Unmanned aerial vehicle user identifier determination method

Abstract

The embodiment of the invention provides an unmanned aerial vehicle user identifier determination method, and the method comprises the steps: obtaining the RTK positioning data of an unmanned aerial vehicle based on a communication identifier of the unmanned aerial vehicle in a sensing task region; and determining an unmanned aerial vehicle user identifier corresponding to the sensing target trajectory based on the RTK positioning data and the sensing target trajectory of the unmanned aerial vehicle. The problem that the AF cannot recognize the identity information of the unmanned aerial vehicle for sensing the target trajectory in the related technology is solved, and the effect that the AF can recognize the identity information of the unmanned aerial vehicle for sensing the target trajectory is achieved.

Description

TECHNICAL FIELD

[0001] Embodiments of the present application relate to the field of communication, in particular to a method for determining user identification of a UAV. BACKGROUND

[0002] With the continuous development of low-altitude economy, the application scenarios of unmanned aerial vehicle (UAV) devices are becoming more and more extensive. 5G and 5G-A communication networks are accelerating the deep integration with various industries such as UAV systems. Based on the trusted access and location management of UAVs based on 5G networks, and with the help of the evolution and enhancement of 5G network integration (5G-Advanced, 5G-A) new technologies, global supervision and efficient services can be realized.

[0003] In the existing 5G-A sensing positioning process, after the sensing base station, i.e., the radio access network (RAN), accesses the sensing function (SF), it initiates a configuration update and carries the base station sensing capability. The SF performs grid processing on the base station sensing capability and reports it to the application function (AF). The AF subsequently issues a sensing task to the SF according to the reported sensing capability. The SF selects a sensing base station that matches the task and issues a task start notification. At this point, the control plane process is complete, and the sensing base station can report the sensing target trajectory to the SF, which is then transmitted to the AF for further use by the client user, such as UAV intrusion detection, UAV obstacle avoidance, and path planning application scenarios.

[0004] In the above sensing positioning process, the user identification of the UAV of the sensing target trajectory cannot be obtained, which causes the AF to be unable to identify the identity information of the UAV reporting the sensing target trajectory. SUMMARY

[0005] Embodiments of the present application provide a method for determining the user identification of a UAV to at least solve the problem that the AF cannot identify the identity information of the UAV of the sensing target trajectory in related technologies.

[0006] According to an embodiment of the present application, a method for determining the user identification of a UAV is provided, comprising: based on the communication identification of a UAV within a sensing task area, obtaining real-time kinematic (RTK) positioning data of the UAV; and based on the RTK positioning data and a sensing target trajectory of the UAV, determining the user identification of the UAV corresponding to the sensing target trajectory.

[0007] According to still another embodiment of the present application, there is also provided a computer readable storage medium having stored therein a computer program, wherein the computer program is arranged to perform the steps of any of the method embodiments described above when executed.

[0008] According to still another embodiment of the present application, there is also provided an electronic device comprising a memory having stored therein a computer program and a processor arranged to execute the computer program to perform the steps of any of the method embodiments described above.

[0009] According to still another embodiment of the present application, there is also provided a computer program product comprising a computer program which, when executed by a processor, performs the steps of any of the method embodiments described above.

[0010] Through the above embodiments of the present application, a UAV user identifier determination method is provided, which obtains RTK positioning data of a UAV based on a communication identifier of the UAV in a perception task area; and determines a UAV user identifier corresponding to a perception target trajectory based on the RTK positioning data and a perception target trajectory of the UAV. The problem that AF cannot identify the identity information of the UAV of the perception target trajectory in the related art is solved, and the effect that AF can identify the identity information of the UAV of the perception target trajectory is achieved. BRIEF DESCRIPTION OF DRAWINGS

[0011] Figure 1 is a schematic diagram of a centralized architecture of sensory fusion;

[0012] Figure 2 is a hardware structure block diagram of a computer terminal of the UAV user identifier determination method executed by the embodiment of the present application;

[0013] Figure 3 is a flowchart of the UAV user identifier determination method of the embodiment of the present application;

[0014] Figure 4 is a flow principle diagram of the UAV user identifier determination method of the embodiment of the present application;

[0015] Figure 5 is a principle schematic diagram of the SF requesting a perception communication identifier to the AMF;

[0016] Figure 6 is a principle schematic diagram of UAV trajectory comparison and analysis;

[0017] Figure 7 is a flowchart of the UAV reporting RTK positioning data of the embodiment of the present application;

[0018] Figure 8 is a flowchart of the AF obtaining RTK positioning data of the embodiment of the present application. Detailed Implementation

[0019] The embodiments of the present invention will be described in detail below with reference to the accompanying drawings and examples.

[0020] It should be noted that the terms "first," "second," etc., in the specification, claims, and drawings of this invention are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence.

[0021] At the current stage, the sensor fusion network architecture can be deployed in a centralized or distributed manner. Figure 1 This is a schematic diagram of a centralized architecture for synesthetic fusion, such as... Figure 1 As shown, the functions of each network element are as follows: Radio Access Network (RAN), responsible for air interface resource scheduling and connection management for terminal access to the network. Access and Mobility Management Function (AMF), a core network control plane entity, primarily responsible for user mobility management, including registration and temporary identifier allocation; maintaining idle and connected states and state transitions; handover in the connected state; and triggering paging in the user's idle state. Sensing Function (SF), responsible for access management, grid management, and task management for sensing base stations. Application Function (AF), a sensing client, primarily responsible for grid rendering, task control management, and user trajectory rendering. Among these, for example... Figure 1 As shown, Uu, N2, NS2, NS3, and N33 represent communication interfaces between different network elements or devices. As conventional communication interfaces in this field, they will not be described in detail here.

