Identity recognition method and device of unmanned aerial vehicle, storage medium and electronic equipment

Abstract

The invention discloses an identity recognition method and device of an unmanned aerial vehicle, a storage medium and electronic equipment. The method relates to the technical field of safety, and comprises the steps that first identity information of a target unmanned aerial vehicle to return is acquired, and the first identity information at least comprises flight parameters and energy consumption parameters of the target unmanned aerial vehicle; performing identity verification on the first identity information according to multiple pieces of second identity information in a target database to obtain a first verification result; under the condition that the first verification result represents that verification is passed, secondary identity verification is carried out according to the external image and the internal image of the target unmanned aerial vehicle, a second verification result is obtained, and the second verification result is used for representing whether identity verification of the target unmanned aerial vehicle is passed or not. Through the method and the device, the problem of relatively low accuracy of identity recognition of the unmanned aerial vehicle caused by identity recognition through the ID of the unmanned aerial vehicle in related technologies is solved.

Description

Technical Field

[0001] The present application relates to the field of security technology, and more specifically, to an identity recognition method and device for a drone, a storage medium, and an electronic device. Background Art

[0002] A drone identification system is a system used to determine the identity and attributes of drones, and is designed to monitor and manage drones in the air. Many drone identification systems have been developed, and these drone identification systems generally identify drones through their IDs. Since the drone identification process of the above drone identification systems is relatively simple, it is not conducive to accurately identifying and judging the identities of different models of external drones, resulting in a defect of reduced drone identification accuracy.

[0003] With regard to the problem that the accuracy of drone identification is relatively low due to the use of drone ID in related technologies, no effective solution has been proposed so far. Summary of the invention

[0004] The main purpose of this application is to provide a method and device for identifying a drone, a storage medium and an electronic device, so as to solve the problem in the related art that the accuracy of drone identification is relatively low due to the identification through the drone's ID.

[0005] In order to achieve the above-mentioned purpose, according to one aspect of the present application, a method for identifying the identity of a drone is provided. The method comprises: obtaining the first identity information of the target drone to be returned, wherein the first identity information at least includes the flight parameters and energy consumption parameters of the target drone; performing identity authentication on the first identity information according to multiple second identity information in the target database to obtain a first verification result; when the first verification result indicates that the verification is passed, performing secondary identity authentication according to the external image and internal image of the target drone to obtain a second verification result, wherein the second verification result is used to indicate whether the identity authentication of the target drone is passed.

[0006] Furthermore, obtaining the first identity information of the target UAV to be returned includes: obtaining the body size parameters and body performance parameters of the target UAV; obtaining the flight parameters, energy consumption parameters, and power parameters of the target UAV based on the test data of the target UAV before leaving the factory; and obtaining the first identity information based on the body size parameters, the body performance parameters, the flight parameters, the energy consumption parameters, and the power parameters.

[0007] Furthermore, based on the test data of the target UAV before leaving the factory, obtaining the flight parameters, energy consumption parameters, and power parameters of the target UAV includes: calculating based on the test duration, maximum speed, maximum acceleration, and reference acceleration in the test data to obtain the flight parameters; calculating based on the average rotation speed and test duration in the test data to obtain the power parameters; and calculating based on the average voltage of the battery of the target UAV in the test data to obtain the energy consumption parameters.

[0008] Furthermore, the energy consumption parameters are obtained by calculating according to the average voltage of the battery of the target UAV in the test data, including: obtaining the target battery type, the total battery capacity and the first number of battery groups of the battery of the target UAV; determining the target value corresponding to the target battery type based on the selection function of the UAV battery type; and obtaining the energy consumption parameters by calculating according to the total battery capacity, the first number of battery groups, the average voltage and the target value.

[0009] Furthermore, a secondary identity authentication is performed based on the external image and internal image of the target UAV to obtain a second verification result, including: obtaining size information and shell maintenance information of the target UAV based on the external image of the target UAV; obtaining motor information, the number of second battery packs and cargo information of the target UAV based on the internal image of the target UAV; and a secondary identity authentication is performed based on the size information, the shell maintenance information, the motor information, the number of second battery packs and the cargo information to obtain the second verification result.

[0010] Furthermore, secondary identity verification is performed based on the size information, the shell maintenance information, the motor information, the second number of battery packs and the cargo information to obtain the second verification result, including: performing calculations based on the shell maintenance information and the size information to obtain an external risk value; determining an internal risk value based on the motor information, the second number of battery packs and the cargo information; and performing secondary identity verification based on the external risk value and the internal risk value to obtain the second verification result.

[0011] Furthermore, determining the internal risk value based on the motor information, the second number of battery packs and the cargo information includes: judging whether there is a change in the motor of the target UAV based on the motor information, and obtaining a judgment result; determining the cargo type based on the cargo information; calculating a target difference between the second number of battery packs and the first number of battery packs of the target UAV when it leaves the factory; and determining the internal risk value based on the judgment result, the cargo type and the target difference.

[0012] In order to achieve the above-mentioned purpose, according to another aspect of the present application, a drone identification device is provided. The device comprises: an acquisition unit, used to acquire the first identity information of the target drone to be returned, wherein the first identity information at least includes the flight parameters and energy consumption parameters of the target drone; a first verification unit, used to authenticate the first identity information according to multiple second identity information in the target database to obtain a first verification result; a second verification unit, used to perform secondary identity authentication according to the external image and internal image of the target drone when the first verification result indicates that the verification is passed, to obtain a second verification result, wherein the second verification result is used to indicate whether the identity authentication of the target drone is passed.

[0013] Furthermore, the acquisition unit includes: a first acquisition subunit, used to acquire the body size parameters and body performance parameters of the target UAV; a second acquisition subunit, used to acquire the flight parameters, energy consumption parameters, and power parameters of the target UAV based on the test data of the target UAV before leaving the factory; and a determination subunit, used to obtain the first identity information based on the body size parameters, body performance parameters, the flight parameters, the energy consumption parameters, and the power parameters.

