CN114026517B

CN114026517B - Information processing method, unmanned aerial vehicle, server and storage medium

Info

Publication number: CN114026517B
Application number: CN202080033688.7A
Authority: CN
Inventors: 彭玄; 王焱; 尹小俊
Original assignee: SZ DJI Technology Co Ltd
Current assignee: SZ DJI Technology Co Ltd
Priority date: 2020-06-30
Filing date: 2020-06-30
Publication date: 2024-02-20
Anticipated expiration: 2040-06-30
Also published as: WO2022000222A1; CN114026517A

Abstract

An information processing method, an unmanned aerial vehicle, a server and a storage medium, the method comprising: acquiring signal quality information of a base station, wherein the signal quality information is measured based on communication connection with the base station in the flight process of an unmanned aerial vehicle; acquiring position information of the unmanned aerial vehicle when measuring the signal quality information; and determining signal quality distribution information according to the signal quality information and the position information. According to the method and the device, the signal quality distribution information is determined according to the signal quality information and the position information, and the signal quality distribution information can be used for guiding the communication connection between the unmanned aerial vehicle and the base station in the flight process, so that the communication quality of the unmanned aerial vehicle and the base station is improved.

Description

Information processing method, unmanned aerial vehicle, server and storage medium

Technical Field

The embodiment of the application relates to the technical field of communication, in particular to an information processing method, an unmanned aerial vehicle, a server and a storage medium.

Background

At present, the communication technology of unmanned aerial vehicles is rapidly developed. The unmanned aerial vehicle can communicate with a server, other unmanned aerial vehicle and other equipment through the base station so as to carry out data transmission. However, since the base station is deployed for a terminal device such as a mobile phone that moves on the ground, the signal coverage capability of the space region near the ground is strong, but the signal coverage capability of the space region above the ground is poor. The unmanned aerial vehicle flies in the region that signal quality is poor, takes place communication quality decline easily, takes place communication interruption even, leads to unmanned aerial vehicle's operation effect relatively poor.

Disclosure of Invention

The embodiment of the application provides an information processing method, an unmanned aerial vehicle, a server and a storage medium, which are used for improving communication quality between the unmanned aerial vehicle and a base station.

In a first aspect, an embodiment of the present application provides an information processing method, including:

acquiring signal quality information of a base station, wherein the signal quality information is measured based on communication connection with the base station in the flight process of an unmanned aerial vehicle;

acquiring position information of the unmanned aerial vehicle when measuring the signal quality information;

and determining signal quality distribution information according to the signal quality information and the position information.

In a second aspect, an embodiment of the present application provides an information processing method, where the method is applied to a unmanned aerial vehicle, and the method includes:

acquiring signal quality information of a base station, wherein the signal quality information is obtained by measuring based on communication connection with the base station in the flight process of an unmanned aerial vehicle;

and transmitting the signal quality information and the position information to a server, wherein the signal quality information and the position information are used for determining signal quality distribution information by the server.

In a third aspect, an embodiment of the present application provides an information processing method, where the method is applied to a server, and the method includes:

receiving signal quality information and position information sent by an unmanned aerial vehicle, wherein the signal quality information is obtained by measuring the unmanned aerial vehicle based on communication connection with the base station in the flight process of the unmanned aerial vehicle, and the position information is the position information of the unmanned aerial vehicle when the signal quality information is measured;

In a fourth aspect, an embodiment of the present application provides an information processing method, where the method is applied to a unmanned aerial vehicle, and the method includes:

receiving signal quality distribution information sent by a server;

and selecting a base station for establishing communication connection according to the signal quality distribution information.

In a fifth aspect, an embodiment of the present application provides an information processing method, where the method is applied to a server, and the method includes:

transmitting signal quality distribution information to the unmanned aerial vehicle;

the signal quality distribution information is used for the unmanned aerial vehicle to select a base station for establishing communication connection.

In a sixth aspect, an embodiment of the present application provides an electronic device, including:

The communication module is used for acquiring signal quality information of the base station, wherein the signal quality information is measured based on communication connection with the base station in the flight process of the unmanned aerial vehicle;

the communication module is further used for acquiring the position information of the unmanned aerial vehicle when the signal quality information is measured;

and the processor is used for determining signal quality distribution information according to the signal quality information and the position information.

In a seventh aspect, embodiments of the present application provide a unmanned aerial vehicle, including:

the processor is used for acquiring signal quality information of the base station, wherein the signal quality information is obtained by measuring the signal quality information based on communication connection with the base station in the flight process of the unmanned aerial vehicle;

the processor is further used for acquiring the position information of the unmanned aerial vehicle when the signal quality information is measured;

and the communication module is used for sending the signal quality information and the position information to a server, wherein the signal quality information and the position information are used for determining signal quality distribution information by the server.

In an eighth aspect, embodiments of the present application provide a server, including:

the communication module is used for receiving signal quality information and position information sent by the unmanned aerial vehicle, wherein the signal quality information is obtained by measuring the unmanned aerial vehicle based on communication connection with the base station in the flight process of the unmanned aerial vehicle, and the position information is the position information of the unmanned aerial vehicle when the signal quality information is measured;

In a ninth aspect, embodiments of the present application provide a unmanned aerial vehicle, including:

the communication module is used for receiving the signal quality distribution information sent by the server;

and the processor is used for selecting a base station for establishing communication connection according to the signal quality distribution information.

In a tenth aspect, embodiments of the present application provide a server, including:

the communication module is used for sending signal quality distribution information to the unmanned aerial vehicle;

In an eleventh aspect, embodiments of the present application provide a readable storage medium having a computer program stored thereon; the computer program, when executed, implements the information processing method as described in the embodiments of the first aspect of the present application.

In a twelfth aspect, embodiments of the present application provide a readable storage medium having a computer program stored thereon; the computer program, when executed, implements the information processing method as described in the embodiments of the second aspect.

In a thirteenth aspect, embodiments of the present application provide a readable storage medium having a computer program stored thereon; the computer program, when executed, implements an information processing method as described in the embodiments of the third aspect of the present application.

In a fourteenth aspect, embodiments of the present application provide a readable storage medium having a computer program stored thereon; the computer program, when executed, implements the information processing method as described in the embodiment of the fourth aspect.

In a fifteenth aspect, embodiments of the present application provide a readable storage medium having a computer program stored thereon; the computer program, when executed, implements the information processing method as described in the embodiments of the fifth aspect.

According to the information processing method, the unmanned aerial vehicle, the server and the storage medium, the unmanned aerial vehicle is used for measuring the signal quality information of the base station based on the communication connection with the base station in the flight process, the position information of the unmanned aerial vehicle is obtained when the signal quality information is measured, the signal quality distribution information is determined according to the signal quality information and the position information, and the signal quality distribution information can be used for guiding the communication connection with the base station in the unmanned aerial vehicle flight process, so that the communication quality of the unmanned aerial vehicle and the base station is improved.

Drawings

For a clearer description of the embodiments of the present application, the drawings that are needed in the description of the embodiments will be briefly described, it being apparent that the drawings in the description below are some embodiments of the present application, and other drawings may be obtained according to these drawings without inventive effort for a person of ordinary skill in the art.

Fig. 1 is a schematic view of a scenario of an information processing method according to an embodiment of the present application;

FIG. 2 is a flowchart of an information processing method according to an embodiment of the present application;

FIG. 3 is a flowchart of an information processing method according to another embodiment of the present application;

FIG. 4 is a flowchart of an information processing method according to another embodiment of the present application;

fig. 5 is a signaling interaction diagram of an information processing method provided in an embodiment of the present application;

FIG. 6 is a flowchart of an information processing method according to another embodiment of the present application;

FIG. 7 is a flowchart of an information processing method according to a further embodiment of the present application;

FIG. 8 is a flowchart of an information processing method according to a further embodiment of the present application;

FIG. 9 is a flowchart of an information processing method according to another embodiment of the present application;

FIG. 10 is a flowchart of an information processing method according to still another embodiment of the present application;

FIG. 11 is a flowchart of an information processing method according to a further embodiment of the present application;

fig. 12 is a signaling interaction diagram of an information processing method according to an embodiment of the present application;

fig. 13 is a schematic structural diagram of an electronic device according to an embodiment of the present disclosure;

fig. 14 is a schematic structural diagram of a drone according to another embodiment of the present disclosure;

fig. 15 is a schematic structural diagram of a server according to another embodiment of the present application;

fig. 16 is a schematic structural view of a drone according to another embodiment of the present disclosure;

fig. 17 is a schematic structural diagram of a server according to another embodiment of the present application.

Detailed Description

For the purposes of making the objects, technical solutions and advantages of the embodiments of the present application more clear, the technical solutions of the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is apparent that the described embodiments are some embodiments of the present application, but not all embodiments. All other embodiments, which can be made by one of ordinary skill in the art based on the embodiments herein without making any inventive effort, are intended to be within the scope of the present application.

Some embodiments of the present application are described in detail below with reference to the accompanying drawings. The following embodiments and features of the embodiments may be combined with each other without conflict.

At present, the communication technology of unmanned aerial vehicles is rapidly developed. The unmanned aerial vehicle can communicate with a server, other unmanned aerial vehicle and other equipment through the base station so as to carry out data transmission. However, since the base station is deployed for a terminal device such as a mobile phone that moves on the ground, the signal coverage capability of the space region near the ground is strong, but the signal coverage capability of the space region above the ground is poor. The unmanned aerial vehicle flies into the region with poor signal quality, so that the communication quality is easy to be reduced, and even the communication is interrupted.

For example, the drone may encounter situations when communicating with a base station that include, but are not limited to, the following: in the first case, the unmanned aerial vehicle is switched from a base station with good signal quality to a base station with poor signal quality in the flying process, so that the communication quality is reduced. In the second case, along with the change of the flight position of the unmanned aerial vehicle, the communication channel between the unmanned aerial vehicle and a base station is changed, and a Line of Sight (LOS) channel is changed into a non-Line of Sight (Non Line of Sight, NLOS) channel, or the relative position and direction between the unmanned aerial vehicle and the base station are changed, so that the unmanned aerial vehicle does not correspondingly adjust the communication parameters, thereby reducing the communication quality and even interrupting the communication. In the third case, the unmanned aerial vehicle enters an area where the signal quality of all base stations is poor, so that communication is interrupted.