[0022] The methods and embodiments provided in this application can be executed on a mobile terminal, a computer terminal, or a similar computing device. Taking running on a computer terminal as an example, Figure 2 This is a hardware structure block diagram of the computer terminal for the drone user identification determination method implemented in an embodiment of the present invention. Figure 2 As shown, computer terminal 200 may include one or more ( Figure 2 Only one is shown in the image. A processor 202 (which may include, but is not limited to, a microprocessor MCU or a programmable logic device FPGA, etc.) and a memory 204 for storing data are also shown. Those skilled in the art will understand that... Figure 2 The structure shown is for illustrative purposes only and does not limit the structure of the computer terminal described above. For example, the computer terminal may also include components that are more complex than those described above. Figure 2 The more or fewer components shown, or having the same Figure 2 The different configurations shown.

[0023] The memory 204 can be used to store computer programs, such as software programs of application software and modules, such as a computer program corresponding to the unmanned aerial vehicle user identification determination method in the embodiments of the present application. The processor 202 performs various functional applications and data processing by running the computer programs stored in the memory 204, that is, implements the above method. The memory 204 can include a high-speed random access memory, and can also include a non-volatile memory, such as one or more magnetic storage devices, flash memories, or other non-volatile solid-state memories. In some examples, the memory 204 can further include a memory remotely arranged with respect to the processor 202, which can be connected to the computer terminal through a network. Examples of the above network include but are not limited to the Internet, an intranet, a local area network, a mobile communication network, and a combination thereof.

[0024] The embodiments of the present application provide a method for determining the user identification of an unmanned aerial vehicle, Figure 3 The flowchart of the method for determining the user identification of an unmanned aerial vehicle according to the embodiments of the present application is shown in FIG. 2, which includes the following steps: Figure 3 The flowchart of the method for determining the user identification of an unmanned aerial vehicle according to the embodiments of the present application is shown in FIG. 2, which includes the following steps:

[0025] In step S302, based on the communication identification of the unmanned aerial vehicle in the perception task area, real-time kinematic (RTK) positioning data of the unmanned aerial vehicle is obtained.

[0026] In the embodiments of the present application, the communication identification of the unmanned aerial vehicle at least includes the unmanned aerial vehicle identification, the unmanned aerial vehicle user identification, and the mapping relationship between the unmanned aerial vehicle identification and the unmanned aerial vehicle user identification.

[0027] In an example embodiment, based on the communication identification of the unmanned aerial vehicle in the perception task area, the RTK positioning data of the unmanned aerial vehicle is obtained, including: according to the unmanned aerial vehicle identification (UAVID) in the communication identification of the unmanned aerial vehicle in the perception task area, the RTK positioning data of the unmanned aerial vehicle is obtained, wherein the perception task area is determined by an application function (AF).

[0028] In the embodiments of the present application, the above perception task area is determined by the AF according to actual perception requirements or actual scenarios, which is a conventional technical means in the art and will not be described here.

[0029] In an example embodiment, according to the unmanned aerial vehicle identification (UAVID) in the communication identification of the unmanned aerial vehicle in the perception task area, the RTK positioning data of the unmanned aerial vehicle is obtained, including: according to the association relationship between the UAVID and the RTK module of the unmanned aerial vehicle, the RTK positioning data of the unmanned aerial vehicle is obtained, wherein the RTK module obtains the corresponding RTK positioning data through an RTK positioning server.

[0030] In the embodiment of the present application, the unmanned aerial vehicle has an RTK module, the RTK module of the unmanned aerial vehicle acquires positioning data of an RTK positioning server, and then reports to a flight control platform of the unmanned aerial vehicle, the flight control platform reports the RTK positioning data to the SF based on the association relationship between the UAVID and the RTK module. The RTK positioning server is a positioning system or a positioning server independent of the unmanned aerial vehicle and the base station. The UAVID of the flight control platform is also reported by the unmanned aerial vehicle, and the UAVID is basic information of the unmanned aerial vehicle and is included in factory information of the unmanned aerial vehicle.

[0031] In one example embodiment, before acquiring the real-time kinematic (RTK) positioning data of the unmanned aerial vehicle based on the communication identifier of the unmanned aerial vehicle in the sensing task area, the method further comprises: receiving a next generation sense (NS) configuration update request from a base station, the NS configuration update request carrying a globally unique AMF identifier (GUAMI) list; determining a target AMF based on the GUAMI list; and acquiring the communication identifier of the unmanned aerial vehicle from the target AMF.

[0032] In the embodiment of the present application, the sensing base station aggregates sensing capabilities of each cell corresponding to the sensing base station, and initiates an NS configuration update request, carrying base station user plane address information (in the case of user plane address information change), a GUAMI list of the AMF, a refresh rate list of the sensing base station, a sensing type of the sensing base station, a sensing area of the sensing base station, etc. The GUAMI list includes the identifier information of multiple AMFs, and the SF determines all or part of the AMFs in the GUAMI list as target AMFs based on the GUAMI list.

[0033] In one example embodiment, acquiring the communication identifier of the unmanned aerial vehicle from the target AMF comprises: sending a first request to the target AMF, the first request carrying a sensing base station identifier (gNBID); and receiving the communication identifier of the unmanned aerial vehicle corresponding to the sensing base station identifier from the target AMF.

[0034] In the embodiment of the present application, the SF selects a target AMF or a target AMF list for the GUAMI list provided by the sensing base station, and initiates a sensing unmanned aerial vehicle user identifier query request (i.e. the first request in the above embodiment) to the target AMF, carrying the field gNBID. If the base station is connected to multiple target AMFs, the request message needs to be broadcasted to all AMFs.

