positioning of the remote control based on the remote control signal; S500: Based on the initial positioning of the target UAV and the initial positioning of the remote controller, assign at least two UAVs in the UAV library to fly to the initial positioning of the target UAV and the initial positioning of the remote controller, respectively. S600: Records video of the target drone using a gimbal camera on a drone that flies to the initial location of the target drone; S700: Records video of the pilot at the remote control via the gimbal camera on the drone as it flies to the initial position of the remote control. S800: Based on the video recording of the target drone, identify the model of the target drone to confirm its identity and record its identity characteristics; S900: Records the video of the pilot; S1000: Obtain the second location of the target drone based on the video recording of the target drone; S1100: Based on the second positioning and the initial positioning of the target UAV, obtain the target positioning of the target UAV.

[0024] As can be seen, this embodiment provides a method for identifying and locating unmanned aerial vehicles (UAVs). By utilizing signals received from each TDOA (Digital Transmission Office) station within the monitoring range, and based on the target UAV signal and remote controller signal obtained from these signals, the initial location of the target UAV, its identity characteristics, and the initial location of the remote controller are obtained, achieving a rough initial location and initial identification of the target UAV and remote controller. The target UAV is recorded by a gimbal camera on a UAV flying to its initial location; the pilot at the remote controller is recorded by a gimbal camera on a UAV flying to its initial location; thus, the video recordings of the target UAV and the pilot at the remote controller are obtained. The target UAV's identity characteristics are confirmed using the video recordings, improving the accuracy of target UAV identification, and the target UAV's identity characteristics are stored. Finally, by fusing the second location obtained from the target UAV's video recordings with the initial location, the positioning accuracy of the target UAV is improved.

[0025] As one embodiment, in S200, based on signals, the target drone signal and the remote controller signal are acquired, including: S210: Based on the signal, obtain the frequency range of the signal; S220: The signal is divided into a drone signal and a remote controller signal based on the frequency range. The frequency range of the remote controller signal is 2400MHz-2483.5MHz, 5150MHz-5250MHz, and 5725MHz-5850MHz, and the frequency range of the remote controller signal is 902MHz-928MHz. As a specific embodiment, in S300, the initial positioning of the target drone is obtained based on the target drone signal, including: S310: Based on the target drone signal, obtain the time when the target drone signal arrives at each TDOA station; S320: Based on the arrival time of the target UAV signal at each TDOA station, obtain the time difference between the arrival times of the target UAV signal at each different TDOA station; S330: Obtain the initial positioning of the drone based on the time difference between the arrival times of the target drone signal at all the different TDOA stations.

[0026] As an example, in the S400, the initial positioning of the remote control is obtained based on the remote control signal, including: S410: Based on the remote control signal, obtain the time when the remote control signal arrives at each TDOA station; S420: Based on the time when the remote control signal arrives at each TDOA station, obtain the time difference when the remote control signal arrives at each different TDOA station; S430: Obtain the initial positioning of the remote control based on the time difference between the arrival times of the remote control signal at all the different TDOA stations.

[0027] In this embodiment, obtaining the initial location of the remote controller is to locate the position of the pilot holding the remote controller.

[0028] As an example, in the S400, the method for obtaining the remote control serial number based on the remote control signal is to identify it through the center frequency of the remote control signal.

[0029] As one implementation method, this embodiment also includes: S440: Generate a detection and positioning result information frame based on the initial positioning of the target UAV and the initial positioning of the remote controller; S450: Sends the initial positioning of the target UAV, the initial positioning of the remote controller, and the detection and positioning result information frames to the backend server. S460: The backend server generates an allocation signal based on the detection and positioning result information frame; S470: The backend server sends the allocation signal to the drone library to control the drone library to allocate at least two drones to fly to the initial position of the target drone and the initial position of the remote controller.

[0030] As a specific implementation method, S800: Based on the video recording of the target drone, identify the model of the target drone, including: S810: Process the video recording of the target drone to remove noise from the video recording of the target drone and acquire drone images; S820: Analyzes drone imagery using a deep learning model to identify the model of the target drone.

[0031] As an example, a Transformer can be used to process the video recording of the target drone to remove video noise. Of course, this invention is not limited to this; this embodiment can also use a variant model of the Transformer to process the video recording of the target drone to remove video noise.

[0032] As a specific embodiment, the method for identifying and locating drones may further include: S910: Obtain the registration information of the pilot; S920: Based on the pilot's registration information and the pilot's video recording, determine whether the pilot is flying illegally; If the drone pilot is registered in the video recording, then the drone pilot is flying legally; If the drone pilot is not registered in the video recording, then the drone pilot is flying illegally.