According to the method and the device, the signal quality information of the base station is obtained through measurement of the unmanned aerial vehicle in the flight process based on communication connection with the base station, the position information of the unmanned aerial vehicle when the signal quality information is measured is obtained, the signal quality distribution information is determined according to the signal quality information and the position information, the signal quality distribution information can be used for guiding the communication connection between the unmanned aerial vehicle and the base station in the flight process, and therefore the communication quality of the unmanned aerial vehicle and the base station is improved.

Fig. 1 is a schematic view of a scenario of an information processing method according to an embodiment of the present application. In fig. 1 is drawn a drone 11, a base station 12, a server 13 and a control terminal 14.

The drone 11 may include, among other things, a power system, a flight control system, a communication module, and a frame. The power system may include one or more electronic speed adjusters, one or more propellers, and one or more motors corresponding to the one or more propellers, wherein the motors are connected between the electronic speed adjusters and the propellers, the motors and the propellers being disposed on a horn of the unmanned aerial vehicle; the electronic speed regulator is used for receiving a driving signal generated by the flight control system and providing driving current for the motor according to the driving signal so as to control the rotating speed of the motor. The motor is used to drive the propeller in rotation to power the flight of the drone 11, which enables the drone 11 to achieve one or more degrees of freedom of movement. It should be appreciated that the motor may be a direct current motor or an alternating current motor. The motor may be a brushless motor or a brushed motor.

The flight control system may include a flight controller and a sensing system. The sensing system is used for measuring attitude information of the unmanned aerial vehicle, namely position information and state information of the unmanned aerial vehicle 11 in space, such as three-dimensional position, three-dimensional angle, three-dimensional speed, three-dimensional acceleration, three-dimensional angular speed and the like. The sensing system may include, for example, at least one of a gyroscope, an ultrasonic sensor, an electronic compass, an inertial measurement unit (Inertial Measurement Unit, IMU), a vision sensor, a global navigation satellite system, and a barometer. For example, the global navigation satellite system may be a global positioning system (Global Positioning System, GPS). The unmanned aerial vehicle 11 is configured to control the flight of the unmanned aerial vehicle 11, for example, the flight of the unmanned aerial vehicle 11 may be controlled according to the gesture information measured by the sensing system. It should be appreciated that the drone 11 may control the drone 11 in accordance with preprogrammed instructions, or the drone 11 may be controlled in response to one or more remote control signals from the control terminal 14.

The communication module is used for the unmanned aerial vehicle 11 to communicate with the base station 12 and the control terminal 14. The communication between the unmanned aerial vehicle 11 and the base station 12 may be a communication technology such as 2G, 3G, 4G, 5G, etc., which is not limited herein. The base station 12 may forward the data sent by the drone 11 to the server 13 or the control terminal 14. The base station 12 and the server 13 may communicate with each other by wired communication or wireless communication, which is not limited herein. The unmanned aerial vehicle 11 and the control terminal 14 may also directly communicate with each other, for example, wireless fidelity (Wireless Fidelity, wi-Fi), bluetooth, narrowband internet of things (Narrow Band Internet of Things, NB-IoT), loRa, global system for mobile communications (Global System for Mobile Communications, GSM), zigbee, ultra Wideband (UWB), code division multiple access (Code Division Multiple Access, CDMA), 4G, 5G, and other communication technologies may be used, which are not limited herein.

The frame may include a fuselage and a foot rest (also referred to as landing gear). The fuselage may include a center frame and one or more arms coupled to the center frame, the one or more arms extending radially from the center frame. The foot rest is connected with the fuselage for supporting the unmanned aerial vehicle 11 when landing.

The control terminal 14 may include, but is not limited to, one or more of the following: remote controls, smart phones, desktop computers, laptop computers, wearable devices, etc.

One or more base stations 12 are deployed in the spatial region, each base station 12 corresponding to a certain signal coverage area. The drone may communicate with a base station 12 as the drone flies within the signal coverage of the base station 12.

In this embodiment, when the unmanned aerial vehicle 11 flies to a location point, the signal quality information of the base station whose signal coverage includes the location point may be measured, the location information of the location point may be obtained, and the signal quality information and the location information may be reported to the server 13. Alternatively, the drone 11 may transmit the signal quality information and the location information to the base station 12 currently establishing the connection, and the base station 12 transmits the signal quality information and the location information to the service 13; the unmanned aerial vehicle 11 may transmit the signal quality information and the position information to the control terminal 14, and the control terminal 14 may report the signal quality information and the position information to the server 13.

The server 13 generates signal quality distribution information based on the signal quality information and the position information, or updates the generated signal quality distribution information based on the signal quality information and the position information, thereby obtaining updated signal quality distribution information. When the unmanned aerial vehicle 11 flies to the position point next time, or when other unmanned aerial vehicles 11 fly to the position point, the server 13 can issue signal quality distribution information to the unmanned aerial vehicle 11, so that the unmanned aerial vehicle 11 performs flight control and/or communication control on itself according to the signal quality distribution information, so as to avoid flying to a position with poor signal quality, avoid establishing connection with a base station with poor signal quality, and the like, thereby avoiding communication quality degradation with the base station and improving communication quality with the base station.

In one scenario, the server 13 may send a control instruction to the drone 11 according to the signal quality distribution information to perform flight control and/or communication control on the drone 11 when the drone 11 next flies to the location point, or when other drones 11 fly to the location point. The server 13 may issue the signal quality distribution information to the control terminal 14 of the unmanned aerial vehicle 11, and the control terminal 14 may send a control command to the unmanned aerial vehicle 11 according to the signal quality distribution information to perform flight control and/or communication control on the unmanned aerial vehicle 11, which is not limited herein.

The server 13 may be a commercial server of a communication carrier, on which a relevant operation program of the unmanned aerial vehicle is installed, so as to update the signal quality distribution information. The server 13 may be a background server of the unmanned aerial vehicle. In addition, the server may manage data relating to one or more unmanned aerial vehicles, and may also manage data relating to other mobile platforms, e.g., vehicles, watercraft. The relevant data of the control terminals of the movable platforms can be managed, such as terminal equipment of remote controllers, mobile phones, tablet computers and the like.

In one scenario, after the unmanned aerial vehicle 11 measures the signal quality information and the position information, the signal quality information and the position information may be transmitted to the control terminal 14, and the control terminal 14 generates or updates the signal quality distribution information according to the signal quality information and the position information.

In one scenario, after the signal quality information and the position information are measured by the drone 11, the signal quality distribution information may be generated or updated by the drone 11 itself according to the signal quality information and the position information.

It should be noted that, the information processing method provided in the embodiment of the present application is not limited to the above-mentioned scenario, but may be applied to other scenarios, and is not limited thereto.

Fig. 2 is a flowchart of an information processing method according to an embodiment of the present application. The execution body of the flowchart is an electronic device, which may be an unmanned aerial vehicle, a server, a control terminal, etc. in fig. 1, and is not limited. The method may include:

s201, acquiring signal quality information of a base station, wherein the signal quality information is measured based on communication connection with the base station in the flight process of the unmanned aerial vehicle.

S202, acquiring position information of the unmanned aerial vehicle when measuring signal quality information.

In this embodiment, the signal quality information includes, but is not limited to, one or more of the following: received Signal strength indication (Received Signal Strength Indication, RSSI), reference Signal received power (Reference Signal Receiving Power, RSRP), reference Signal received quality (Reference Signal Receiving Quality, RSRQ), signal-to-Noise Ratio (SNR), signal-to-interference-and-Noise Ratio (Signal to Interference plus Noise Ratio, SINR), channel quality indication (Channel Quality Indication, CQI), channel state information (Channel State Information, CSI), channel impulse response (Channel Impluse Response, CIR), channel frequency response (Channel Frequency Response, CFR), channel matrix, modulation and coding strategy (Modulation and Coding Scheme, MCS), block Error rate (BLER), bit Error rate (Bit Error Ratio, BER), and the like.

Each base station corresponds to a respective signal coverage area. When the drone flies to a location point, it can communicate with at least some of the base stations whose signal coverage includes the location point to measure signal quality information of at least some of the base stations at the location point. The unmanned aerial vehicle can acquire the position information of the position point through a positioning device such as a global navigation satellite system, an inertial measurement unit and the like. Wherein, the global navigation satellite system can be a Beidou satellite navigation system

BeiDou Navigation Satellite System, BDS), global positioning system (Global Positioning System, GPS), etc. The location information may include three-dimensional spatial coordinates of the location point.

When the electronic device is other devices except the unmanned aerial vehicle, such as a server, a control terminal and the like, the unmanned aerial vehicle can actively send the signal quality information and the position information to the electronic device, and can also send the signal quality information and the position information to the electronic device after receiving the request of the electronic device.

S203, determining signal quality distribution information according to the signal quality information and the position information.

In this embodiment, the signal quality distribution information characterizes the signal quality distribution in the three-dimensional space. The signal quality distribution information may include location information of a plurality of location points and corresponding signal quality information. The signal quality distribution information may be displayed and stored in the form of a distribution map, a relationship table, or the like, without limitation. For example, the signal quality distribution information may be a signal quality distribution diagram in a three-dimensional space, and at least some position points in the signal quality distribution diagram correspond to the signal quality information. The signal quality information corresponding to each position point comprises the signal quality information of at least one base station at the position point.

The electronic device may generate signal quality distribution information based on the signal quality information and the location information. For example, for a spatial region where signal quality information is first collected, the electronic device may generate signal quality distribution information according to signal quality information and position information measured during flight of the unmanned aerial vehicle.

The electronic device may update the existing signal quality distribution information according to the signal quality information and the location information. For example, the electronic device may search for whether the location information already has corresponding signal quality information in the existing signal quality distribution information, and if not, store the newly measured signal quality information in association with the location information into the signal quality distribution information; if yes, judging whether the signal quality information corresponding to the position point is consistent with the newly measured signal quality information, and if not, updating the newly measured signal quality information.