[0035] Step S304: determining the unmanned aerial vehicle user identifier corresponding to the sensing target trajectory based on the RTK positioning data and the sensing target trajectory of the unmanned aerial vehicle.

[0036] In an example embodiment, based on the RTK positioning data and the perceived target trajectory of the UAV, the UAV user identifier corresponding to the perceived target trajectory is determined, comprising: obtaining the communication positioning trajectory of the UAV based on the RTK positioning data; determining the UAV user identifier in the communication identifier of the UAV corresponding to the perceived target trajectory based on the communication positioning trajectory and the perceived target trajectory, wherein the perceived target trajectory is the SF receiving the perceived trajectory of the UAV from the base station.

[0037] In the embodiment of the application, the communication positioning trajectory of the UAV is obtained based on the RTK positioning data fitting, wherein a conventional fitting algorithm can be used for RTK positioning data fitting, and the fitting algorithm is not specifically limited here. After obtaining the communication positioning trajectory, the communication positioning trajectory and the perceived target trajectory are compared, wherein a conventional comparison algorithm can be used to compare the communication positioning trajectory and the perceived target trajectory, and the comparison algorithm is not specifically limited here. Since the RTK positioning data is obtained from the flight control platform of the UAV based on the UAVID association, the communication positioning trajectory obtained by fitting the RTK positioning data also associates the UAVID. By comparing the communication positioning trajectory and the perceived target trajectory, the communication positioning trajectory and the perceived target trajectory belonging to the same target, i.e., the UAV, can be determined. Therefore, the perceived target trajectory sent to the SF can determine the UAVID of the communication positioning trajectory as the UAVID of itself, and the perceived target trajectory realizes the association of the UAVID. Based on the mapping relationship between the UAVID and the UAV user identifier, the perceived target trajectory can further associate the UAV user identifier based on the mapping relationship, thereby realizing the determination of the UAV user identifier in the communication identifier of the UAV corresponding to the perceived target trajectory.

[0038] In the embodiment of the application, the SF obtains the communication positioning trajectory of the UAV based on the RTK positioning data fitting, wherein a conventional fitting algorithm can be used for RTK positioning data fitting, and the fitting algorithm is not specifically limited here.

[0039] In an example embodiment, based on the communication positioning trajectory and the perceived target trajectory, the UAV user identifier in the communication identifier of the UAV corresponding to the perceived target trajectory is determined, comprising: determining the UAVID in the communication identifier of the UAV based on the communication positioning trajectory and the perceived target trajectory; determining the UAV user identifier corresponding to the perceived target trajectory based on the UAVID in the communication identifier and the mapping relationship, wherein the mapping relationship is the mapping relationship between the UAV user identifier and the UAVID.

[0040] In the embodiment of the present application, after obtaining the communication positioning track, the communication positioning track and the perception target track are compared to determine the UAVID in the communication identifier of the UAV, wherein the communication positioning track and the perception target track can be compared by using a conventional comparison algorithm, and the comparison algorithm is not limited here. Based on the UAVID in the communication identifier and the mapping relationship, the UAV user identifier corresponding to the perception target track is determined, the perception target track is labeled with the UAV user identifier, and is sent to the AF.

[0041] In one example embodiment, after determining the UAV user identifier corresponding to the perception target track, it further includes: sending the perception target track labeled with the UAV user identifier to the application function AF.

[0042] Through the above steps, a UAV user identifier determination method is provided, which obtains RTK positioning data of a UAV based on a communication identifier of the UAV in a perception task area; determines a UAV user identifier corresponding to a perception target track based on the RTK positioning data and the perception target track of the UAV. The problem that the AF cannot identify the UAV identity information of the perception target track in the related art is solved, and the effect that the AF can identify the UAV identity information of the perception target track is achieved.

[0043] In the embodiment, a UAV user identifier determination apparatus is also provided, which is used to implement the above embodiments and preferred embodiments, and will not be described here. As used below, the term "module" can be a combination of software and / or hardware that implements a predetermined function. Although the apparatus described in the following embodiments is preferably implemented in software, hardware, or a combination of software and hardware is also possible and contemplated.

[0044] The UAV user identifier determination apparatus provided by the embodiment of the present application can be arranged in the SF of the core network, and can include a data acquisition module arranged to acquire RTK positioning data of a UAV based on a communication identifier of the UAV in a perception task area. An identifier determination module arranged to determine a UAV user identifier corresponding to a perception target track based on the RTK positioning data and the perception target track of the UAV.

[0045] In the embodiment of the present application, the above-mentioned UAV user identifier determination apparatus can further include different modules, and the naming and function division of the modules can also select different ways according to the actual situation, which is not limited here.

[0046] It should be noted that the above-mentioned modules can be realized by software or hardware. For the latter, the following implementation manners can be used, but are not limited thereto: the above-mentioned modules are located in the same processor; or the above-mentioned modules are located in different processors in any combination.

[0047] Those skilled in the art can clearly understand that the method according to the above-mentioned embodiments can be realized by means of software necessary for a general hardware platform, and of course, can also be realized by hardware, but in many cases, the former is a better embodiment. Based on such understanding, the technical solutions of the present application can be embodied in the form of a software product, which is stored in a storage medium (such as a ROM / RAM, a magnetic disk, or an optical disk) and includes a plurality of instructions for causing a terminal device (which can be a mobile phone, a computer, a server, or a network device) to execute the method described in each embodiment of the present application.

[0048] The embodiments of the present application also provide a computer readable storage medium, which stores a computer program, and the computer program is configured to execute the steps in any of the above-mentioned method embodiments when running.