[0033] In summary, in this embodiment, since each TDOA station receives signals within its monitoring range; based on these signals, the target drone signal and the remote controller signal are obtained; based on the target drone signal, the initial location and identity characteristics of the target drone are obtained, including the drone's model and serial number; based on the remote controller signal, the initial location of the remote controller is obtained; therefore, a rough initial location and initial identification of the target drone and the remote controller are achieved. Furthermore, based on the initial location of the target drone and the initial location of the remote controller, at least two drones from the drone library are assigned to fly to the initial locations of the target drone and the remote controller, respectively; the gimbal camera on the drone flying to the initial location of the target drone records video of the target drone; the gimbal camera on the drone flying to the initial location of the remote controller records video of the pilot at the remote controller. Thus, video recordings of the target drone and the pilot at the remote controller are obtained. Based on this, on the one hand, by identifying the target drone's model based on its video recording, the target drone's identity is confirmed and its characteristics are recorded. Therefore, using the target drone's video recording to confirm its identity improves the accuracy of target drone identification, and the target drone's identity characteristics are stored. On the other hand, the pilot's video is recorded, thus facilitating subsequent evidence collection. Furthermore, by obtaining the target drone's target location based on its second and initial positioning, the target drone's positioning accuracy is improved through multi-source data fusion.

[0034] Furthermore, embodiments of the present invention also provide a drone identification and positioning system for implementing the aforementioned drone identification and positioning method, comprising: The monitoring module 10 includes a TDOA submodule 11 and a first data processing submodule 12. The TDOA submodule 11 includes three or more TDOA stations, each of which receives signals within its monitoring range and sends the signals to the first data processing submodule 12. The first data processing submodule 12 receives the signals and, based on the signals, acquires the target drone signal and the remote controller signal. The first data processing submodule 12 is also used to acquire the initial location and identity characteristics of the target drone based on the target drone signal. The identity characteristics of the target drone include the model and serial number of the target drone. The first data processing submodule 12 is also used to acquire the initial location of the remote controller based on the remote controller signal. The first data processing submodule 12 is also used to send the initial location of the target drone, the identity characteristics of the target drone, and the initial location of the remote controller to the backend server and the second data processing submodule. The backend server 20 is used to send an allocation signal to the drone library based on the initial positioning of the target drone, the identity characteristics of the target drone, and the initial positioning of the remote controller after receiving the initial positioning of the target drone and the initial positioning of the remote controller. The drone pool 30 is used to receive allocation signals and, based on the allocation signals, allocate at least two drones in the drone pool to fly to the initial position of the target drone and the initial position of the remote controller, respectively. The drone pool includes several drones, each equipped with a gimbal camera. The gimbal camera on the drone flying to the initial position of the target drone records video of the target drone, and the gimbal camera on the drone flying to the initial position of the remote controller records video of the pilot at the remote controller. The video of the target drone and the video of the pilot at the remote controller are then uploaded to the second data processing submodule. The second data processing submodule 40 is used to identify the model of the target drone based on the video recording of the target drone, so as to confirm the identity characteristics of the target drone and record the identity characteristics of the target drone; to record the video recording of the pilot; to obtain the second location of the target drone based on the video recording of the target drone; and to obtain the target location of the target drone based on the second location and the initial location of the target drone.

[0035] Embodiments of the present invention also provide an electronic device, including a memory and a processor. Memory, used to store code; A processor for executing code in memory to implement the method for identification and positioning of unmanned aerial vehicles as described above.

[0036] Furthermore, embodiments of the present invention also provide a storage medium on which a program is stored, which, when executed by a processor, implements the aforementioned method for identifying and locating unmanned aerial vehicles.

[0037] While the present invention has been disclosed above, it is not limited thereto. Any person skilled in the art can make various modifications and alterations without departing from the spirit and scope of the invention; therefore, the scope of protection of the present invention should be determined by the scope defined in the claims.

Claims

1. A method for identifying and locating unmanned aerial vehicles (UAVs), characterized in that, include: Each TDOA station receives signals within its monitoring range, and the number of TDOA stations is greater than 3; Based on the aforementioned signals, the target drone signal and the remote controller signal of the target drone are obtained; Based on the target drone signal, the initial location and identity characteristics of the target drone are obtained, including the model and serial number of the target drone; Based on the remote control signal, the initial positioning of the remote control is obtained; Based on the initial location of the target drone and the initial location of the remote controller, at least two drones in the drone library are assigned to fly to the initial location of the target drone and the initial location of the remote controller, respectively. The target drone is recorded by a gimbal camera on a drone that flies to the initial location of the target drone; The drone, flying to the initial position of the remote controller, records the pilot's video at the remote controller via a gimbal camera. Based on the video recording of the target drone, the model of the target drone is identified to confirm the identity characteristics of the target drone, and the identity characteristics of the target drone are recorded. Record the video of the pilot. Based on the video recording of the target drone, the second location of the target drone is obtained; Based on the second positioning and the initial positioning of the target UAV, the target positioning of the target UAV is obtained.