In the embodiment of the application, the signal quality information of the base station is obtained through measurement of the unmanned aerial vehicle in the flight process based on communication connection with the base station, the position information of the unmanned aerial vehicle when the signal quality information is measured is obtained, the signal quality distribution information is determined according to the signal quality information and the position information, and the signal quality distribution information can be used for guiding the communication connection between the unmanned aerial vehicle and the base station in the flight process, so that the communication quality of the unmanned aerial vehicle and the base station is improved.

In this embodiment of the present application, the signal quality distribution information may be used to instruct the unmanned aerial vehicle to perform flight control and/or communication control, so as to improve the communication quality between the unmanned aerial vehicle and the base station in the flight process. The following is a description of seven embodiments based on the embodiment of fig. 2.

In a first embodiment, the signal quality distribution information is used for the target drone to select the base station that establishes the communication connection.

In this embodiment, the target unmanned aerial vehicle is an unmanned aerial vehicle flying in a target space region. The target spatial region is a spatial region corresponding to the signal quality distribution information. The target unmanned aerial vehicle can be an unmanned aerial vehicle for measuring signal quality information, and when the unmanned aerial vehicle flies to a target space area next time, a base station for establishing communication connection can be selected according to the signal quality distribution information. The target drone may also be a drone flying to a target spatial region, in addition to the drone measuring signal quality information.

The target unmanned aerial vehicle can determine the signal quality of the base station corresponding to the designated position point according to the signal quality distribution information. When the number of the base stations corresponding to the designated location point is one, the base station corresponding to the designated location point is selected to establish communication connection at the designated location point. When the number of the base stations corresponding to the designated location point is multiple, selecting the base station with the optimal signal quality from the plurality of base stations corresponding to the designated location point on the designated location point to establish communication connection.

Optionally, the designated location point includes, but is not limited to, at least one of: the method comprises the steps of a current position point of a target unmanned aerial vehicle, a next position point of the target unmanned aerial vehicle, and a navigation point on a preset navigation line of the target unmanned aerial vehicle. When the number of the base stations corresponding to the designated location point is multiple, the target unmanned aerial vehicle can acquire signal quality information of each base station corresponding to the designated location point from the signal quality distribution information, and the base station with the optimal signal quality is determined according to the signal quality information of each base station and a preset mode. The preset mode may be determined according to actual requirements, and is not limited herein. The preset manner may be to select one item of data in the signal quality information for comparison, and determine the base station with the optimal signal quality, for example, select the base station with the highest RSRQ as the base station with the optimal signal quality, or select the base station with the highest SINR as the base station with the optimal signal quality. The preset mode may be that the base station is scored according to multiple items of data in the signal quality information, and the base station with the highest score is used as the base station with the optimal signal quality. For example, each base station may be scored according to RSRP, RSRQ, SINR, etc., to obtain a score for each base station.

In this embodiment, the signal quality distribution information may be used for determining the signal quality of the base station corresponding to the designated location point by the target unmanned aerial vehicle, so that the target unmanned aerial vehicle does not need to perform base station measurement at each location point, and the time for switching the base station can be reduced, thereby improving the communication quality; when a plurality of base stations corresponding to the designated position points are provided, communication connection is established by selecting the base station with the optimal signal quality, so that the target unmanned aerial vehicle can be connected to the base station with relatively good signal quality, and the communication quality is improved; the base station to be connected with the next position point and the navigation point on the preset navigation line is determined in advance, and proper time and position can be selected in advance to complete the communication link switching between the target unmanned aerial vehicle and the adjacent base station, so that the time and communication expense for switching the base station are reduced, the target unmanned aerial vehicle is ensured to be always in the coverage range of the base station with optimal communication quality, and the communication quality is further improved.

In the second embodiment, the signal quality distribution information is used for the target unmanned aerial vehicle to select a route with the optimal signal quality from a plurality of routes according to the signal quality information of each waypoint on the route.

In this embodiment, in a scenario where the target unmanned aerial vehicle performs route planning, the target unmanned aerial vehicle may plan to obtain a plurality of routes from the starting position point to the target position point, then determine signal quality of each waypoint in each route according to the signal quality distribution information, and determine a route with the optimal signal quality from the plurality of routes.

The target unmanned aerial vehicle can plan a plurality of routes from the starting position point to the target position point according to the electronic map. The starting position point and the target position point may be determined according to actual requirements, which are not limited herein. For example, in a scene of automatic return of the target unmanned aerial vehicle, the starting position point may be a current position point of the target unmanned aerial vehicle, and the target position point is a position point where the control terminal is located; when the user indicates that the target unmanned aerial vehicle automatically navigates to reach the position point of image acquisition, the initial position point can be the current position point of the target unmanned aerial vehicle, and the target position point is the position point of image acquisition indicated by the user.

Optionally, the target unmanned aerial vehicle may search corresponding signal quality information from the signal quality distribution information according to the position information of each waypoint in each route, so as to determine the signal quality of each waypoint in each route. Then, for each route, the target unmanned aerial vehicle can determine the signal quality of the route according to the signal quality of each waypoint on the route. The target unmanned aerial vehicle compares the signal quality of each route, so that the route with the optimal communication quality in a plurality of routes is determined.

Taking a scene of automatic return of the target unmanned aerial vehicle as an example, a user sends an instruction through the control terminal to instruct the target unmanned aerial vehicle to automatically navigate from the current position to return to the position of the control terminal. The target unmanned aerial vehicle can plan to obtain a plurality of routes from the current position to the position of the control terminal, then select a route with optimal signal quality from the plurality of routes according to the signal quality distribution information, and return to the position of the control terminal along the route.

In the embodiment, the signal quality distribution information is used for determining the route with the optimal signal quality in a plurality of routes when the target unmanned aerial vehicle is in route planning, so that the target unmanned aerial vehicle flies along the route with the optimal signal quality, and the communication quality between the target unmanned aerial vehicle and the base station is improved.

In a third embodiment, the signal quality distribution information is used for the target unmanned aerial vehicle to avoid waypoints on the preset route for which the signal quality is lower than the first threshold.

In this embodiment, in a scene where the target unmanned aerial vehicle flies along the preset route, a waypoint with signal quality lower than the first threshold on the preset route may be determined according to the signal quality distribution information, and then the preset route is adjusted, so that the adjusted preset route avoids the waypoint with signal quality lower than the first threshold.

Optionally, when the target unmanned aerial vehicle flies along the preset route, or before flying, the signal quality of each waypoint on the preset route can be determined according to the signal quality distribution information, then the signal quality of each waypoint is compared with a first threshold value, and if the waypoint with the signal quality lower than the first threshold value exists, the preset route is adjusted, so that the adjusted preset route avoids the waypoint with the signal quality lower than the first threshold value. For example, the target unmanned aerial vehicle may select one or more newly added waypoints within a preset range of waypoints having a signal quality below a first threshold to replace the waypoints having the signal quality below the first threshold to form an adjusted preset course. The first threshold may be set accordingly according to a determination manner of the signal quality, which is not limited herein. For example, the signal quality is determined using RSRP, then the first threshold may be-85 dBm; the signal quality is determined using scores of the plurality of data, and the first threshold is a set score threshold.

According to the method and the device, the target unmanned aerial vehicle can avoid the waypoints with poor signal quality on the preset route, so that the communication quality between the target unmanned aerial vehicle and the base station when the target unmanned aerial vehicle flies along the preset route is improved.

In a fourth embodiment, the signal quality distribution information is used to avoid areas where the signal quality is below the second threshold when the target unmanned aerial vehicle is planning the route.

In this embodiment, the target unmanned aerial vehicle may determine, according to the signal quality distribution information, an area where the signal quality is lower than the second threshold. When the target unmanned aerial vehicle performs route planning, a route from the starting position point to the target position point can be planned in an area outside the area with the signal quality lower than the second threshold value.

The signal quality of a region may be determined according to the signal quality of each location point in the region, and the specific determination method is not limited herein. For example, the average value of the signal quality of each position point in the area is taken as the signal quality of the area, or the minimum value of the signal quality of each position point in the area is taken as the signal quality of the area. The division of the area may be set according to actual requirements, and is not limited herein.

Optionally, the target unmanned aerial vehicle determines the signal quality of each position point in each area according to the signal quality distribution information, and then determines the signal quality of each area according to the signal quality of each position point in each area. The signal quality of each region is compared to a second threshold to determine regions having signal quality below the second threshold. When the target unmanned aerial vehicle performs route planning, the route from the starting position point to the target position point can be planned in the area outside the area with the signal quality lower than the second threshold value.

According to the method, the area with poor signal quality is determined by the signal quality distribution information, and the route is made to bypass the areas when the target unmanned aerial vehicle performs route planning, so that the target unmanned aerial vehicle is prevented from flying to the area with poor signal quality, and the communication quality between the target unmanned aerial vehicle and the base station is improved.

In a fifth embodiment, the signal quality distribution information is used for sending warning information to the control terminal when the target unmanned aerial vehicle approaches the area where the signal quality is lower than the second threshold.

In this embodiment, the target unmanned aerial vehicle may determine, according to a preset proximity condition, an area where the quality of the proximity signal of the target unmanned aerial vehicle is lower than a second threshold. The preset proximity condition is not limited herein, for example, the preset proximity condition may be that the distance between the current location point of the target unmanned aerial vehicle and the area is smaller than a preset distance threshold, or the target unmanned aerial vehicle enters a preset space range centered on the area, or the like.

For example, in a scenario in which the user manually controls the target drone to fly through the control terminal, the target drone may send alert information to the control terminal to prompt the user to control the target drone not to enter the area when it is determined that the proximity signal quality is below the second threshold.

In this embodiment, when the target unmanned aerial vehicle approaches the area with poor signal quality, the user is prompted through the warning information, so that the user can be prevented from controlling the target unmanned aerial vehicle to fly to the area with poor signal quality, and the communication quality between the target unmanned aerial vehicle and the base station is improved.

In the sixth embodiment, the signal quality distribution information is used to disconnect the communication connection with the base station and establish the communication connection with the control terminal of the target unmanned aerial vehicle when the target unmanned aerial vehicle is located in the area where the signal quality is lower than the second threshold.