[0049] In an example embodiment, the above-mentioned computer readable storage medium can include, but is not limited to, a U disk, a read-only memory (ROM), a random access memory (RAM), a mobile hard disk, a magnetic disk or an optical disk, and various media that can store computer programs.

[0050] The embodiments of the present application also provide an electronic device, which includes a memory and a processor, the memory stores a computer program, and the processor is configured to execute the computer program to execute the steps in any of the above-mentioned method embodiments.

[0051] In an example embodiment, the above-mentioned electronic device can further include a transmission device and an input / output device, wherein the transmission device is connected to the processor, and the input / output device is connected to the processor.

[0052] The embodiments of the present application also provide a computer program product, which includes a computer program, and the computer program is executed by a processor to implement the steps in any of the above-mentioned method embodiments.

[0053] In an example embodiment, the above-mentioned computer program product includes a non-volatile computer readable storage medium, which stores a computer program, and the computer program is executed by a processor to implement the steps in the method described in each embodiment of the present application.

[0054] The specific examples in the present embodiment can refer to the examples described in the above-mentioned embodiments and example embodiments, which will not be described here again.

[0055] It is apparent to those skilled in the art that the modules or steps of the present application described above can be implemented by general computing devices, which can be centralized on a single computing device or distributed on a network composed of multiple computing devices, and can be implemented by program codes executable by the computing devices, so that they can be stored in storage devices and executed by the computing devices, and in some cases, the steps shown or described can be executed in different order, or they can be made into individual integrated circuit modules or a single integrated circuit module. Thus, the present application is not limited to any specific combination of hardware and software.

[0056] In order to enable those skilled in the art to better understand the technical solutions of the present application, different embodiments are described below.

[0057] Embodiment one

[0058] Figure 4 The flow principle diagram of the unmanned aerial vehicle user identification determination method of the embodiment of the present application is shown in FIG. 1, which includes the following steps: Figure 4

[0059] S401, the sensing base station initiates an NS establishment request.

[0060] In the embodiment of the present application, the NS establishment request carries the sensing base station identifier gNBID information and the base station user plane address information. The base station user plane address information is a conventional communication information in the art, which is not described here.

[0061] S402, after receiving the NS establishment request, the SF saves the corresponding communication information and returns an NS establishment response to the base station (sensing base station).

[0062] In the embodiment of the present application, the NS establishment response carries the SF user plane address information. The SF user plane address information is a conventional communication information in the art, which is not described here.

[0063] S403, the sensing base station aggregates the sensing capabilities of each cell corresponding to the sensing base station, and initiates an NS configuration update request, carrying the base station user plane address information (if changed), the GUAMI list of the AMF, the refresh rate list of the sensing base station, the sensing type of the sensing base station, the sensing area of the sensing base station, etc.

[0064] In the embodiment of the present application, the communication identifier of the unmanned aerial vehicle includes the unmanned aerial vehicle identifier UAVID, the unmanned aerial vehicle user identifier, and the mapping relationship between the unmanned aerial vehicle identifier and the unmanned aerial vehicle user identifier.

[0065] ​In one embodiment, the drone user identifier includes the user's Subscription Permanent Identifier (SUPI); International Mobile Equipment Identifier (IMEI); and Generic Public Subscription Identifier (GPSI).

[0066] S404 After receiving the NS configuration update request, the SF saves the updated base station user plane address information (if changed), the GUAMI list, and the base station's sensing capability information, and returns the NS configuration update response to the sensing base station, carrying the SF user plane address information (if changed).

[0067] In one embodiment, the SF rasterizes the base station's sensing area based on the managed sensing area and configured grid specifications to obtain grid information, and then reports it to the AF.

[0068] S405, AF initiates the task based on the reported grid information and the desired sensing task area, and sends a sensing task initiation request to SF.

[0069] In this embodiment of the invention, the sensing task initiation request carries the AF identifier, the sensing task identifier, the refresh rate supported by AF, the sensing task area, and the task sensing type.

[0070] S406. After receiving the perception task start request from the AF, the SF checks whether the AF is registered and the validity of the perception task area. If the check passes, the SF returns a perception task start response to the AF; otherwise, it returns a failure and indicates the reason for the failure.

[0071] S407, SF selects a sensing base station within the sensing task area that meets the sensing type indicated by AF and sends a sensing task start notification to the sensing base station.

[0072] In this embodiment of the invention, the sensing task initiation request carries a refresh rate (if the refresh rate indicated by AF is within the range supported by the sensing base station, the indicated value of AF is used; otherwise, the minimum value in the list of refresh rates supported by the sensing base station is selected), and initiates the base station cell identifier list, etc.

[0073] In embodiments of the present invention, such as Figure 4 As shown, while the SF sends a task initiation request to the sensing base station, it also includes step 7a, where the SF needs to select the target AMF based on GUAMI, and step 7b, where the SF initiates a sensing UAV user ID query request to the target AMF, wherein the UAV user ID query request carries the field gNBID.

[0074] In actual implementation, the SF selects all or part of AMFs in the GUAMI list as target AMFs according to the GUAMI list, and in general, all AMFs in the GUAMI list are selected as target AMFs, and if part of AMFs are selected as target AMFs, the actual situation can be determined, which is not described here.

[0075] In the embodiment of the application, after the sensing base station and the AMF initiate the next generation network connection establishment (NG SETUP), the SF initiates a request to the AMF through the interface Namf_Communication_ProvideSenseUserInfo, carrying the field gNBID, and the AMF receives the request, queries the UAV information (i.e. the communication identifier) according to the gNBID, if the query is successful, returns the query UAV information list, otherwise returns the response 404 indicating the failure reason value USER_NOT_FOUND. Wherein, Namf_Communication_ProvideSenseUserInfo is the interface name, Namf_Communication represents the service name, i.e. the communication interface naming, ProvideSenseUserInfo represents the service operation as providing sensing user information, wherein the sensing user is the UAV, and the sensing user information is the UAV information (i.e. the communication identifier) of the UAV.