[0014] Furthermore, the second acquisition subunit includes: a first calculation module, used to calculate according to the test time, maximum speed, maximum acceleration and reference acceleration in the test data to obtain the flight parameters; a second calculation module, used to calculate according to the average rotation speed and test time in the test data to obtain the power parameters; a third calculation module, used to calculate according to the average voltage of the battery of the target UAV in the test data to obtain the energy consumption parameters.

[0015] Furthermore, the third calculation module includes: an acquisition submodule, used to obtain the target battery type, total battery capacity and first battery group number of the battery of the target UAV; a first determination submodule, used to determine the target value corresponding to the target battery type based on the selection function of the UAV battery type; and a first calculation submodule, used to calculate according to the total battery capacity, the first battery group number, the average voltage and the target value to obtain the energy consumption parameter.

[0016] Furthermore, the second verification unit includes: a third acquisition subunit, used to acquire size information and shell maintenance information of the target drone based on the external image of the target drone; a fourth acquisition subunit, used to acquire motor information, the number of second battery packs and cargo information of the target drone based on the internal image of the target drone; a verification subunit, used to perform secondary identity authentication based on the size information, the shell maintenance information, the motor information, the number of second battery packs and the cargo information to obtain the second verification result.

[0017] Furthermore, the verification subunit includes: a fourth calculation module, used to calculate based on the shell maintenance information and the size information to obtain an external risk value; a determination module, used to determine the internal risk value based on the motor information, the second number of battery packs and the cargo information; a verification model, used to perform secondary identity authentication based on the external risk value and the internal risk value to obtain the second verification result.

[0018] Furthermore, the determination module includes: a judgment submodule, used to judge whether there is a change in the motor of the target UAV based on the motor information, and obtain a judgment result; a second determination submodule, used to determine the type of cargo based on the cargo information; a second calculation submodule, used to calculate the target difference between the second number of battery packs and the first number of battery packs of the target UAV when it leaves the factory; and a third determination submodule, used to determine the internal risk value based on the judgment result, the cargo type and the target difference.

[0019] In order to achieve the above-mentioned purpose, according to one aspect of the present application, a computer-readable storage medium is provided, wherein the storage medium stores a program, wherein when the program is running, the device where the storage medium is located is controlled to execute any one of the above-mentioned drone identification methods.

[0020] In order to achieve the above-mentioned purpose, according to another aspect of the present application, an electronic device is also provided, the electronic device includes one or more processors and a memory, and the memory is used to store the one or more processors to implement the identity recognition method of the drone described in any one of the above-mentioned items.

[0021] Through this application, the following steps are adopted: obtaining the first identity information of the target drone to be returned, wherein the first identity information at least includes the flight parameters and energy consumption parameters of the target drone; performing identity authentication on the first identity information according to multiple second identity information in the target database to obtain a first verification result; when the first verification result indicates that the verification is passed, performing secondary identity authentication according to the external image and internal image of the target drone to obtain a second verification result, wherein the second verification result is used to indicate whether the identity authentication of the target drone is passed, which solves the problem that the accuracy of drone identity identification is relatively low due to identity identification through the ID of the drone in the related technology. In this scheme, when the drone needs to return, the first identity authentication is performed through the flight parameters and energy consumption parameters of the target drone. When the verification is passed, the secondary identity authentication is performed according to the external image and internal image of the target drone. Finally, it is determined whether the identity authentication of the target drone is passed according to the verification result of the secondary identity authentication. Through the flight parameters, energy consumption parameters, external images and internal images, more dimensions are added to the drone identity identification, thereby achieving the effect of improving the accuracy and stability of the identification process. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] The drawings constituting a part of the present application are used to provide a further understanding of the present application. The illustrative embodiments and descriptions of the present application are used to explain the present application and do not constitute an improper limitation on the present application. In the drawings:

[0023] Figure 1 The following is a flow chart of the method for identifying a drone according to an embodiment of the present application: Figure 1 ;

[0024] Figure 2 The following is a flow chart of the method for identifying a drone according to an embodiment of the present application: Figure 2 ;

[0025] Figure 3 is a schematic diagram of an identity recognition device for a drone provided according to an embodiment of the present application;

[0026] Figure 4 is a schematic diagram of a drone identification system provided according to an embodiment of the present application;

[0027] Figure 5 is a schematic diagram of a drone behavior data entry module provided according to an embodiment of the present application;

[0028] Figure 6 is a schematic diagram of a real-time identification terminal provided according to an embodiment of the present application;

[0029] Figure 7 is a schematic diagram of a real-time identification and analysis module provided according to an embodiment of the present application;

[0030] Figure 8 is a schematic diagram of an electronic device provided according to an embodiment of the present application. DETAILED DESCRIPTION

[0031] It should be noted that, in the absence of conflict, the embodiments and features in the embodiments of the present application can be combined with each other. The present application will be described in detail below with reference to the accompanying drawings and in combination with the embodiments.

[0032] In order to enable those skilled in the art to better understand the solution of the present application, the technical solution in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of the present application.

[0033] It should be noted that the terms "first", "second", etc. in the specification and claims of the present application and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequential order. It should be understood that the data used in this way can be interchanged where appropriate, so that the embodiments of the present application described here. In addition, the terms "including" and "having" and any of their variations are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device comprising a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0034] It should be noted that the relevant information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data for display, data for analysis, etc.) involved in this disclosure are all information and data authorized by the user or fully authorized by all parties. For example, an interface is set between this system and the relevant user or organization. Before obtaining relevant information, it is necessary to send an acquisition request to the aforementioned user or organization through the interface, and obtain relevant information after receiving the consent information fed back by the aforementioned user or organization.

[0035] The present invention is described below in conjunction with preferred implementation steps. Figure 1 The following is a flow chart of the method for identifying a drone according to an embodiment of the present application: Figure 1 ,like Figure 1 As shown, the method comprises the following steps:

[0036] Step S101, obtaining first identity information of a target UAV to be returned, wherein the first identity information at least includes flight parameters and energy consumption parameters of the target UAV.