In this embodiment, when the target unmanned aerial vehicle has flown into the area where the signal quality is lower than the second threshold, the communication mode of the target unmanned aerial vehicle may be switched from data transmission through the base station to data transmission through the control terminal, so as to ensure that the data transmission of the target unmanned aerial vehicle is not interrupted.

In the seventh embodiment, the signal quality distribution information is used to stop transmitting the collected image through the base station when the target unmanned aerial vehicle is located in the area where the signal quality is lower than the second threshold value, and resume transmitting the collected image through the base station after leaving the area where the signal quality is lower than the second threshold value.

In this embodiment, when the flight task of the target unmanned aerial vehicle is to collect an image, when the target unmanned aerial vehicle has flown into an area with signal quality lower than the second threshold, the transmission of the collected image through the base station may be stopped, so as to prevent an image transmission error caused by poor signal quality. The target drone may continue to capture images and store the images in an internal memory of the target drone. After the target unmanned aerial vehicle flies away from the area, the image in the internal memory is sent to the base station, and the base station sends the image to the server or the control terminal.

In the embodiment, when the target unmanned aerial vehicle is located in the area with the signal quality lower than the second threshold value, the collected image is stopped being sent through the base station, and after the target unmanned aerial vehicle leaves the area, the collected image is restored to be sent through the base station, so that the image transmission error is prevented.

As an embodiment of the present application, the signal quality information and the location information are further used to update the communication policy model on the basis of any of the above embodiments. The method may further comprise:

and updating a communication strategy model according to the signal quality information and the position information, wherein the communication strategy model is used for determining communication parameters for communication with the base station by the target unmanned aerial vehicle.

In this embodiment, a communication policy model is preset in the electronic device. The communication policy model may be pre-generated based on the location information and corresponding signal quality information for the drone to determine communication parameters with the base station. The communication parameters may include, but are not limited to, at least one of: beamforming parameters, channel coding strategy, channel modulation strategy, channel type, etc.

The specific form of the communication policy model is not limited herein, and for example, the communication policy model may include a deep learning-based communication parameter prediction model. The input of the communication parameter prediction model is position information, and the output is communication parameters. The generation process of the communication parameter prediction model can be as follows: pre-constructing a communication parameter prediction model based on deep learning; then, acquiring a plurality of position information and corresponding signal quality information thereof, and determining communication parameters corresponding to each position information according to the signal quality information corresponding to each position information; and then forming a sample set from each position information and the corresponding communication parameters, and training the constructed communication parameter prediction model by adopting the sample set, so as to generate the communication parameter prediction model, and enabling the communication parameter prediction model to output predicted communication parameters according to the input position information.

The communication policy model may also include a mapping table of location information and communication parameters. In the map table, each piece of position information corresponds to a respective communication parameter. And when the unmanned aerial vehicle flies on the position point of the position information, the communication quality of the communication between the unmanned aerial vehicle and the base station by adopting the communication parameters is optimal. The generation process of the mapping relation table can be as follows: acquiring a plurality of position information and corresponding signal quality information thereof; then, according to the signal quality information corresponding to each position information, determining the communication parameters corresponding to each position information; and carrying out association storage on each position information and the corresponding communication parameters thereof, thereby obtaining a mapping relation table.

According to the embodiment, through the communication strategy model, the unmanned aerial vehicle can communicate with the base station by adopting proper communication parameters, and further the communication quality between the unmanned aerial vehicle and the base station is improved. After the electronic device obtains the signal quality information and the position information, the communication strategy model can be updated according to the signal quality information and the position information.

Optionally, when the communication policy model includes a deep learning-based communication parameter prediction model, updating the communication policy model according to the signal quality information and the location information may specifically include:

Generating training samples according to the signal quality information and the position information;

adding training samples to the training set;

and training the communication parameter prediction model according to the training set so as to update the communication parameter prediction model.

In this embodiment, the training samples include location information and corresponding communication parameters. The communication parameters corresponding to the position information can be determined according to the signal quality information, and then the position information and the communication parameters corresponding to the position information are formed into training samples and added into the training set. And training the current communication parameter prediction model by using the training set to obtain an updated communication parameter prediction model.

According to the embodiment, the communication parameter prediction model is updated through the signal quality information and the position information, so that the prediction accuracy of the communication parameter prediction model can be improved.

Optionally, when the communication policy model includes the mapping relation table of the location information and the communication parameters, updating the communication policy model according to the signal quality information and the location information may specifically include:

determining communication parameters corresponding to the position information according to the signal quality information;

and updating the position information and the communication parameters corresponding to the position information into a mapping relation table.

According to the embodiment, the mapping relation table is updated through the signal quality information and the position information, so that the data in the mapping relation table can be updated in time, and the mapping relation table is more perfect.

Fig. 3 is a flowchart of an information processing method according to another embodiment of the present application. The method is performed by the unmanned aerial vehicle in fig. 1. As shown in fig. 3, the method may include:

s301, the unmanned aerial vehicle acquires signal quality information of a base station, wherein the signal quality information is obtained by measuring the unmanned aerial vehicle based on communication connection with the base station in the flight process.

S302, the unmanned aerial vehicle obtains position information of the unmanned aerial vehicle when measuring signal quality information.

S303, the unmanned aerial vehicle sends signal quality information and position information to the server, wherein the signal quality information and the position information are used for determining signal quality distribution information by the server.

In this embodiment, when the unmanned aerial vehicle flies to a location point in the flying process, the unmanned aerial vehicle may communicate with at least part of the base stations whose signal coverage area includes the location point, so as to measure signal quality information of at least part of the base stations at the location point. The unmanned aerial vehicle can acquire the position information of the position point through a positioning device such as a global navigation satellite system, an inertial measurement unit and the like. And transmitting the signal quality information and the position information to a server, and determining signal quality distribution information according to the signal quality information and the position information by the server.

According to the method and the device, the signal quality information of the base station is obtained through measurement of the unmanned aerial vehicle in the flight process based on communication connection with the base station, the position information of the unmanned aerial vehicle is obtained when the signal quality information is measured, the signal quality information and the position information are sent to the server, the signal quality distribution information is determined by the server according to the signal quality information and the position information, and the signal quality distribution information can be used for guiding the communication connection between the unmanned aerial vehicle and the base station in the flight process, so that the communication quality between the unmanned aerial vehicle and the base station is improved.

Optionally, S303 may specifically include: and sending the signal quality information and the position information to a server through a base station which establishes communication connection with the unmanned aerial vehicle or a control terminal of the unmanned aerial vehicle.

In this embodiment, the unmanned aerial vehicle may transmit signal quality information and position information to a base station currently establishing a communication connection, and the base station transmits the signal quality information and the position information to the server. The unmanned aerial vehicle may also transmit signal quality information and position information to the control terminal, which transmits the signal quality information and position information to the server.

As an embodiment of the present application, the signal quality distribution information includes location information of a plurality of location points and signal quality information on the basis of the embodiment shown in fig. 3.

In this embodiment of the present application, the signal quality distribution information may be used to instruct the unmanned aerial vehicle to perform flight control and/or communication control, so as to improve the communication quality between the unmanned aerial vehicle and the base station in the flight process. The following is a description of several embodiments based on the embodiment of fig. 3.

In one embodiment, the signal quality distribution information is used for the target drone to select a base station to establish a communication connection.

In one embodiment, the signal quality distribution information is used for the target unmanned aerial vehicle to select a route with the optimal signal quality from a plurality of routes according to the signal quality information of each waypoint on the route.

In one embodiment, the signal quality distribution information is used for the target unmanned aerial vehicle to evade waypoints on the preset route for which the signal quality is below the first threshold.

In one embodiment, the signal quality distribution information is used to circumvent areas where the signal quality is below a second threshold when the target drone is planning the route.

In one embodiment, the signal quality distribution information is used for sending warning information to the control terminal when the target unmanned aerial vehicle approaches an area with signal quality lower than a second threshold value.

In one embodiment, the signal quality distribution information is used to disconnect the communication connection with the base station and establish the communication connection with the control terminal of the target drone when the target drone is located in an area where the signal quality is below the second threshold.

In one embodiment, the signal quality distribution information is used to stop sending the acquired image through the base station when the target drone is located in an area where the signal quality is below the second threshold, and to resume sending the acquired image through the base station after leaving the area where the signal quality is below the second threshold.

Optionally, in the above embodiment, the target unmanned aerial vehicle is an unmanned aerial vehicle flying in a target space region.

As an embodiment of the present application, on the basis of the embodiment shown in fig. 3, or on the basis of any embodiment based on fig. 3, the signal quality information and the location information are further used for updating a communication policy model by the server, where the communication policy model is used for determining communication parameters for the target drone to communicate with the base station.

In one implementation, the communication strategy model includes a deep learning based communication parameter prediction model.

In another implementation, the communication policy model includes a mapping table of location information and communication parameters.

The information processing method of the present embodiment is similar to the technical solution of the embodiment of fig. 2 and the corresponding method, and its implementation principle and technical effects are similar, and are not repeated here.

Fig. 4 is a flowchart of an information processing method according to another embodiment of the present application. The method is performed by the server in fig. 1. As shown in fig. 4, the method may include:

S401, the server receives signal quality information and position information sent by the unmanned aerial vehicle, wherein the signal quality information is obtained by measuring the signal quality information based on communication connection with a base station in the flight process of the unmanned aerial vehicle, and the position information is the position information of the unmanned aerial vehicle when the signal quality information is measured.

S402, the server determines signal quality distribution information according to the signal quality information and the position information.

In this embodiment, when the unmanned aerial vehicle flies to a location point in the flying process, the unmanned aerial vehicle may communicate with at least part of the base stations whose signal coverage area includes the location point, so as to measure signal quality information of at least part of the base stations at the location point. The unmanned aerial vehicle can acquire the position information of the position point through a positioning device such as a global navigation satellite system, an inertial measurement unit and the like. The unmanned aerial vehicle sends signal quality information and position information to the server. The server receives the signal quality information and the position information sent by the unmanned aerial vehicle, and determines signal quality distribution information according to the signal quality information and the position information.