[0076] Figure 5 is the principle diagram of the SF requesting the sensing communication identifier to the AMF, as shown in Figure 5 , the SF selects the target AMF or the target AMF list for the GUAMI list provided by the sensing base station, and initiates Namf_Communication_RequestSenseUserInfo (sensing UAV user identifier query request, i.e. the first request in the above embodiment) to the target AMF, carrying the field gNBID, if the base station is connected to multiple target AMFs, the request message needs to be broadcasted to all AMFs. The AMF returns the corresponding UAV user identifier or the query error, and the AMF returns the specific problem details, Figure 5 , wherein the specific problem details can be various actual problems, for example, information instruction error, request transmission error, and unable to query the corresponding information, which is not described here. Wherein, Figure 5 , 200OK in the above embodiment is used to indicate that the query is successful, and the AMF returns 200OK and the UAV user identifier at the same time.

[0077] In the embodiment of the present application, the sensing base station initiates NG SETUP to the AMF, and the AMF returns NG SETUP response carrying the AMF name, the GUAMI list of the served, the supported Public Land Mobile Network (PLMN) list, etc.

[0078] In the embodiment of the present application, the sensing base station carries the GUAMI list when notifying the SF of its sensing capability through NS configuration update, and the GUMAI can identify one or more AMFs. The SF acquires the routing information of the target AMF according to the GUAMI, in the SF locally or in the Network Repository Function (NRF), so as to broadcast to the AMF according to the routing information.

[0079] In the embodiment of the present application, the service interface interaction between the SF and the AMF is based on the HTTP protocol.

[0080] S408, after receiving the base station task start response, the SF maintains the base station task state information.

[0081] In the embodiment of the present application, the above base station task state information mainly includes the state information of the sensing task being performed by the sensing base station, etc. As a routine technology in the art, it will not be described here.

[0082] In the embodiment of the present application, as shown in Figure 4 When the SF receives the base station task start response, it also includes step 8a, the SF receives the UAV user identification query response from the target AMF. In an embodiment, after the AMF returns the query sensing UAV user identification and UAV identification UAVID query response, the SF saves the user identification and UAVID of all sensing targets (i.e. UAVs) under the base station, i.e. as shown in Figure 4 Step 8b, the SF caches the mapping relationship between the UAV user identification and the UAVID; step 8c, the SF queries the RTK positioning data corresponding to the UAVID from the flight control platform (UAV_PLAT), wherein the query method can be that the SF sends a query request to the flight control platform (UAV_PLAT); step 8d, the SF receives the response of the query RTK positioning data from the flight control platform (UAV_PLAT), i.e. receives the RTK positioning data corresponding to the UAVID returned by the flight control platform (UAV_PLAT).

[0083] In the embodiment of the present application, the unmanned aerial vehicle has an RTK module, the RTK module of the unmanned aerial vehicle acquires RTK positioning data of an RTK positioning server, and then reports to a flight control platform, wherein the reporting content is RTK positioning data marked with a UAVID, that is, the RTK positioning data and the UAVID are reported at the same time, the flight control platform reports the RTK positioning data marked with the UAVID to an SF based on the association relationship between the UAVID and the RTK module. The RTK positioning server is a positioning system or a positioning server independent of the unmanned aerial vehicle and the base station.

[0084] S409, the sensing base station reports the sensing target trajectory to the SF.

[0085] In the embodiment of the present application, in the case where the sensing base station reports the sensing target trajectory to the SF, as shown in Figure 4 , it further includes step 9a, the SF matches the sensing target trajectory and the communication positioning trajectory to acquire the unmanned aerial vehicle user identifier. In an embodiment, the SF receives the sensing target trajectory, the SF compares and matches the sensing target trajectory and the communication positioning trajectory acquired by fitting the RTK positioning data, and the sensing target trajectory and the communication positioning trajectory satisfying the matching degree are determined as the trajectory of the same sensing target, that is, the trajectory of the unmanned aerial vehicle, wherein the matching degree is preset or set according to the actual situation, and is a common technology for trajectory comparison. The comparison method used in the trajectory comparison is also a conventional comparison algorithm, which will not be described here. In the case where it is determined that the sensing target trajectory and the communication positioning trajectory belong to the same unmanned aerial vehicle, since the communication positioning trajectory has the association relationship with the UAVID, the sensing target trajectory also has the association relationship with the UAVID, and since the mapping relationship between the UAVID and the unmanned aerial vehicle user identifier has been cached in the SF, the sensing target trajectory can be associated with the corresponding unmanned aerial vehicle user identifier based on the mapping relationship. As shown in Figure 4 , step 9b, the SF reports the sensing target trajectory carrying the unmanned aerial vehicle user identifier to the AF.

[0086] Figure 6 is a schematic diagram of the principle of the unmanned aerial vehicle trajectory comparison and analysis, as shown in Figure 6 , the implementation principles of the above steps S409, step 9a and step 9b are shown, the SF receives the trajectory message, that is, the sensing target trajectory, from the sensing base station, the SF also receives the RTK positioning data from the flight control platform, and obtains the communication positioning trajectory by fitting the RTK positioning data, the SF compares and analyzes the sensing target trajectory and the communication positioning trajectory to determine the UAVID corresponding to the sensing target trajectory, queries the mapping relationship between the UAVID and the unmanned aerial vehicle user identifier, determines the unmanned aerial vehicle user identifier corresponding to the sensing target trajectory, and reports the sensing target trajectory carrying the unmanned aerial vehicle user identifier to the AF.