[0037] Optionally, after the target UAV completes the corresponding mission, the first identity information entered by the user for the UAV can be used to match the identity data of a UAV of the same model. It should be noted that the above-mentioned first identity information includes but is not limited to the flight parameters and energy consumption parameters of the target UAV.

[0038] In an optional embodiment, the flight parameter may be the maximum speed of the drone during a test after production, and the energy consumption parameter may be the average rotation speed of the drone during a test after production.

[0039] Step S102, performing identity verification on the first identity information according to the plurality of second identity information in the target database to obtain a first verification result;

[0040] Optionally, the first identity information is authenticated by using a plurality of second identity information stored in the target database. If there is second identity information identical to the first identity information in the target database, the first verification result indicates that the verification is successful.

[0041] It should be noted that the second identity information in the target database can be obtained by acquiring the identity data of various models of drones after the various models of drones are produced, that is, after the various models of drones are produced, the identity information such as the flight parameters and energy consumption parameters of the drones are obtained, and the identity information is written into the target database.

[0042] Step S103, when the first verification result indicates that the verification is passed, a secondary identity verification is performed based on the external image and the internal image of the target drone to obtain a second verification result, wherein the second verification result is used to indicate whether the identity verification of the target drone is passed.

[0043] Optionally, when the first verification result indicates that the verification is passed, external and internal images of the target UAV are collected, and then secondary identity authentication is performed through the external and internal images, which can accurately detect external and internal changes of the target UAV.

[0044] It should be noted that, when the second verification result indicates that the verification is successful, the verification of the identity of the target drone is successful.

[0045] It should be noted that if the second verification result indicates that the target drone identity verification fails, the target drone is not allowed to return to the content area, and relevant personnel need to be notified to handle the target drone.

[0046] To sum up, when the drone needs to return, the first identity authentication is performed through the flight parameters and energy consumption parameters of the target drone. If the verification is passed, the secondary identity authentication is performed based on the external and internal images of the target drone. Finally, based on the verification result of the secondary identity authentication, it is determined whether the identity authentication of the target drone is passed. Through flight parameters, energy consumption parameters, external images and internal images, more dimensions are added to the drone identity recognition, thereby achieving the effect of improving the accuracy and stability of the recognition process.

[0047] Optionally, in the drone identity identification method provided in the embodiment of the present application, obtaining the first identity information of the target drone to be returned includes: obtaining the body size parameters and body performance parameters of the target drone; obtaining the flight parameters, energy consumption parameters, and power parameters of the target drone based on the test data of the target drone before leaving the factory; obtaining the first identity information based on the body size parameters, body performance parameters, flight parameters, energy consumption parameters, and power parameters.

[0048] In an optional embodiment, obtaining the first identity information of the target UAV includes: first obtaining the body size parameters and body performance parameters of the target UAV. Then, obtaining the flight parameters, energy consumption parameters, and power parameters based on the test data of the target UAV before leaving the factory. Finally, the body size parameters, body performance parameters, flight parameters, energy consumption parameters, and power parameters are vectorized to obtain the first identity information.

[0049] Identification through body size parameters, fuselage performance parameters, flight parameters, energy consumption parameters and power parameters helps to improve the accuracy of drone identification.

[0050] Optionally, in the drone identification method provided in the embodiment of the present application, the flight parameters, energy consumption parameters, and power parameters of the target drone are obtained based on the test data of the target drone before leaving the factory, including: calculating based on the test time, maximum speed, maximum acceleration and reference acceleration in the test data to obtain the flight parameters; calculating based on the average rotation speed and test time in the test data to obtain the power parameters; and calculating based on the average voltage of the battery of the target drone in the test data to obtain the energy consumption parameters.

[0051] In an optional embodiment, the following steps are used to obtain the above-mentioned flight parameters, energy consumption parameters, and power parameters: the flight parameters are calculated based on the test duration, maximum speed, maximum acceleration and reference acceleration in the test data.

[0052] In an optional embodiment, the above flight parameters are calculated by formula (1):

[0053]

[0054] Among them, F(V max , a max , T) represents the value of the flight parameter; V max It indicates the maximum speed of the drone during the test after it is manufactured, which is directly measured by the corresponding testing equipment during the test; a max It indicates the maximum acceleration of the drone during the test after it is manufactured, which is directly measured by the corresponding detection equipment during the test; a ref Indicates the reference acceleration of the corresponding drone; T indicates the test duration.

[0055] Then, the power parameters are calculated using the average speed and test duration in the test data.

[0056] In an optional embodiment, the above power parameters are calculated by formula (2):

[0057]

[0058] in, Indicates the numerical value of the dynamic parameter; Indicates the average rotation speed of the drone during the test after it was produced.

[0059] Finally, the corresponding energy consumption parameters are calculated by the average voltage of the battery of the target UAV in the test data. In an optional embodiment, the above energy consumption parameters can be calculated by the average voltage and the weights of different battery types.

[0060] Optionally, in the drone identification method provided in the embodiment of the present application, the energy consumption parameters are obtained by calculating based on the average voltage of the battery of the target drone in the test data, including: obtaining the target battery type, total battery capacity and number of first battery groups of the battery of the target drone; determining the target value corresponding to the target battery type based on the selection function of the drone battery type; and obtaining the energy consumption parameters by calculating based on the total battery capacity, the number of first battery groups, the average voltage and the target value.

[0061] In an optional embodiment, the energy consumption parameters are calculated by the following steps: the target battery type, total battery capacity and number of first battery groups of the target UAV battery when it leaves the factory are obtained. Then, a corresponding selection function is set according to the battery type of the UAV, and then the target value corresponding to the target battery type can be determined according to the selection function. Finally, the energy consumption parameters are calculated according to the total battery capacity, the number of first battery groups, the average voltage and the target value.

[0062] In an optional embodiment, the above energy consumption parameters can be calculated by formulas (3) and (4):

[0063]

[0064]

[0065] in, Represents the value of the energy consumption parameter; R represents the total battery capacity of the drone; represents the average voltage of the battery in the test after the drone is produced; N represents the number of battery packs in the drone; f(kind e ) represents the value selection function based on the type of drone battery; kind e Indicates the type of drone battery; kind e =1 means the drone battery type is lithium-ion battery; kind e =2 means the drone battery type is NiMH battery; kind e =3 indicates the drone battery type is lead-acid battery; kind e =4 means the drone battery type is lithium polymer battery.