According to the method and the device, the signal quality information of the base station is obtained through measurement of the unmanned aerial vehicle in the flight process based on communication connection with the base station, the position information of the unmanned aerial vehicle is obtained when the signal quality information is measured, the signal quality information and the position information are sent to the server, the server determines signal quality distribution information according to the signal quality information and the position information, and the signal quality distribution information can be used for guiding the communication connection between the unmanned aerial vehicle and the base station in the flight process, so that the communication quality between the unmanned aerial vehicle and the base station is improved.

Optionally, S402 may include: the server receives signal quality information and position information sent by a base station which establishes communication connection with the unmanned aerial vehicle or a control terminal of the unmanned aerial vehicle.

In this embodiment, the server may receive the signal quality information and the location information forwarded by the base station, or may receive the signal quality information and the location information transmitted by the control terminal.

Optionally, in this implementation, updating the communication policy model according to the signal quality information and the location information may specifically include:

adding training samples to the training set;

Fig. 5 is a signaling interaction diagram of an information processing method according to an embodiment of the present application. The execution subject of the signal interaction diagram comprises an unmanned aerial vehicle and a server. The method comprises the following steps:

s501, the unmanned aerial vehicle acquires signal quality information of the base station, wherein the signal quality information is obtained by measuring the unmanned aerial vehicle based on communication connection with the base station in the flight process.

S502, the unmanned aerial vehicle obtains the position information of the unmanned aerial vehicle when measuring the signal quality information.

And S503, the unmanned aerial vehicle sends the signal quality information and the position information to the server.

S504, the server determines signal quality distribution information according to the signal quality information and the position information.

The information processing method of the present embodiment is similar to the technical solutions of the embodiments of fig. 3, fig. 4 and the corresponding methods, and its implementation principle and technical effects are similar, and are not repeated here.

Fig. 6 is a flowchart of an information processing method according to still another embodiment of the present application. The execution main body of the method is an unmanned aerial vehicle. As shown in fig. 6, the method may include:

s601, the unmanned aerial vehicle receives signal quality distribution information sent by a server.

In this embodiment, the unmanned aerial vehicle may send a request to the server during the flight, so as to request the server to send the signal quality distribution information. Alternatively, the request may carry location information of the specified location point, so as to request the server to issue signal quality distribution information of the target spatial area including the specified location point. Wherein the designated location point may include, but is not limited to, at least one of: the current position point of the unmanned aerial vehicle, the next position point of the unmanned aerial vehicle, the waypoint on the preset route of the unmanned aerial vehicle and the like.

In the flight process of the unmanned aerial vehicle, the signal quality distribution information actively issued by the server can also be received, and the signal quality distribution information can be the signal quality distribution information of the target space region including the position point which is determined and issued by the server according to the current position point of the unmanned aerial vehicle.

S602, the unmanned aerial vehicle selects a base station for establishing communication connection according to the signal quality distribution information.

In this embodiment, the unmanned aerial vehicle receives the signal quality distribution information sent by the server, and selects the base station to be connected with in the flight according to the signal quality distribution information, so that the unmanned aerial vehicle can establish communication connection with the base station with relatively good communication quality in the flight, and the communication quality between the unmanned aerial vehicle and the base station in the flight is improved.

Optionally, the signal quality distribution information includes location information of a plurality of location points and signal quality information.

Optionally, during the flight of the unmanned aerial vehicle, on one hand, a base station for establishing communication connection is selected according to the signal quality distribution information, on the other hand, at least part of the base stations of which the signal coverage area comprises the position points of the unmanned aerial vehicle are measured to obtain signal quality information of at least part of the base stations, and the signal quality information and the corresponding position information are uploaded to a server, so that the server updates the signal quality distribution information according to the signal quality information and the corresponding position information.

Fig. 7 is a flowchart of an information processing method according to another embodiment of the present application, based on the embodiment provided in fig. 6. As shown in fig. 7, the method may include:

S701, the unmanned aerial vehicle receives signal quality distribution information sent by a server.

S702, the unmanned aerial vehicle determines the signal quality of the base station corresponding to the designated position point according to the signal quality distribution information.

S703, when the base station corresponding to the appointed position point is one, the unmanned aerial vehicle selects the base station corresponding to the appointed position point on the appointed position point to establish communication connection; when the number of the base stations corresponding to the designated location point is multiple, the unmanned aerial vehicle selects a base station with the optimal signal quality from the multiple base stations corresponding to the designated location point on the designated location point to establish communication connection.

In this embodiment, the specified location point includes, but is not limited to, at least one of the following: the method comprises the steps of a current position point of the unmanned aerial vehicle, a next position point of the unmanned aerial vehicle, and a waypoint on a preset wayline of the unmanned aerial vehicle.

When the number of the base stations corresponding to the designated location point is multiple, the unmanned aerial vehicle can acquire signal quality information of each base station corresponding to the designated location point from the signal quality distribution information, and the base station with the optimal signal quality is determined according to the signal quality information of each base station and preset conditions. The preset mode may be determined according to actual requirements, and is not limited herein. The preset manner may be to select one item of data in the signal quality information for comparison, and determine the base station with the optimal signal quality, for example, select the base station with the highest RSRQ as the base station with the optimal signal quality, or select the base station with the highest SINR as the base station with the optimal signal quality. The preset mode may be that the base station is scored according to multiple items of data in the signal quality information, and the base station with the highest score is used as the base station with the optimal signal quality. For example, each base station may be scored according to RSRP, RSRQ, SINR, etc., to obtain a score for each base station.

In this embodiment, the unmanned aerial vehicle determines the signal quality of the base station corresponding to the designated location point according to the signal quality distribution information, so that the unmanned aerial vehicle does not need to perform base station measurement at each location point, and the time for switching the base station can be reduced, thereby improving the communication quality; when a plurality of base stations corresponding to the designated position points are provided, communication connection is established by selecting the base station with the optimal signal quality, so that the unmanned aerial vehicle can be connected to the base station with relatively good signal quality, and the communication quality is improved; the base station to be connected with the next position point and the navigation point on the preset navigation line is determined in advance, and the communication link switching between the unmanned aerial vehicle and the adjacent base station can be completed by selecting proper time and position in advance, so that the time and communication cost for switching the base station are reduced, the unmanned aerial vehicle is ensured to be always in the coverage range of the base station with optimal communication quality, and the communication quality is improved.

Fig. 8 is a flowchart of an information processing method according to a next embodiment of the present application, based on the embodiment provided in fig. 6 or fig. 7. In this embodiment, the unmanned aerial vehicle determines a route with optimal signal quality according to the signal quality distribution information. As shown in fig. 8, the method may further include:

S801, the unmanned aerial vehicle determines a plurality of routes from the starting position point to the target position point.

In this embodiment, the unmanned aerial vehicle may plan a plurality of routes from the starting location point to the target location point according to the electronic map. The starting position point and the target position point may be determined according to actual requirements, which are not limited herein. For example, in a scene of automatic return of the unmanned aerial vehicle, the starting position point may be a current position point of the unmanned aerial vehicle, and the target position point is a position point where the control terminal is located; when the user indicates that the unmanned aerial vehicle automatic navigation reaches the position point of image acquisition, the initial position point can be the current position point of the unmanned aerial vehicle, and the target position point is the position point of image acquisition indicated by the user.

S802, the unmanned aerial vehicle determines a route with optimal signal quality from a plurality of routes according to the signal quality distribution information.

In this embodiment, the unmanned aerial vehicle may determine signal quality information of each waypoint on each route according to the signal quality distribution information, and then determine a route with the optimal signal quality from the multiple routes based on the signal quality information of each waypoint on each route.

Optionally, S802 may include:

determining the signal quality of each waypoint in each route according to the signal quality distribution information;

For each route, determining the signal quality of the route according to the signal quality of each waypoint on the route;

and determining the route with the optimal signal quality according to the signal quality of each route.

In this embodiment, the unmanned aerial vehicle may search corresponding signal quality information from the signal quality distribution information according to the position information of each waypoint in each route, so as to determine the signal quality of each waypoint in each route. The signal quality of the waypoint may be determined by one item or a plurality of items of data in the signal quality information corresponding to the waypoint, and the specific determining manner is not limited herein, for example, the signal quality of the waypoint may be determined according to RSRP, RSRQ, SINR in the signal quality information corresponding to the waypoint. The signal quality of a waypoint may be represented by a score, the higher the score, the better the signal quality. For each route, the unmanned aerial vehicle can determine the signal quality of the route according to the signal quality of each waypoint on the route. For example, the signal quality of each waypoint corresponds to a score, and the result of calculation such as the sum or the mean of the scores of the waypoints on the route can be used as the signal quality of the route. The unmanned aerial vehicle compares the signal quality of each route, so that the route with the optimal communication quality in a plurality of routes is determined.

S803, the unmanned aerial vehicle controls the unmanned aerial vehicle to fly according to the route with the optimal signal quality.

In this embodiment, the unmanned aerial vehicle may determine signal quality information of each waypoint on each route according to the signal quality distribution information, and then determine a route with the optimal signal quality from the multiple routes based on the signal quality information of each waypoint on each route. The unmanned aerial vehicle controls the unmanned aerial vehicle to fly according to the route with the optimal signal quality.

According to the signal quality distribution information, the unmanned aerial vehicle determines the route with the optimal signal quality from the multiple routes, and further flies according to the route with the optimal signal quality, so that the communication quality with the base station in the flying process along the route can be improved.

On the basis of any of the embodiments shown in fig. 6-8, the method may further comprise:

determining waypoints with signal quality lower than a first threshold value on a preset route according to the signal quality distribution information;

and adjusting the preset route so as to enable the adjusted preset route to avoid the waypoints with the signal quality lower than the first threshold value.

In this embodiment, when the unmanned aerial vehicle flies along the preset route, or before flying, the signal quality of each waypoint on the preset route may be determined according to the signal quality distribution information, then the signal quality of each waypoint is compared with the first threshold value, and if there is a waypoint with the signal quality lower than the first threshold value, the preset route is adjusted, so that the adjusted preset route avoids the waypoint with the signal quality lower than the first threshold value. For example, the drone may select another newly added waypoint or waypoints within a preset range of waypoints having a signal quality below a first threshold to replace the waypoint having the signal quality below the first threshold to form an adjusted preset course. The first threshold may be set accordingly according to a determination manner of the signal quality, which is not limited herein. For example, the signal quality is determined using RSRP, then the first threshold may be-85 dBm; the signal quality is determined using scores of the plurality of data, and the first threshold is a set score threshold.