[0087] S410, the AF issues a sensing task stop request to the SF, and the SF deletes the task information.

[0088] S411, the SF replies to the AF sensing task stop response.

[0089] S412, the SF notifies the sensing base station of the sensing task stop when the sensing base station has been notified of the start task notification and the task coverage area no longer exists or does not cover the sensing area of the base station.

[0090] In the embodiment of the application, when the SF notifies the sensing base station of the sensing task stop, as shown in Figure 4 step 12a, the UAV user identifier and the UAVID mapping relationship maintained for the base station are deleted, and the local task state information also needs to be deleted.

[0091] S413, the sensing base station receives the sensing task stop request, replies to the SF sensing task stop response, and stops the trajectory reporting.

[0092] Embodiment two

[0093] In embodiment one, the RTK positioning data of the UAV is obtained based on the UAVID, the communication positioning trajectory is obtained based on the RTK positioning data, and the UAV user identifier is obtained by comparing the communication positioning trajectory and the sensing target trajectory from the sensing base station, so that the sensing target trajectory labeled with the UAV user identifier is sent to the AF, thereby solving the problem in the related art that the AF cannot identify the UAV user identifier of the sensing target trajectory because the sensing base station cannot obtain the UAV user identifier.

[0094] In embodiment two, the obtaining of the RTK positioning data and the determination of the UAV user identifier of the sensing target trajectory are described in detail.

[0095] In the related art, with the rapid development of the field of low-altitude economy, UAVs are widely used in agricultural plant protection, power inspection, urban road inspection, emergency rescue and other fields as a typical form of low-altitude economy. The frequent occurrence of black flying and random flying poses a challenge to the management of network-connected UAVs. Currently, the integration of sensing and communication technologies plays a very important role in UAV device discovery and trajectory display. However, only sensing can identify whether there is a UAV type terminal device, but it cannot lock the SIM card number of the communication module of the UAV device, and there is no effective way to ensure the communication of network UAVs and to control the flight.

[0096] In the related art, by means of the sensing and communication fusion identity recognition technology, the sensing position data and the communication positioning data are fitted into a track, the same unmanned aerial vehicle is determined by means of track comparison, and the identity information of the unmanned aerial vehicle is recognized. The sensing position data is reported to the SF by the sensing base station, and the communication positioning data is obtained in various ways. One of the commonly used technologies is that the network side initiates terminal positioning to the base station through the gateway mobile location center (GMLC) or the location management function (LMF) network element, but the communication positioning data obtained by the technology has low precision, resulting in errors in the track comparison result, and increasing the base station density is required to improve the positioning precision, which has high networking requirements and deployment cost. The networked unmanned aerial vehicle with an RTK module will report the RTK positioning data of the unmanned aerial vehicle to the flight control platform in real time after taking off, so that the positioning data is obtained from the flight control platform, which is an effective way to reduce the networking requirements. However, the flight control platform of the unmanned aerial vehicle is usually provided by the unmanned aerial vehicle manufacturer, and lacks the unmanned aerial vehicle user identifier in the communication identifier such as GPSI / IMSI, so that the RTK module identifier and the communication module identifier cannot be simply and efficiently connected.

[0097] To solve the above problems, the embodiment of the present application provides a method for obtaining high-precision communication positioning data and RTK positioning data, which is used for sensing and communication fusion identity recognition technology, does not need to increase the base station density, can effectively reduce the networking requirements, improve the positioning precision, and increase the accuracy of target identity recognition.

[0098] The RTK positioning data obtained by the embodiment of the present application can be realized based on a communication network architecture, and the communication network architecture comprises a core network, a wireless access network (i.e., a sensing base station), a networked unmanned aerial vehicle and a data network.

[0099] In the embodiment of the present application, the core network (5 Generation Core network, 5GC) has a plurality of network functions (Network Function, NF), and each NF can access each other through a service interface. In an embodiment, the main NFs of the core network include: a user plane function (User Plane Function, UPF), which is a user plane access NF of the network, mainly responsible for functions such as packet routing and forwarding of user plane data, policy implementation, traffic reporting, quality of service (Quality of Service, QoS) processing, etc. Unified data management (Unified Data Management, UDM) is responsible for the unified management of user subscription information, security information and other user data, as well as related user identification, access authorization and mobility management functions. Session management function (Session Management Function, SMF) is mainly responsible for functions such as tunnel maintenance, Internet Protocol (Internet Protocol, IP) address allocation and management, user plane (User Plane, UP) management, policy implementation, QoS control, charging data collection, roaming, etc. Access and mobility management function AMF, as a control plane access NF of the user, is mainly responsible for functions such as user registration management, connection management, reachability management, security management, mobility management, etc. Sensing function (Sensing Function, SF) network element is used for environmental sensing and context awareness. The SF network element can use wireless signals in the network to detect and identify objects, personnel and other dynamic changes in the environment, thereby providing rich sensing information to support various applications and services. In an embodiment, the above-mentioned sensing information can include trajectory information, height information, area information, location information, etc. It should be noted that the SF network element can be deployed together or C / U separated, and the present embodiment does not limit this.

[0100] In the embodiment of the present application, the network-connected UAV is connected with the AMF through the signaling interface N1. In an embodiment, the network-connected UAV is a UAV with an RTK module, which supports reporting of the RTK module ID and RTK positioning data.