[0066] Optionally, in the drone identification method provided in the embodiment of the present application, secondary identity authentication is performed based on the external image and internal image of the target drone, and a second verification result is obtained, including: obtaining size information and shell maintenance information of the target drone based on the external image of the target drone; obtaining motor information, the number of second battery packs and cargo information of the target drone based on the internal image of the target drone; and performing secondary identity authentication based on the size information, shell maintenance information, motor information, the number of second battery packs and cargo information to obtain a second verification result.

[0067] In an optional embodiment, the following steps are used to achieve identity authentication of the target drone: collect external images and internal images of the target drone, and obtain the size information and shell maintenance information of the target drone through the external image of the target drone. For example, the body size, number of maintenance locations, and type of maintenance locations of the drone are obtained by identifying the external image of the target drone.

[0068] Then, the motor information, the number of second battery packs and cargo information of the target UAV are obtained by identifying the internal image of the target UAV. Finally, secondary identity authentication is performed through the size information, shell maintenance information, motor information, the number of second battery packs and cargo information to obtain the second verification result.

[0069] External and internal images can be used to accurately detect external and internal changes of the target drone.

[0070] Optionally, in the drone identification method provided in the embodiment of the present application, secondary identity verification is performed based on size information, shell maintenance information, motor information, the number of second battery packs and cargo information, and a second verification result is obtained, including: calculating based on the shell maintenance information and size information to obtain an external risk value; determining an internal risk value based on the motor information, the number of second battery packs and cargo information; and performing secondary identity verification based on the external risk value and the internal risk value to obtain a second verification result.

[0071] In an optional embodiment, performing secondary identity verification through size information, housing maintenance information, motor information, the number of second battery packs, and cargo information includes the following steps: calculating an external risk value through the identified housing maintenance information and size information. Then determining an internal risk value through the motor information, the number of second battery packs, and cargo information, and finally performing secondary identity verification based on the external risk value and the internal risk value to obtain a second verification result.

[0072] In an optional embodiment, the above external risk value can be calculated by formula (5) and formula (6):

[0073]

[0074] Wherein, outside represents the external risk value, L represents the length of the drone in the drone body size extracted from the external image; l represents the reference length of the drone in the factory body size parameters; W represents the width of the drone in the drone body size extracted from the external image; w represents the reference width of the drone in the factory body size parameters; S a represents the maintenance area of ​​the ath maintenance position on the drone; A represents the total number of maintenance positions on the drone; g(kind a ) represents the weight selection function based on the type of maintenance location; kind a Indicates the maintenance location type of the a-th maintenance location; kind a =1 means the repair location type is the scratch repair type; kind a =2 means the repair location type is the sunken repair type; kind a =3 indicates that the repair location type is a damaged repair type; the damaged repair type refers to the type of damage in which the drone has an open gap due to damage, the dent repair type refers to the type of damage in which the drone is deformed due to impact but has no open gap, and the scratch repair type refers to the type of damage in which the drone is scratched but has no deformation or open gap.

[0075] In an optional embodiment, if the product of the external risk and the internal risk is greater than or equal to a threshold, it indicates that the secondary verification has not passed; if the product of the external risk and the internal risk is less than the threshold, it indicates that the secondary verification has passed.

[0076] The accuracy and security of drone identification can be improved by analyzing the external and internal changes of the target drone.

[0077] Optionally, in the drone identification method provided in the embodiment of the present application, determining the internal risk value based on the motor information, the second battery pack number and the cargo information includes: judging whether there is a change in the motor of the target drone based on the motor information, and obtaining a judgment result; determining the cargo type based on the cargo information; calculating a target difference between the second battery pack number and the first battery pack number of the target drone when it leaves the factory; and determining the internal risk value based on the judgment result, the cargo type and the target difference.

[0078] In an optional embodiment, the above internal risk value is calculated by the following steps: judging whether the motor has changed, i.e., repairing the motor, disassembling the motor, replacing the motor, and modifying the motor, based on the motor information identified from the internal image. Identifying the category of the goods based on the cargo information identified from the internal image to obtain the above cargo type. It should be noted that the acquired types include but are not limited to dangerous goods and non-dangerous goods.

[0079] Then, the target difference between the second number of battery packs identified from the internal image and the first number of battery packs at the time of leaving the factory is calculated, and finally the internal risk value is obtained according to the judgment result, the type of goods and the target difference.

[0080] In an optional embodiment, the above internal risk value can be calculated by formula (7) and formula (8):

[0081] inside=J(M 1 &M 2 )×[1+|n 1 -n 2 ](7)

[0082]

[0083] Where, inside represents the internal risk value; J(M 1 &M 2 ) represents the value selection function based on the cargo type and motor conditions; M 1 =1 means the cargo type is identified as dangerous goods, which may include but are not limited to liquids, sharp objects, and flammable and explosive items; M 1 =0 means that the dangerous goods situation in the internal structure of the drone is identified as not existing dangerous goods; M 2=1 means that the motor condition in the internal structure of the drone is identified as modified. The motor condition identified as modified may include but is not limited to repairing the motor, disassembling the motor, replacing the motor, and modifying the motor, that is, the motor condition is inconsistent with the original factory setting; M 2 =0 means that the motor condition in the internal structure of the drone is identified as not modified; MAX means the maximum selected value; n 1 Indicates the number of battery packs identified in the internal structure of the drone; n 2 Indicates the total number of battery packs in the drone identity data; it should be noted that the maximum selected value can be set according to actual needs.

[0084] Through image recognition, the drone’s body size, number of maintenance locations, and type of maintenance locations are extracted from external images, and the external risk value is calculated. Through image recognition, the drone’s internal structure is extracted from internal X-ray scan information, and the internal risk value is calculated to improve the accuracy of drone identification.