According to the embodiment, the unmanned aerial vehicle can avoid the waypoints with low signal quality on the preset route, so that the communication quality between the unmanned aerial vehicle and the base station when the unmanned aerial vehicle flies along the preset route is improved.

determining a region with signal quality lower than a second threshold according to the signal quality distribution information;

and planning a route from the starting position point to the target position point in an area outside the area with the signal quality lower than the second threshold value.

In this embodiment, the signal quality of a region may be determined according to the signal quality of each location point in the region, and the specific determining manner is not limited herein. For example, the average value of the signal quality of each position point in the area is taken as the signal quality of the area, or the minimum value of the signal quality of each position point in the area is taken as the signal quality of the area. The division of the area may be set according to actual requirements, and is not limited herein.

The unmanned aerial vehicle determines the signal quality of each position point in each area according to the signal quality distribution information, and then determines the signal quality of each area according to the signal quality of each position point in each area. The signal quality of each region is compared to a second threshold to determine regions having signal quality below the second threshold. When the unmanned aerial vehicle performs route planning, the route from the starting position point to the target position point can be planned in the area outside the area with the signal quality lower than the second threshold value.

According to the method, the area with poor signal quality is determined by the signal quality distribution information, and the air route is made to bypass the area when the unmanned aerial vehicle performs air route planning, so that the unmanned aerial vehicle is prevented from flying to the area with poor signal quality, and the communication quality between the unmanned aerial vehicle and the base station is improved.

and when the signal quality is close to the area lower than the second threshold value, sending warning information to the control terminal of the unmanned aerial vehicle.

In this embodiment, the unmanned aerial vehicle may determine, according to a preset proximity condition, an area where the quality of a proximity signal of the unmanned aerial vehicle is lower than a second threshold. The preset proximity condition is not limited herein, for example, the preset proximity condition may be that the minimum distance between the current position point of the unmanned aerial vehicle and the area is smaller than a preset distance threshold, or that the unmanned aerial vehicle enters a preset space range centered on the area, or the like.

For example, in a scenario in which the user manually controls the unmanned aerial vehicle to fly through the control terminal, the unmanned aerial vehicle may send alert information to the control terminal when determining that the proximity signal quality is below the second threshold, to prompt the user to control the unmanned aerial vehicle not to enter the region.

In this embodiment, when unmanned aerial vehicle approaches the region that signal quality is poor, through warning information suggestion user, can prevent that user control unmanned aerial vehicle from flying to the region that signal quality is poor, improve the communication quality between unmanned aerial vehicle and the basic station when flying.

and when the unmanned aerial vehicle is positioned in an area with the signal quality lower than a second threshold value, disconnecting the communication connection with the base station, and establishing the communication connection with the control terminal of the unmanned aerial vehicle.

In this embodiment, when the unmanned aerial vehicle has flown into the area where the signal quality is lower than the second threshold, the communication mode of the unmanned aerial vehicle may be switched from data transmission through the base station to data transmission through the control terminal, so as to ensure that the data transmission of the unmanned aerial vehicle is not interrupted.

and stopping transmitting the acquired image through the base station when the unmanned aerial vehicle is positioned in the area with the signal quality lower than the second threshold value, and recovering transmitting the acquired image through the base station after leaving the area with the signal quality lower than the second threshold value.

In this embodiment, when the flight task of the unmanned aerial vehicle is to collect an image, when the unmanned aerial vehicle has flown into an area with signal quality lower than a second threshold, the unmanned aerial vehicle may stop sending the collected image through the base station first, so as to prevent data transmission errors caused by poor communication quality. The drone may continue to capture images and store the images in an internal memory of the target drone. After the unmanned aerial vehicle flies away from the area, the image in the internal memory is sent to the base station, and the base station sends the image to the server or the control terminal.

In the embodiment, when the unmanned aerial vehicle is located in the area with the signal quality lower than the second threshold value, the collected image is stopped being sent through the base station, and after the unmanned aerial vehicle leaves the area, the collected image is restored to be sent through the base station, so that the image transmission error is prevented.

Fig. 9 is a flowchart of an information processing method according to another embodiment of the present application, based on any of the embodiments shown in fig. 6 to 8. As shown in fig. 9, the method includes:

s901, the unmanned aerial vehicle receives signal quality distribution information sent by a server.

S902, the unmanned aerial vehicle selects a base station for establishing communication connection according to the signal quality distribution information.

S903, the unmanned aerial vehicle determines communication parameters of the unmanned aerial vehicle and the base station for communication according to the communication strategy model.

In this embodiment, the communication policy model may be preset, or may be sent to the unmanned aerial vehicle by the server, which is not limited herein. The communication policy model may be pre-generated based on the location information and corresponding signal quality information for the drone to determine communication parameters with the base station. The communication parameters may include, but are not limited to, at least one of: beamforming parameters, channel coding strategy, channel modulation strategy, channel type, etc.

The specific form of the communication policy model is not limited herein, and for example, the communication policy model may include a deep learning-based communication parameter prediction model. The input of the communication parameter prediction model is position information, and the output is communication parameters. The communication policy model may also include a mapping table of location information and communication parameters. In the map table, each piece of position information corresponds to a respective communication parameter.

In this embodiment, the unmanned aerial vehicle determines the communication parameters for communication with the base station according to the communication policy model, so that the unmanned aerial vehicle can communicate with the base station by adopting appropriate communication parameters, and further, the communication quality between the unmanned aerial vehicle and the base station is improved.

In addition, the base station can optimize the communication link parameters in advance according to the communication quality distribution information of the flight area which the unmanned aerial vehicle needs to pass through. For example, if the unmanned aerial vehicle is known to pass through the target waypoint, the communication coverage quality of the target waypoint can be enhanced by adjusting parameters such as beam forming parameters, channel coding strategies, channel modulation strategies, channel types and the like.

For specific application scenes including power line inspection, tower inspection and the like, a base station communication strategy can be further customized according to signal quality distribution information, for example, a base station is additionally arranged in an area with poor signals, or the original base station is enabled to enhance signals and the like.

Alternatively, on the basis of the embodiment shown in fig. 9, S903 may include:

determining a target position point of unmanned aerial vehicle flight;

determining target communication parameters of the target position point according to the communication strategy model;

and controlling the unmanned aerial vehicle to communicate with the base station at the target position point by adopting the target communication parameters of the target position point.

In this embodiment, the target location point is a location point of a communication parameter to be determined, for example, the target location point may include, but is not limited to, at least one of the following: the next position point of unmanned aerial vehicle flight, the waypoint on the unmanned aerial vehicle's the preset route, etc.

When the communication strategy model is a communication parameter prediction model based on deep learning, the unmanned aerial vehicle can input the position information of the target position point into the communication parameter prediction model so as to obtain the communication parameter output by the communication parameter prediction model, namely the target communication parameter of the target position point.

When the communication strategy model is a mapping relation table of the position information and the communication parameters, the unmanned aerial vehicle can search the communication parameters corresponding to the position information of the target position point in the mapping relation table, namely, the target communication parameters of the target position point.

In this embodiment, the unmanned aerial vehicle determines the target communication parameter of the target location point according to the communication policy model, and may determine the target communication parameter in advance when the unmanned aerial vehicle does not reach the target location point, so as to adjust the communication link in advance according to the target communication parameter, thereby avoiding degradation of communication quality caused by slow adjustment speed of the communication link, and improving communication quality between the unmanned aerial vehicle and the base station.

acquiring current position information of the unmanned aerial vehicle;

inputting the current position information into a communication strategy model to obtain target communication parameters output by the communication strategy model;

And the control unmanned aerial vehicle communicates with the base station by adopting the target communication parameters.

In this embodiment, when the communication policy model is a communication parameter prediction model based on deep learning, the unmanned aerial vehicle may input current location information into the communication parameter prediction model to obtain a target communication parameter output by the communication parameter prediction model. When the communication strategy model is a mapping relation table of the position information and the communication parameters, the unmanned aerial vehicle can search the target communication parameters corresponding to the current position information in the mapping relation table.

In this embodiment, the unmanned aerial vehicle determines the target communication parameter of the current position information according to the communication policy model, and can timely adjust the communication link of the current position according to the target communication parameter, thereby improving the adjustment speed of the communication link and improving the communication quality between the unmanned aerial vehicle and the base station.

Fig. 10 is a flowchart of an information processing method according to still another embodiment of the present application. The execution subject of the method is a server. As shown in fig. 10, the method may include:

s1001, the server sends signal quality distribution information to the unmanned aerial vehicle. The signal quality distribution information is used for the unmanned aerial vehicle to select a base station for establishing communication connection.

In this embodiment, the server may send signal quality distribution information to the unmanned aerial vehicle when receiving a request from the unmanned aerial vehicle; the signal quality distribution information can be actively sent to the unmanned aerial vehicle when the unmanned aerial vehicle flies.

In this embodiment, the server sends the signal quality distribution information to the unmanned aerial vehicle, so that the unmanned aerial vehicle can select a base station to be connected with the base station in the flight according to the signal quality distribution information, and thereby the unmanned aerial vehicle can establish communication connection with the base station with relatively good communication quality in the flight, and the communication quality between the unmanned aerial vehicle and the base station in the flight is improved.

Optionally, the communication strategy model comprises a deep learning based communication parameter prediction model. Alternatively, the communication policy model includes a mapping relation table of location information and communication parameters.

In the embodiment shown in fig. 10, fig. 11 is a flowchart of an information processing method according to another embodiment of the present application. As shown in fig. 11, the method includes:

s1101, the server sends signal quality distribution information to the unmanned aerial vehicle. The signal quality distribution information is used for the unmanned aerial vehicle to select a base station for establishing communication connection.

S1102, the server sends a communication strategy model to the unmanned aerial vehicle, wherein the communication strategy model is used for the unmanned aerial vehicle to determine communication parameters for communication with the base station.