[0101] In the embodiment of the present application, the sensing base station RAN is a type of access network (Access Network, AN). RAN refers to introducing a certain part or all of the access network AN into a wireless transmission medium to provide fixed terminal services and / or mobile terminal services to users. Among them, the RAN is connected with the AMF through the signaling interface N2. The RAN is connected with the UPF through N3, which is used for transmission of uplink and downlink user plane data.

[0102] In the embodiments of the present application, a data network (DN) corresponds to operator services, Internet access, or third-party services, etc. In an embodiment, a third-party application (App) can be deployed in the DN.

[0103] In an embodiment, a UAV flight control platform and a UAV management and control platform can be deployed in the DN. The UAV flight control platform can issue a sensing task and configure an RTK module ID and a UAVID association relationship. The UAV management and control platform can display a sensing target trajectory.

[0104] In the embodiments of the present application, the AF (for example, a UAV management and control platform) obtaining a sensing target trajectory labeled with a UAV user identifier mainly includes two main processes, which are a UAV reporting RTK positioning data to a flight control platform of the UAV, and an SF obtaining RTK data from the flight control platform based on a UAVID and sending the RTK data to the AF.

[0105] Figure 7 is a flowchart of the UAV reporting RTK positioning data in the embodiments of the present application, as shown in Figure 7 , including the following steps:

[0106] S701, a network-connected UAV accesses a 5G communication network using a communication module.

[0107] S702, during the flight of the network-connected UAV, data messages are sent to a UPF via a RAN.

[0108] In the embodiments of the present application, the above-mentioned data messages are RTK positioning data and an RTK module ID of the UAV.

[0109] Through step S702, the RTK module ID and the RTK positioning data establish an association relationship, wherein the association relationship represents that there is a corresponding relationship or a mapping relationship between the two.

[0110] S703, the UPF identifies that the data messages are of the UAV, and reports the RTK positioning data and the RTK module ID of the UAV to a flight control platform via an Npfu-af interface (GTPU protocol), and the flight control platform saves the information.

[0111] Through step S703, the flight control platform establishes an association relationship between the RTK module ID and a UAV identifier UAVID according to the above-mentioned saved information and UAV factory information (including a UAV identifier).

[0112] Figure 8 is a flowchart of the AF obtaining RTK positioning data in the embodiments of the present application, as shown in Figure 8 , including the following steps:

[0113] S801, the RAN performs a UAV sensing task, collects sensing target data of the UAV, and reports a SENSE_MEASUREMENT_REPORT message and sensing information (base station information, sensing ID, UAV trajectory) to a sensing function user plane (SF-U) through an Nsfu-ns interface (GTPU protocol).

[0114] In the embodiment of the application, the sensing base station receives a sensing task issued by the SF, and the sensing base station reports sensing information of a target to the SF-U after sensing the UAV. The target includes the UAV, and in actual implementation, the target can also include other types of targets, such as a moving object.

[0115] S802, the SF-U sends a GET_UAV_RTK_POSITION_REQUEST to a sensing function control plane (SF-C) to request RTK positioning data of the UAV and a communication identifier of the UAV. The GET_UAV_RTK_POSITION_REQUEST carries sensing base station information and a sensing area and a start time of the RTK positioning data.

[0116] S803, the SF-C carries the sensing base station information and queries an AMF to obtain a UAV user identifier (GPSI / IMSI) and a UAV identifier UAV ID.

[0117] Through step S803, the SF-C of the core network establishes an association relationship between the UAV user identifier and the UAV ID.

[0118] S804, the SF-C sends a GET_UAV_RTK_POSITION_REQUEST to a flight control platform through an Nsfc-af interface, where the GET_UAV_RTK_POSITION_REQUEST carries a sensing area, a start time of RTK positioning data, and a UAV ID.

[0119] S805, the flight control platform returns RTK positioning data of the UAV to the SF-C through a GET_UAV_RTK_POSITION_RESPONSE according to a matching relationship between the UAV ID and an RTK module ID.

[0120] Through step S805, the SF-C of the core network establishes an association relationship between the UAV user identifier and the RTK positioning data, and sends the association relationship to the SF-U in step S806.

[0121] S806, the SF-C returns the RTK positioning data of the UAV and the UAV user identifier (GPSI / IMSI) to the SF-U through a GET_UAV_RTK_POSITION_RESPONSE.

[0122] S807, the SF-U fits the perception position data, i.e., the RTK positioning data, into a perception target trajectory, fits the RTK positioning data into a communication positioning trajectory, correlates the perception target trajectory and the UAV user identifier by comparing the perception target trajectory and the communication positioning trajectory, and reports the perception target trajectory and the UAV user identifier (GPSI / IMSI) to a UAV management and control platform through a SENSE_MEASUREMENT_REPORT (perception measurement report) message of an Nsfu-af interface (GTPU protocol), wherein the UAV management and control platform is an instance of an AF.

[0123] In the embodiment of the application, the Nsfc-af interface and the Nsfu-af interface are commonly used data transmission interfaces in the field, and the interface names are named according to fixed rules. As a conventional naming rule, it will not be described here.

[0124] In the embodiment of the application, the SF fits the RTK positioning data into a communication positioning trajectory, and establishes an association between the UAV user identifier and the communication positioning trajectory based on the association between the UAVID and the UAV user identifier and the association between the UAVID and the RTK positioning data. The SF correlates the perception target trajectory of the UAV and the corresponding UAV user identifier by comparing the perception target trajectory and the communication positioning trajectory, and reports the perception target trajectory and the UAV user identifier to the UAV management and control platform.

[0125] In actual implementation, the UAV management and control platform judges the legality of the UAV according to the UAV user identifier and the flight trajectory of the UAV, and issues a communication guarantee or supervision countermeasure command for the UAV through the communication identifier of the UAV.