[0085] In an optional embodiment, the Figure 2 The flowchart shown realizes the identification of the drone:

[0086] S1, acquiring identity data of various types of drones after they are produced, and generating drone model fingerprint information (i.e., second identity information) of various types of drones according to the identity data;

[0087] S2, stores drone model fingerprint information of various drone models;

[0088] S3, obtaining the comparison parameters (i.e., the first identity information) of the drone that has completed the mission and returned;

[0089] S4, comparing the comparison parameter with the second identity information, and outputting corresponding drone identity recognition information according to the comparison result.

[0090] The method for identifying the identity of a drone provided in the embodiment of the present application obtains the first identity information of the target drone to be returned, wherein the first identity information at least includes the flight parameters and energy consumption parameters of the target drone; the first identity information is authenticated according to multiple second identity information in the target database to obtain a first authentication result; when the first authentication result indicates that the authentication is passed, a secondary authentication is performed according to the external image and internal image of the target drone to obtain a second authentication result, wherein the second authentication result is used to indicate whether the identity authentication of the target drone is passed, which solves the problem that the accuracy of the drone identity authentication is relatively low due to the ID of the drone in the related technology. In this solution, when the drone needs to return, the first identity authentication is performed according to the flight parameters and energy consumption parameters of the target drone, and when the authentication is passed, the secondary identity authentication is performed according to the external image and internal image of the target drone, and finally, it is determined whether the identity authentication of the target drone is passed according to the verification result of the secondary identity authentication, and more dimensions are added to the drone identity authentication through the flight parameters, energy consumption parameters, external images and internal images, thereby achieving the effect of improving the accuracy and stability of the identification process.

[0091] It should be noted that the steps shown in the flowcharts of the accompanying drawings can be executed in a computer system such as a set of computer executable instructions, and that, although a logical order is shown in the flowcharts, in some cases, the steps shown or described can be executed in an order different from that shown here.

[0092] The embodiment of the present application also provides an identification device for a drone. It should be noted that the identification device for a drone in the embodiment of the present application can be used to execute the identification method for a drone provided in the embodiment of the present application. The identification device for a drone provided in the embodiment of the present application is introduced below.

[0093] Figure 3 Schematic diagram of the identity recognition device of the drone according to the embodiment of the present application. Figure 3 As shown, the device includes: an acquisition unit 301, a first verification unit 302 and a second verification unit 303.

[0094] The acquisition unit 301 is used to acquire the first identity information of the target UAV to be returned, wherein the first identity information at least includes the flight parameters and energy consumption parameters of the target UAV;

[0095] A first verification unit 302, configured to authenticate the first identity information based on the plurality of second identity information in the target database to obtain a first verification result;

[0096] The second verification unit 303 is used to perform secondary identity authentication based on the external image and internal image of the target drone to obtain a second verification result when the first verification result indicates that the authentication is passed, wherein the second verification result is used to indicate whether the identity authentication of the target drone is passed.

[0097] The identification device of the drone provided in the embodiment of the present application obtains the first identity information of the target drone to be returned through the acquisition unit 301, wherein the first identity information at least includes the flight parameters and energy consumption parameters of the target drone; the first verification unit 302 performs identity authentication on the first identity information according to multiple second identity information in the target database to obtain a first verification result; the second verification unit 303 performs secondary identity authentication according to the external image and internal image of the target drone when the first verification result indicates that the verification is passed, and obtains a second verification result, wherein the second verification result is used to indicate whether the identity authentication of the target drone is passed, which solves the problem that the accuracy of the drone identity identification is relatively low due to the identity identification through the ID of the drone in the related technology. In this solution, when the drone needs to return, the first identity authentication is performed through the flight parameters and energy consumption parameters of the target drone, and when the verification is passed, the secondary identity authentication is performed according to the external image and internal image of the target drone, and finally, it is determined whether the identity authentication of the target drone is passed according to the verification result of the secondary identity authentication, and more dimensions are added to the drone identity identification through the flight parameters, energy consumption parameters, external images and internal images, thereby achieving the effect of improving the accuracy and stability of the identification process.

[0098] Optionally, in the identity recognition device of the drone provided in the embodiment of the present application, the acquisition unit includes: a first acquisition subunit, used to acquire the body size parameters and body performance parameters of the target drone; a second acquisition subunit, used to acquire the flight parameters, energy consumption parameters, and power parameters of the target drone based on the test data of the target drone before leaving the factory; a determination subunit, used to obtain the first identity information based on the body size parameters, body performance parameters, flight parameters, energy consumption parameters and power parameters.

[0099] Optionally, in the identity recognition device of the drone provided in the embodiment of the present application, the second acquisition subunit includes: a first calculation module, used to calculate according to the test time, maximum speed, maximum acceleration and reference acceleration in the test data to obtain flight parameters; a second calculation module, used to calculate according to the average rotation speed and test time in the test data to obtain power parameters; a third calculation module, used to calculate according to the average voltage of the battery of the target drone in the test data to obtain energy consumption parameters.

[0100] Optionally, in the identity recognition device of the drone provided in the embodiment of the present application, the third calculation module includes: an acquisition submodule, used to obtain the target battery type, total battery capacity and first battery pack number of the battery of the target drone; a first determination submodule, used to determine the target value corresponding to the target battery type based on the selection function of the drone battery type; and a first calculation submodule, used to calculate according to the total battery capacity, the first battery pack number, the average voltage and the target value to obtain the energy consumption parameter.

[0101] Optionally, in the identity recognition device of the drone provided in the embodiment of the present application, the second verification unit includes: a third acquisition subunit, used to obtain size information and shell maintenance information of the target drone based on the external image of the target drone; a fourth acquisition subunit, used to obtain motor information, the number of second battery packs and cargo information of the target drone based on the internal image of the target drone; a verification subunit, used to perform secondary identity authentication based on the size information, shell maintenance information, motor information, the number of second battery packs and cargo information to obtain a second verification result.