In this embodiment, the communication policy model is stored in the server. The server may send a communication policy model to the drone so that the drone determines communication parameters for communicating with the base station according to the communication policy model. The server can update the communication strategy model according to the position information acquired during the flight of the unmanned aerial vehicle and the signal quality information of the base station. The execution order of S1101 and S1102 is not limited herein, and they may be executed first and then, or may be executed in parallel.

The information processing method of the present embodiment is similar to the technical solution of the embodiment of fig. 6 and the corresponding method, and its implementation principle and technical effects are similar, and are not repeated here.

Fig. 12 is a signaling interaction diagram of an information processing method according to an embodiment of the present application. The execution main body of the signal interaction diagram is an unmanned aerial vehicle and a server. The method comprises the following steps:

and S1201, the server sends signal quality distribution information to the unmanned aerial vehicle.

S1202, the unmanned aerial vehicle selects a base station for establishing communication connection according to the signal quality distribution information.

And S1203, the server sends the communication strategy model to the unmanned aerial vehicle.

And S1204, the unmanned aerial vehicle determines communication parameters of the unmanned aerial vehicle for communication with the base station according to the communication strategy model.

The information processing method of the present embodiment is similar to the technical solutions of the embodiments of fig. 6, 10 and the corresponding methods, and its implementation principle and technical effects are similar, and are not repeated here.

Fig. 13 is a schematic structural diagram of an electronic device according to an embodiment of the present application. As shown in fig. 13, the electronic device 130 includes: a communication module 1301 and a processor 1302.

The communication module 1301 is configured to obtain signal quality information of a base station, where the signal quality information is measured based on communication connection with the base station in a flight process of the unmanned aerial vehicle;

the communication module 1301 is further configured to obtain location information of the unmanned aerial vehicle when measuring signal quality information;

a processor 1302 for determining signal quality distribution information based on the signal quality information and the location information.

Optionally, the signal quality distribution information is used for the target drone to select a base station that establishes the communication connection.

Optionally, the signal quality distribution information is used for the target unmanned aerial vehicle to select a route with optimal signal quality from a plurality of routes according to the signal quality information of each waypoint on the route.

Optionally, the signal quality distribution information is used for the target unmanned aerial vehicle to avoid the waypoint with the signal quality lower than the first threshold value on the preset route.

Optionally, the signal quality distribution information is used for avoiding an area where the signal quality is lower than a second threshold when the target unmanned aerial vehicle plans the route.

Optionally, the signal quality distribution information is used for sending warning information to the control terminal when the target unmanned aerial vehicle approaches to the area with the signal quality lower than the second threshold value.

Optionally, the signal quality distribution information is used for disconnecting the communication connection with the base station and establishing the communication connection with the control terminal of the target unmanned aerial vehicle when the target unmanned aerial vehicle is located in an area with the signal quality lower than the second threshold value.

Optionally, the signal quality distribution information is used for stopping sending the collected image through the base station when the target unmanned aerial vehicle is located in the area with the signal quality lower than the second threshold value, and resuming sending the collected image through the base station after leaving the area with the signal quality lower than the second threshold value.

Optionally, the processor 1302 is further configured to:

Optionally, the communication strategy model comprises a deep learning based communication parameter prediction model.

Optionally, the processor 1302 is configured to:

adding training samples to the training set;

Optionally, the communication policy model includes a mapping relation table of location information and communication parameters.

Optionally, the processor 1302 is configured to:

Optionally, the target drone is a drone flying within a target spatial region.

The electronic device of the present embodiment may be used to implement the technical solutions of the embodiments of fig. 2 and the corresponding methods, and the implementation principle and the technical effects are similar, and are not repeated here.

Fig. 14 is a schematic structural diagram of an unmanned aerial vehicle according to another embodiment of the present disclosure. As shown in fig. 14, the unmanned aerial vehicle 140 includes: a processor 1401 and a communication module 1402.

A processor 1401, configured to obtain signal quality information of a base station, where the signal quality information is obtained by measuring based on a communication connection with the base station during a flight of the unmanned aerial vehicle;

the processor 1401 is further configured to obtain location information of the unmanned aerial vehicle when measuring signal quality information;

A communication module 1402 for sending signal quality information and location information to a server, the signal quality information and the location information being used by the server to determine signal quality distribution information.

Optionally, the signal quality information and the location information are further used for the server to update a communication policy model for the target drone to determine communication parameters for communicating with the base station.

Optionally, the target drone is a drone flying within a target spatial region.

Optionally, the communication module 1401 is configured to:

and sending the signal quality information and the position information to a server through a base station which establishes communication connection with the unmanned aerial vehicle or a control terminal of the unmanned aerial vehicle.

The unmanned aerial vehicle of the embodiment can be used for executing the technical scheme of the embodiment of fig. 3 and the corresponding method, and the implementation principle and the technical effect are similar, and are not repeated here.

Fig. 15 is a schematic structural diagram of a server according to another embodiment of the present application. As shown in fig. 15, the server 150 includes: a communication module 1501 and a processor 1502.

The communication module 1501 is configured to receive signal quality information and position information sent by an unmanned aerial vehicle, where the signal quality information is obtained based on measurement of communication connection with a base station in a flight process of the unmanned aerial vehicle, and the position information is position information of the unmanned aerial vehicle when the signal quality information is measured;

a processor 1502 for determining signal quality distribution information based on the signal quality information and the location information.

Optionally, a processor 1502 for

Optionally, the processor 1502 is configured to:

adding training samples to the training set;

Optionally, the processor 1502 is configured to:

Optionally, the target drone is a drone flying within a target spatial region.

Optionally, the communication module 1501 is configured to:

and receiving signal quality information and position information sent by a base station which establishes communication connection with the unmanned aerial vehicle or a control terminal of the unmanned aerial vehicle.

The server of the present embodiment may be used to execute the technical solutions of the embodiments of fig. 4 and the corresponding methods, and the implementation principle and the technical effects are similar, and are not repeated here.

Fig. 16 is a schematic structural diagram of an unmanned aerial vehicle according to another embodiment of the present disclosure. As shown in fig. 16, the unmanned aerial vehicle 160 includes: a communication module 1601 and a processor 1602.

A communication module 1601, configured to receive signal quality distribution information sent by the server.

A processor 1602 is configured to select a base station for establishing a communication connection based on the signal quality distribution information.

Optionally, the processor 1602 is configured to:

Determining the signal quality of the base station corresponding to the designated position point according to the signal quality distribution information;

when the number of the base stations corresponding to the designated position points is one, the unmanned aerial vehicle selects the base station corresponding to the designated position point on the designated position point to establish communication connection;

when the number of the base stations corresponding to the designated location point is multiple, the unmanned aerial vehicle selects a base station with the optimal signal quality from the multiple base stations corresponding to the designated location point on the designated location point to establish communication connection.

Optionally, the designated location point includes at least one of:

the method comprises the steps of a current position point of the unmanned aerial vehicle, a next position point of the unmanned aerial vehicle, and a waypoint on a preset wayline of the unmanned aerial vehicle.

Optionally, the processor 1602 is further configured to:

determining a plurality of routes from the starting location point to the target location point;

determining a route with optimal signal quality from a plurality of routes according to the signal quality distribution information;

and controlling the unmanned aerial vehicle to fly according to the route with the optimal signal quality.

Optionally, the processor 1602 is configured to:

Optionally, the processor 1602 is further configured to:

and determining communication parameters of the unmanned aerial vehicle for communication with the base station according to the communication strategy model.

Optionally, the communication policy model is preset or sent by the server.

Optionally, the processor 1602 is configured to:

determining a target position point of unmanned aerial vehicle flight;

Optionally, the processor 1602 is configured to:

acquiring current position information of the unmanned aerial vehicle;

The unmanned plane of the present embodiment may be used to implement the technical schemes of the embodiments of fig. 6-9 and the corresponding methods, and its implementation principle and technical effects are similar, and will not be repeated here.

Fig. 17 is a schematic structural diagram of a server according to another embodiment of the present application. As shown in fig. 17, the server 170 includes: a communication module 1701.

A communication module 1701, configured to send signal quality distribution information to the unmanned aerial vehicle;

Optionally, the communication module 1701 is further configured to:

and sending a communication strategy model to the unmanned aerial vehicle, wherein the communication strategy model is used for the unmanned aerial vehicle to determine communication parameters for communication with the base station.

The server of the present embodiment may be used to execute the technical solutions of the embodiments of fig. 10 and the corresponding methods, and the implementation principle and the technical effects are similar, and are not repeated here.

The embodiment of the application also provides a readable storage medium, and the readable storage medium stores a computer program; the computer program, when executed, performs some or all of the steps of the information processing method as in fig. 2 and its corresponding embodiments.

The embodiment of the application also provides a readable storage medium, and the readable storage medium stores a computer program; the computer program, when executed, performs some or all of the steps of the information processing method as in fig. 3 and its corresponding embodiments.

The embodiment of the application also provides a readable storage medium, and the readable storage medium stores a computer program; the computer program, when executed, performs some or all of the steps of the information processing method as in fig. 4 and its corresponding embodiments.

The embodiment of the application also provides a readable storage medium, and the readable storage medium stores a computer program; the computer program, when executed, implements some or all of the steps of the information processing method as in fig. 6-9 and their corresponding embodiments.

The embodiment of the application also provides a readable storage medium, and the readable storage medium stores a computer program; the computer program, when executed, implements some or all of the steps of the information processing method as in fig. 10 and its corresponding embodiments.

Those of ordinary skill in the art will appreciate that: all or part of the steps for implementing the above method embodiments may be implemented by hardware associated with program instructions, where the foregoing program may be stored in a computer readable storage medium, and when executed, the program performs steps including the above method embodiments; and the aforementioned storage medium includes: read-Only Memory (ROM), random access Memory (Random Access Memory, RAM), magnetic or optical disk, and the like, which can store program codes.

Finally, it should be noted that: the above embodiments are only for illustrating the technical solution of the present application, and not for limiting the same; although the present application has been described in detail with reference to the foregoing embodiments, it should be understood by those of ordinary skill in the art that: the technical scheme described in the foregoing embodiments can be modified or some or all of the technical features thereof can be replaced by equivalents; such modifications and substitutions do not depart from the spirit of the corresponding technical solutions from the scope of the technical solutions of the embodiments of the present application.