[0126] Through the above steps, the RTK positioning data of the UAV can be accurately obtained in the embodiment of the application, the accuracy of the identification of the identity information of the target UAV is effectively improved, and the requirement for networking is reduced.

[0127] In the embodiment of the application, the SF queries the UAVID from the 5GC through the UAV IMSI, obtains the RTK positioning data from the flight control platform by means of the association between the UAVID and the RTK module, and thus realizes the identity identification of the networked UAV by comparing the perception trajectory and the positioning trajectory.

[0128] To sum up, the unmanned aerial vehicle user identifier determination method provided by the embodiment of the application, the client network element, that is, the application function AF, selects a control area (that is, a perception task area), the SF obtains the mapping relationship between the unmanned aerial vehicle user identifier and the UAVID of all unmanned aerial vehicles in the control area by interacting with the communication network element, and uses the UAVID to obtain the RTK positioning data of the unmanned aerial vehicle from the flight control platform. After the SF obtains the perception target trajectory from the base station, the unmanned aerial vehicle user identifier is obtained by comparing and analyzing the perception target trajectory and the communication positioning trajectory obtained based on the RTK positioning data, and is reported to the AF.

[0129] The unmanned aerial vehicle user identifier determination method provided by the embodiment of the application uses the UAVID to obtain the RTK positioning data of the unmanned aerial vehicle from the flight control platform, can accurately specify and obtain the RTK positioning data, and can reduce the impact of large flow data compared with the prior art, that is, fitting and comparing all RTK data.

[0130] In the future sensing and communication integrated system and intelligent low-altitude deep fusion scene, the technical solution of the embodiment of the application can further perform trajectory accurate prediction after comparing and analyzing the trajectory of the specified target unmanned aerial vehicle, and is suitable for application scenarios such as unmanned aerial vehicle intrusion detection, unmanned aerial vehicle obstacle avoidance and path planning. In the actual implementation process, whether the technical solution provided by the embodiment of the application is adopted can be judged by detecting whether the AMF initiatively queries the unmanned aerial vehicle user identifier through the gNBID between the AMF and the SF.

[0131] The above only describes the preferred embodiments of the application and is not used to limit the application. For those skilled in the art, the application can have various modifications and changes. Any modification, equivalent replacement, improvement, etc. within the principles of the application shall be included in the protection scope of the application.

Claims

1. A method for determining the user identifier of a drone, characterized in that, Applications to sensing functions include: Based on the communication identifiers of the UAV within the sensing task area, the real-time dynamic measurement technology (RTK) positioning data of the UAV is obtained. Based on the RTK positioning data and the perceived target trajectory of the UAV, the UAV user identifier corresponding to the perceived target trajectory is determined.

2. The method according to claim 1, characterized in that, The acquisition of real-time dynamic positioning (RTK) data of the UAV based on the communication identifier of the UAV within the sensing task area includes: The RTK positioning data of the UAV is obtained based on the UAV identifier UAVID in the communication identifier of the UAV within the sensing task area, wherein the sensing task area is determined by the application function AF.

3. The method according to claim 2, characterized in that, Based on the UAV identifier (UAVID) in the communication identifier of the UAV within the sensing task area, the RTK positioning data of the UAV is obtained, including: Based on the association between the UAVID and the RTK module of the drone, the RTK positioning data of the drone is obtained, wherein the RTK module obtains the corresponding RTK positioning data through an RTK positioning server.

4. The method according to claim 1, characterized in that, Before acquiring the real-time dynamic positioning (RTK) data of the UAV based on the communication identifier of the UAV within the sensing task area, the method further includes: Receive a Next Generation Sensing Interface (NS) configuration update request from a base station, the NS configuration update request carrying a globally unique AMF identifier (GUAMI) list; Based on the GUAMI list, the target access and mobility management function (AMF) is determined; Obtain the communication identifier of the UAV from the target AMF.

5. The method according to claim 4, characterized in that, The step of obtaining the communication identifier of the UAV from the target AMF includes: Send a first request to the target AMF, the first request carrying a sensing base station identifier; The communication identifier of the UAV corresponding to the identifier of the sensing base station is received from the target AMF.

6. The method according to claim 1, characterized in that, The step of determining the drone user identifier corresponding to the perceived target trajectory based on the RTK positioning data and the drone's perceived target trajectory includes: The communication positioning trajectory of the UAV is obtained based on the RTK positioning data; Based on the communication positioning trajectory and the sensing target trajectory, the UAV user identifier in the communication identifier of the UAV corresponding to the sensing target trajectory is determined, wherein the sensing target trajectory is the sensing trajectory of the UAV received by the SF from the base station.

7. The method according to claim 6, characterized in that, Based on the communication positioning trajectory and the sensing target trajectory, the UAV user identifier in the communication identifier of the UAV corresponding to the sensing target trajectory is determined, including: Based on the communication positioning trajectory and the perceived target trajectory, the UAVID in the communication identifier of the UAV is determined; Based on the UAVID and mapping relationship in the communication identifier, the UAV user identifier corresponding to the perceived target trajectory is determined, wherein the mapping relationship is the mapping relationship between the UAV user identifier and the UAVID.

8. The method according to claim 1, characterized in that, After determining the UAV user identifier corresponding to the perceived target trajectory, the method further includes: The trajectory of the perceived target, marked with the user identifier of the drone, is sent to the application function AF.

9. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program, wherein the computer program, when executed by a processor, implements the steps of the method described in any one of claims 1 to 8.

10. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements the steps of the method described in any one of claims 1 to 8.

11. A computer program product, comprising a computer program, characterized in that, When the computer program is executed by a processor, it implements the steps of the method described in any one of claims 1 to 8.

Images