[0102] Optionally, in the identity recognition device of the drone provided in the embodiment of the present application, the verification subunit includes: a fourth calculation module, used to calculate based on the shell maintenance information and size information to obtain an external risk value; a determination module, used to determine the internal risk value based on the motor information, the number of second battery packs and cargo information; a verification model, used to perform secondary identity verification based on the external risk value and the internal risk value to obtain a second verification result.

[0103] Optionally, in the identity recognition device of the drone provided in the embodiment of the present application, the determination module includes: a judgment submodule, used to judge whether there is a change in the motor of the target drone based on the motor information, and obtain a judgment result; a second determination submodule, used to determine the type of cargo based on the cargo information; a second calculation submodule, used to calculate the target difference between the second number of battery packs and the first number of battery packs of the target drone when it leaves the factory; a third determination submodule, used to determine the internal risk value based on the judgment result, the cargo type and the target difference.

[0104] The identification device of the drone includes a processor and a memory. The acquisition unit 301, the first verification unit 302 and the second verification unit 303 are all stored in the memory as program units, and the processor executes the program units stored in the memory to realize corresponding functions.

[0105] The processor contains a kernel, which calls the corresponding program unit from the memory. One or more kernels can be set, and the accurate identification of the drone can be achieved by adjusting the kernel parameters.

[0106] The memory may include non-permanent memory in a computer-readable medium, random access memory (RAM) and / or non-volatile memory, such as read-only memory (ROM) or flash RAM, and the memory includes at least one memory chip.

[0107] In an optional embodiment, there is also provided Figure 4 The drone identification system shown includes a drone model fingerprint information entry terminal 41, a drone model fingerprint information database terminal 42, a comparison parameter acquisition terminal 43 and a drone identification terminal 44.

[0108] The drone model fingerprint information entry terminal 41 is used to obtain identity data of various models of drones after the various models of drones are produced, and generate drone model fingerprint information of various models of drones based on the identity data; the identity data includes body size parameters, body performance parameters, flight parameters, power parameters and energy parameters; the drone model fingerprint information database terminal 42 is used to store drone model fingerprint information of various models of drones; the comparison parameter acquisition terminal 43 is used to obtain the comparison parameters of drones that have completed the mission and returned; the comparison parameters refer to the parameters entered by the user for the drone for matching the identity data of the same model of drones; the drone identity recognition terminal 44 is used to compare the comparison parameters with the identity data, and output the corresponding drone identity recognition information according to the comparison results.

[0109] Alternatively, if Figure 4 As shown, the drone model fingerprint information entry terminal 41 includes a drone specification data entry module 410 , a drone behavior data entry module 411 and a drone model fingerprint information generation module 412 .

[0110] The drone specification data entry module 410 is used to obtain the body size parameters and body performance parameters of various models of drones after the various models of drones are produced; the drone behavior data entry module 411 is used to obtain the flight parameters, power parameters and energy parameters of various models of drones after the various models of drones are produced; the drone model fingerprint information generation module 412 is used to generate the corresponding drone model fingerprint according to the body size parameters, body performance parameters, flight parameters, power parameters and energy parameters.

[0111] Alternatively, if Figure 4 As shown, the drone identification terminal 44 includes a comparison parameter reading module 440 , a specification data comparison module 441 , a behavior data comparison module 442 and a drone identification information generation module 443 .

[0112] The comparison parameter reading module 440 is used to read the comparison parameters sent by the drone; the specification data comparison module 441 is used to compare the body size parameters and body performance parameters in the comparison parameters with the body size parameters and body performance parameters in the identity data to generate specification data comparison information; when the specification data comparison information indicates pass, the behavior data comparison module 442 starts working and compares the flight parameters, power parameters, and energy parameters in the comparison parameters with the flight parameters, power parameters, and energy parameters in the identity data to generate behavior data comparison information; when the specification data comparison information indicates fail or the behavior data comparison information indicates fail, the drone identity recognition information generation module 443 is used to generate drone identity recognition information indicating that the drone identity recognition is wrong; when the specification data comparison information indicates pass and the behavior data comparison information indicates pass, the drone identity recognition information generation module is used to generate drone identity recognition information indicating that the drone identity recognition is correct.

[0113] Optional, such as Figure 5 As shown, the UAV behavior data entry module 411 includes a flight parameter acquisition submodule 4110 , a power parameter acquisition submodule 4111 and an energy parameter acquisition submodule 4112 .

[0114] The flight parameter acquisition submodule 4110 is used to calculate the flight parameters according to the maximum speed, maximum acceleration and test duration in the test after the UAV is produced; the power parameter acquisition submodule 4111 is used to calculate the power parameters according to the average rotation speed and test duration in the test after the UAV is produced; the energy parameter acquisition submodule 4112 is used to calculate the energy consumption analysis parameters according to the total battery capacity, average voltage and number of battery packs in the test after the UAV is produced.

[0115] Optionally, the drone identification system further includes a real-time identification terminal 45; the real-time identification terminal 45 is used to perform secondary identity authentication on the drone when the drone identification information of the drone indicates that the drone identification is correct, and generate a corresponding verification result.

[0116] Optional, such as Figure 6 As shown, the real-time recognition terminal 45 includes an external image acquisition module 450 , an X-ray scanning module 451 , a real-time recognition analysis module 452 and a real-time recognition information output module 453 .

[0117] The external image acquisition module 450 is used to photograph the drone and generate external image information of the drone; the X-ray scanning module 451 is used to perform X-ray scanning on the drone and generate internal X-ray scanning information of the drone; the real-time recognition and analysis module 452 is used to perform real-time recognition and analysis based on the external image information and the internal X-ray scanning information; the real-time recognition information output module 453 is used to output verification results based on the real-time recognition and analysis results.

[0118] Optional, such as Figure 7 As shown, the real-time identification and analysis module 452 includes an external image information analysis submodule 4520 and an internal X-ray scanning information analysis submodule 4521; the external image information analysis submodule 4520 is used to perform external identification and analysis of the UAV based on external image information; the internal X-ray scanning information analysis submodule 4521 is used to perform internal identification and analysis of the UAV based on internal X-ray scanning information.