2. The method for identifying and locating unmanned aerial vehicles (UAVs) as described in claim 1, characterized in that, Based on the aforementioned signal, the target drone signal and the remote controller signal are acquired, including: Based on the signal, the frequency range of the signal is obtained; Based on the frequency range, the signal is divided into the drone signal and the remote controller signal. The frequency range of the remote controller signal is 2400MHz-2483.5MHz, 5150MHz-5250MHz, and 5725MHz-5850MHz, and the frequency range of the remote controller signal is 902MHz-928MHz.

3. The method for identifying and locating unmanned aerial vehicles (UAVs) as described in claim 1, characterized in that, Based on the target drone signal, the initial location of the target drone is obtained, including: Based on the target drone signal, the time when the target drone signal arrives at each of the TDOA stations is obtained; Based on the time when the target UAV signal arrives at each of the TDOA stations, the time difference when the target UAV signal arrives at each pair of different TDOA stations is obtained; The initial location of the drone is obtained based on the time difference between the arrival of the target drone signal at all the different TDOA stations.

4. The method for identifying and locating unmanned aerial vehicles (UAVs) as described in claim 1, characterized in that, Based on the remote control signal, the initial positioning of the remote control is obtained, including: Based on the remote control signal, the time when the remote control signal arrives at each of the TDOA stations is obtained; Based on the time when the remote control signal arrives at each of the TDOA stations, the time difference when the remote control signal arrives at each pair of different TDOA stations is obtained; The initial positioning of the remote controller is obtained based on the time difference between the arrival times of the remote controller signal at all the different TDOA stations.

5. The method for identifying and locating unmanned aerial vehicles (UAVs) as described in claim 1, characterized in that, include: A detection and positioning result information frame is generated based on the initial positioning of the target UAV and the initial positioning of the remote controller; The detection and positioning result information frame is sent to the backend server; The backend server generates an allocation signal based on the detection and positioning result information frame. The backend server sends the allocation signal to the drone library to control the drone library to allocate at least two drones to fly to the initial position of the target drone and the initial position of the remote controller.

6. The method for identifying and locating unmanned aerial vehicles (UAVs) as described in claim 1, characterized in that, Based on the video recording of the target drone, the model of the target drone is identified, including: The video recording of the target drone is processed to remove noise from the video recording and acquire drone images; The drone images are analyzed using a deep learning model to identify the model of the target drone.

7. The method for identifying and locating unmanned aerial vehicles (UAVs) as described in claim 1, characterized in that, The method further includes: Obtain the registration information of the drone pilot; Based on the pilot's registration information and the pilot's video recording, determine whether the pilot is flying illegally. If the drone pilot is registered in the video recording, then the drone pilot is flying legally; If the drone pilot is not registered in the video recording, then the drone pilot is flying illegally.

8. A system for identifying and locating unmanned aerial vehicles (UAVs), characterized in that, include: The monitoring module includes a TDOA submodule and a first data processing submodule. The TDOA submodule includes three or more TDOA stations. Each TDOA station receives signals within its monitoring range and sends the signals to the first data processing submodule. The first data processing submodule receives the signals and, based on the signals, acquires the target drone signal and the remote controller signal of the target drone. The first data processing submodule is further configured to obtain the initial location and identity features of the target drone based on the target drone signal, wherein the identity features of the target drone include the model and serial number of the target drone; the first data processing submodule is configured to obtain the initial location of the remote controller based on the remote controller signal; the first data processing submodule is further configured to send the initial location of the target drone, the identity features of the target drone, and the initial location of the remote controller to the background server and the second data processing submodule; The backend server is used to send an allocation signal to the drone library based on the initial location of the target drone, the identity characteristics of the target drone, and the initial location of the remote controller after receiving the initial location of the target drone and the initial location of the remote controller. The drone library is used to receive the allocation signal and, based on the allocation signal, allocate at least two drones in the drone library to fly to the initial position of the target drone and the initial position of the remote controller, respectively. The drone library includes several drones, each equipped with a gimbal camera. The gimbal camera on the drone flying to the initial position of the target drone records video of the target drone, and the gimbal camera on the drone flying to the initial position of the remote controller records video of the pilot at the remote controller. The video of the target drone and the video of the pilot at the remote controller are then uploaded to the second data processing submodule. The second data processing submodule is used to identify the model of the target drone based on the video recording of the target drone, so as to confirm the identity characteristics of the target drone and record the identity characteristics of the target drone; to record the video recording of the pilot; to obtain the second location of the target drone based on the video recording of the target drone; and to obtain the target location of the target drone based on the second location and the initial location of the target drone.

9. An electronic device, characterized in that, Including memory and processor, The memory is used to store code; The processor is configured to execute the code in the memory to implement the identification and positioning method for unmanned aerial vehicles as described in any one of claims 1 to 7.

10. A storage medium having a program stored thereon, characterized in that, When executed by the processor, the program implements the method for identifying and locating the UAV as described in any one of claims 1 to 7.

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