[0119] An embodiment of the present invention provides a computer-readable storage medium having a program stored thereon, and when the program is executed by a processor, a method for identifying an unmanned aerial vehicle is implemented.

[0120] An embodiment of the present invention provides a processor, which is used to run a program, wherein the program executes a method for identifying an identity of a drone when the program is running.

[0121] like Figure 8 As shown, an embodiment of the present invention provides an electronic device, the device includes a processor, a memory, and a program stored in the memory and executable on the processor, and the processor implements the following steps when executing the program: obtaining first identity information of a target UAV to be returned, wherein the first identity information includes at least flight parameters and energy consumption parameters of the target UAV; performing identity authentication on the first identity information based on multiple second identity information in a target database to obtain a first verification result; when the first verification result indicates that the verification is passed, performing secondary identity authentication based on external images and internal images of the target UAV to obtain a second verification result, wherein the second verification result is used to indicate whether the identity authentication of the target UAV is passed.

[0122] Optionally, obtaining the first identity information of the target UAV to be returned includes: obtaining the body size parameters and body performance parameters of the target UAV; obtaining the flight parameters, energy consumption parameters, and power parameters of the target UAV based on the test data of the target UAV before leaving the factory; and obtaining the first identity information based on the body size parameters, body performance parameters, flight parameters, energy consumption parameters, and power parameters.

[0123] Optionally, based on the test data of the target UAV before leaving the factory, the flight parameters, energy consumption parameters, and power parameters of the target UAV are obtained, including: calculating based on the test time, maximum speed, maximum acceleration and reference acceleration in the test data to obtain the flight parameters; calculating based on the average rotation speed and test time in the test data to obtain the power parameters; calculating based on the average voltage of the battery of the target UAV in the test data to obtain the energy consumption parameters.

[0124] Optionally, the energy consumption parameters are obtained by calculating based on the average voltage of the battery of the target UAV in the test data, including: obtaining the target battery type, total battery capacity and number of first battery groups of the battery of the target UAV; determining the target value corresponding to the target battery type based on the selection function of the UAV battery type; and obtaining the energy consumption parameters by calculating based on the total battery capacity, the number of first battery groups, the average voltage and the target value.

[0125] Optionally, secondary identity authentication is performed based on the external image and internal image of the target UAV to obtain a second verification result, including: obtaining size information and shell maintenance information of the target UAV based on the external image of the target UAV; obtaining motor information, the number of second battery packs and cargo information of the target UAV based on the internal image of the target UAV; secondary identity authentication is performed based on the size information, shell maintenance information, motor information, the number of second battery packs and cargo information to obtain a second verification result.

[0126] Optionally, secondary identity verification is performed based on the size information, shell maintenance information, motor information, the number of second battery packs and cargo information to obtain a second verification result including: obtaining an external risk value by calculation based on the shell maintenance information and size information; determining an internal risk value based on the motor information, the number of second battery packs and cargo information; and secondary identity verification is performed based on the external risk value and the internal risk value to obtain a second verification result.

[0127] Optionally, determining the internal risk value based on the motor information, the second battery pack number and the cargo information includes: judging whether the motor of the target drone has changed based on the motor information, and obtaining a judgment result; determining the cargo type based on the cargo information; calculating a target difference between the second battery pack number and the first battery pack number of the target drone when it leaves the factory; and determining the internal risk value based on the judgment result, the cargo type and the target difference. The device in this article can be a server, a PC, a PAD, a mobile phone, etc.

[0128] The present application also provides a computer program product, which, when executed on a data processing device, is suitable for executing a program that initializes the following method steps: obtaining first identity information of a target UAV to be returned, wherein the first identity information includes at least flight parameters and energy consumption parameters of the target UAV; performing identity authentication on the first identity information based on multiple second identity information in a target database to obtain a first verification result; when the first verification result indicates that the verification is passed, performing secondary identity authentication based on the external image and internal image of the target UAV to obtain a second verification result, wherein the second verification result is used to indicate whether the identity authentication of the target UAV is passed.

[0129] Optionally, obtaining the first identity information of the target UAV to be returned includes: obtaining the body size parameters and body performance parameters of the target UAV; obtaining the flight parameters, energy consumption parameters, and power parameters of the target UAV based on the test data of the target UAV before leaving the factory; and obtaining the first identity information based on the body size parameters, body performance parameters, flight parameters, energy consumption parameters, and power parameters.

[0130] Optionally, based on the test data of the target UAV before leaving the factory, the flight parameters, energy consumption parameters, and power parameters of the target UAV are obtained, including: calculating based on the test time, maximum speed, maximum acceleration and reference acceleration in the test data to obtain the flight parameters; calculating based on the average rotation speed and test time in the test data to obtain the power parameters; calculating based on the average voltage of the battery of the target UAV in the test data to obtain the energy consumption parameters.

[0131] Optionally, the energy consumption parameters are obtained by calculating based on the average voltage of the battery of the target UAV in the test data, including: obtaining the target battery type, total battery capacity and number of first battery groups of the battery of the target UAV; determining the target value corresponding to the target battery type based on the selection function of the UAV battery type; and obtaining the energy consumption parameters by calculating based on the total battery capacity, the number of first battery groups, the average voltage and the target value.

[0132] Optionally, secondary identity authentication is performed based on the external image and internal image of the target UAV to obtain a second verification result, including: obtaining size information and shell maintenance information of the target UAV based on the external image of the target UAV; obtaining motor information, the number of second battery packs and cargo information of the target UAV based on the internal image of the target UAV; secondary identity authentication is performed based on the size information, shell maintenance information, motor information, the number of second battery packs and cargo information to obtain a second verification result.

[0133] Optionally, secondary identity verification is performed based on the size information, shell maintenance information, motor information, the number of second battery packs and cargo information to obtain a second verification result including: obtaining an external risk value by calculation based on the shell maintenance information and size information; determining an internal risk value based on the motor information, the number of second battery packs and cargo information; and secondary identity verification is performed based on the external risk value and the internal risk value to obtain a second verification result.

[0134] Optionally, determining the internal risk value based on the motor information, the number of second battery packs and the cargo information includes: judging whether there is any change in the motor of the target UAV based on the motor information, and obtaining a judgment result; determining the cargo type based on the cargo information; calculating a target difference between the number of second battery packs and the number of first battery packs of the target UAV when it leaves the factory; and determining the internal risk value based on the judgment result, the cargo type and the target difference.

[0135] Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, systems, or computer program products. Therefore, the present application may adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment in combination with software and hardware. Moreover, the present application may adopt the form of a computer program product implemented in one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) that include computer-usable program code.

[0136] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0137] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0138] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0139] In a typical configuration, a computing device includes one or more processors (CPU), input / output interfaces, network interfaces, and memory.

[0140] The memory may include non-permanent memory in a computer-readable medium, random access memory (RAM) and / or non-volatile memory in the form of read-only memory (ROM) or flash RAM. The memory is an example of a computer-readable medium.

[0141] Computer readable media include permanent and non-permanent, removable and non-removable media that can be implemented by any method or technology to store information. Information can be computer readable instructions, data structures, program modules or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technology, compact disk read-only memory (CD-ROM), digital versatile disk (DVD) or other optical storage, magnetic cassettes, magnetic tape disk storage or other magnetic storage devices or any other non-transmission media that can be used to store information that can be accessed by a computing device. As defined herein, computer readable media does not include temporary computer readable media (transitory media), such as modulated data signals and carrier waves.

[0142] It should also be noted that the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, commodity or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, commodity or device. In the absence of more restrictions, the elements defined by the sentence "comprises a ..." do not exclude the existence of other identical elements in the process, method, commodity or device including the elements.

[0143] Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, systems or computer program products. Therefore, the present application may adopt the form of a complete hardware embodiment, a complete software embodiment or an embodiment in combination with software and hardware. Moreover, the present application may adopt the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) that contain computer-usable program code.

[0144] The above are only embodiments of the present application and are not intended to limit the present application. For those skilled in the art, the present application may have various changes and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application should be included within the scope of the claims of the present application.

Claims

1. A method for identifying an unmanned aerial vehicle, characterized in that: include: Acquire first identity information of the target UAV to be returned, wherein the first identity information at least includes flight parameters and energy consumption parameters of the target UAV; authenticating the first identity information according to the plurality of second identity information in the target database to obtain a first authentication result; When the first verification result indicates that the verification is passed, a secondary identity verification is performed based on the external image and the internal image of the target drone to obtain a second verification result, wherein the second verification result is used to indicate whether the identity verification of the target drone is passed.

2. The method according to claim 1, characterized in that The first identity information of the target drone to be returned includes: Obtaining body size parameters and body performance parameters of the target UAV; Obtaining flight parameters, energy consumption parameters, and power parameters of the target UAV based on the test data of the target UAV before it leaves the factory; The first identity information is obtained according to the body size parameters, the body performance parameters, the flight parameters, the energy consumption parameters and the power parameters.

3. The method according to claim 2, characterized in that According to the test data of the target UAV before leaving the factory, the flight parameters, energy consumption parameters, and power parameters of the target UAV are obtained, including: Calculating according to the test duration, maximum speed, maximum acceleration and reference acceleration in the test data to obtain the flight parameters; Calculating according to the average rotation speed and test duration in the test data to obtain the power parameter; The energy consumption parameter is obtained by calculating according to the average voltage of the battery of the target UAV in the test data.

4. The method according to claim 3, characterized in that The energy consumption parameters obtained by calculating according to the average voltage of the battery of the target UAV in the test data include: Obtaining a target battery type, a total battery capacity, and a first battery pack number of a battery of the target drone; Based on the value selection function of the drone battery type, determine the target value corresponding to the target battery type; The energy consumption parameter is obtained by calculation based on the total battery capacity, the number of the first battery groups, the average voltage and the target value.

5. The method according to claim 1, characterized in that Performing secondary identity authentication based on the external image and the internal image of the target drone, obtaining a second authentication result including: Acquiring size information and shell maintenance information of the target UAV based on the external image of the target UAV; According to the internal image of the target drone, obtaining motor information, the number of second battery packs and cargo information of the target drone; A secondary identity verification is performed based on the size information, the shell maintenance information, the motor information, the second battery pack number and the cargo information to obtain the second verification result.

6. The method according to claim 5, characterized in that Performing secondary identity authentication based on the size information, the housing maintenance information, the motor information, the second battery pack number, and the cargo information, and obtaining the second authentication result includes: Calculating according to the shell maintenance information and the size information to obtain an external risk value; Determining an internal risk value according to the motor information, the number of the second battery groups and the cargo information; A secondary identity verification is performed according to the external risk value and the internal risk value to obtain the second verification result.

7. The method according to claim 6, characterized in that Determining the internal risk value according to the motor information, the number of the second battery groups, and the cargo information includes: According to the motor information, determine whether there is a change in the motor of the target UAV, and obtain a determination result; Determine the type of goods based on the goods information; Calculating a target difference between the second number of battery packs and a first number of battery packs of the target drone when it leaves the factory; The internal risk value is determined based on the judgment result, the cargo type and the target difference.

8. An identity recognition device for a drone, characterized in that: include: An acquisition unit, configured to acquire first identity information of a target UAV to be returned, wherein the first identity information at least includes flight parameters and energy consumption parameters of the target UAV; A first verification unit, configured to authenticate the first identity information according to a plurality of second identity information in a target database to obtain a first verification result; The second verification unit is used to perform secondary identity authentication based on the external image and internal image of the target drone to obtain a second verification result when the first verification result indicates that the verification is passed, wherein the second verification result is used to indicate whether the identity authentication of the target drone is passed.

9. A computer-readable storage medium, characterized in that: The computer-readable storage medium includes a stored program, wherein when the program is executed, the storage medium is controlled to execute the drone identification method according to any one of claims 1 to 7 on a device.

10. An electronic device, characterized in that: It includes one or more processors and a memory, wherein the memory is used to store one or more programs, wherein when the one or more programs are executed by the one or more processors, the one or more processors implement the drone identification method described in any one of claims 1 to 7.

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