Claims

1. An information processing method, characterized in that the method comprises:

determining signal quality distribution information according to the signal quality information and the position information;

the signal quality distribution information comprises position information of a plurality of position points and signal quality information;

the signal quality distribution information is used for a target unmanned aerial vehicle to select a base station for establishing communication connection, wherein the target unmanned aerial vehicle comprises an unmanned aerial vehicle flying in a target space region, and the target space region comprises a space region corresponding to the signal quality distribution information;

and determining the signal quality of the base station corresponding to the designated position point according to the signal quality distribution information, wherein the designated position point comprises a navigation point on a preset navigation line of the unmanned aerial vehicle.

2. The method of claim 1, wherein the signal quality distribution information is used for the target unmanned aerial vehicle to select a route with the best signal quality from a plurality of routes according to the signal quality information of each waypoint on the route.

3. The method of claim 1, wherein the signal quality distribution information is used for a target drone to evade waypoints on a preset route for which signal quality is below a first threshold.

4. The method of claim 1, wherein the signal quality distribution information is used to avoid areas where signal quality is below a second threshold when the target drone is planning a route.

5. The method according to claim 1, wherein the signal quality distribution information is used for sending warning information to the control terminal when the target unmanned aerial vehicle approaches an area with signal quality lower than a second threshold.

6. The method according to claim 1, characterized in that the signal quality distribution information is used for disconnecting the communication connection with the base station and establishing the communication connection with the control terminal of the target drone when the target drone is located in an area where the signal quality is below a second threshold.

7. The method of claim 1, wherein the signal quality distribution information is used to stop sending the collected image by the base station when the target drone is located in an area where the signal quality is below a second threshold, and to resume sending the collected image by the base station after leaving the area where the signal quality is below the second threshold.

8. The method according to claim 1, wherein the method further comprises:

9. The method of claim 8, wherein the communication strategy model comprises a deep learning based communication parameter prediction model.

10. The method of claim 9, wherein updating a communication policy model based on the signal quality information and the location information comprises:

adding the training samples to a training set;

11. The method of claim 8, wherein the communication policy model includes a mapping table of location information and communication parameters.

12. The method of claim 11, wherein updating a communication policy model based on the signal quality information and the location information comprises:

And updating the position information and the communication parameters corresponding to the position information into the mapping relation table.

13. The method of any one of claims 1-12, wherein the target drone is a drone flying within the target space region.

14. An information processing method, wherein the method is applied to a unmanned aerial vehicle, and the method comprises:

transmitting the signal quality information and the position information to a server, wherein the signal quality information and the position information are used for determining signal quality distribution information by the server;

15. The method of claim 14, wherein the signal quality distribution information is used for the target unmanned aerial vehicle to select a route with the best signal quality from a plurality of routes according to the signal quality information of each waypoint on the route.

16. The method of claim 14, wherein the signal quality distribution information is used for a target drone to evade waypoints on a preset route for which signal quality is below a first threshold.

17. The method of claim 14, wherein the signal quality distribution information is used to avoid areas where signal quality is below a second threshold when the target drone is planning the route.

18. The method of claim 14, wherein the signal quality distribution information is used for sending alert information to the control terminal when the target drone is near an area where signal quality is below a second threshold.

19. The method according to claim 14, wherein the signal quality distribution information is used to disconnect the communication connection with the base station and to establish the communication connection with the control terminal of the target drone when the target drone is located in an area where the signal quality is below a second threshold.

20. The method of claim 14, wherein the signal quality distribution information is used to stop sending the collected image by the base station when the target drone is located in an area having a signal quality below a second threshold, and to resume sending the collected image by the base station after leaving the area having a signal quality below the second threshold.

21. The method of claim 14, wherein the signal quality information and the location information are further used by the server to update a communication policy model for the target drone to determine communication parameters for communicating with the base station.

22. The method of claim 21, wherein the communication strategy model comprises a deep learning based communication parameter prediction model.

23. The method of claim 21, wherein the communication policy model includes a mapping table of location information and communication parameters.

24. The method of any one of claims 14-23, wherein the target drone is a drone flying within the target space region.

25. The method according to any of claims 14-23, wherein transmitting the signal quality information and the location information to a server comprises:

And sending the signal quality information and the position information to the server through a base station which establishes communication connection with the unmanned aerial vehicle or a control terminal of the unmanned aerial vehicle.

26. An information processing method, wherein the method is applied to a server, the method comprising:

receiving signal quality information and position information sent by an unmanned aerial vehicle, wherein the signal quality information is measured based on communication connection with a base station in the flight process of the unmanned aerial vehicle, and the position information is the position information of the unmanned aerial vehicle when the signal quality information is measured;

27. The method of claim 26, wherein the signal quality distribution information is used for the target drone to select a route with the best signal quality from among the plurality of routes based on the signal quality information for each waypoint on the route.

28. The method of claim 26, wherein the signal quality distribution information is used for a target drone to evade waypoints on a preset route for which signal quality is below a first threshold.

29. The method of claim 26, wherein the signal quality distribution information is used to avoid areas where signal quality is below a second threshold when the target drone is planning the route.

30. The method of claim 26, wherein the signal quality distribution information is used for sending alert information to the control terminal when the target drone is near an area where signal quality is below a second threshold.

31. The method according to claim 26, wherein the signal quality distribution information is used to disconnect the communication connection with the base station and establish the communication connection with the control terminal of the target drone when the target drone is located in an area where the signal quality is below a second threshold.

32. The method of claim 26, wherein the signal quality distribution information is used to stop transmitting the collected image by the base station when the target drone is located in an area having a signal quality below a second threshold, and to resume transmitting the collected image by the base station after leaving the area having a signal quality below the second threshold.

33. The method of claim 26, wherein the method further comprises:

34. The method of claim 33, wherein the communication strategy model comprises a deep learning based communication parameter prediction model.

35. The method of claim 34, wherein updating a communication policy model based on the signal quality information and the location information comprises:

adding the training samples to a training set;

36. The method of claim 33, wherein the communication policy model includes a mapping table of location information and communication parameters.

37. The method of claim 36, wherein updating a communication policy model based on the signal quality information and the location information comprises:

38. The method of any one of claims 26-37, wherein the target drone is a drone flying within the target space region.

39. The method according to any of claims 26-37, wherein receiving signal quality information and location information transmitted by the drone, comprises:

and receiving the signal quality information and the position information sent by a base station which establishes communication connection with the unmanned aerial vehicle or a control terminal of the unmanned aerial vehicle.

40. An information processing method, characterized in that it is applied to an unmanned aerial vehicle, the method comprising:

receiving signal quality distribution information sent by a server;

Selecting a base station for establishing communication connection according to the signal quality distribution information;

41. The method of claim 40, wherein selecting a base station for establishing a communication connection based on the signal quality distribution information comprises:

when the number of the base stations corresponding to the appointed position point is one, the unmanned aerial vehicle selects the base station corresponding to the appointed position point to establish communication connection on the appointed position point;

when the number of the base stations corresponding to the designated location point is multiple, the unmanned aerial vehicle selects a base station with the optimal signal quality from the plurality of base stations corresponding to the designated location point to establish communication connection on the designated location point.

42. The method of claim 40, further comprising:

determining a plurality of routes from the starting position point to the target position point;

determining a route with optimal signal quality from the multiple routes according to the signal quality distribution information;

43. The method of claim 42, wherein determining a route of optimal signal quality from the plurality of routes based on the signal quality distribution information comprises:

44. The method of claim 40, further comprising:

and adjusting the preset route so that the adjusted preset route avoids the waypoints with the signal quality lower than a first threshold value.

45. The method of claim 40, further comprising:

and planning a route from the starting position point to the target position point in a region outside the region with the signal quality lower than the second threshold value.

46. The method of claim 40, further comprising:

and when the signal quality is close to the area with the signal quality lower than the second threshold value, sending warning information to the control terminal of the unmanned aerial vehicle.

47. The method of claim 40, further comprising:

48. The method of claim 40, further comprising:

And stopping sending the collected image through the base station when the unmanned aerial vehicle is positioned in the area with the signal quality lower than the second threshold value, and recovering sending the collected image through the base station after leaving the area with the signal quality lower than the second threshold value.

49. The method of any one of claims 40-48, further comprising:

50. The method of claim 49, wherein the communication policy model is preset or transmitted by the server.

51. The method of claim 49, wherein the communication strategy model comprises a deep learning based communication parameter prediction model.

52. The method of claim 49, wherein the communication policy model includes a mapping table of location information and communication parameters.

53. The method of claim 49, wherein determining the communication policy of the drone according to the communication policy model comprises:

determining a target position point of the unmanned aerial vehicle flight;

determining target communication parameters of the target position point according to a communication strategy model;

And controlling the unmanned aerial vehicle to communicate with a base station at the target position point by adopting target communication parameters of the target position point.

54. The method of claim 49, further comprising:

acquiring current position information of the unmanned aerial vehicle;

inputting the current position information into the communication strategy model to obtain target communication parameters output by the communication strategy model;

and controlling the unmanned aerial vehicle to communicate with a base station by adopting the target communication parameters.

55. An information processing method, characterized by being applied to a server, the method comprising:

the signal quality distribution information is used for the unmanned aerial vehicle to select a base station for establishing communication connection;

56. The method of claim 55, further comprising:

and sending a communication strategy model to the unmanned aerial vehicle, wherein the communication strategy model is used for the unmanned aerial vehicle to determine communication parameters for communication with a base station.

57. The method of claim 56, wherein said communication strategy model comprises a deep learning based communication parameter prediction model.

58. The method of claim 56, wherein said communication policy model comprises a mapping table of location information and communication parameters.

59. An electronic device, comprising:

a processor for determining signal quality distribution information from the signal quality information and the location information;

60. The electronic device of claim 59, wherein the signal quality distribution information is used for the target drone to select a route with the best signal quality from among the plurality of routes based on the signal quality information for each waypoint on the route.

61. The electronic device of claim 59, wherein the signal quality distribution information is used to target unmanned aerial vehicle avoid waypoints on a preset route for which signal quality is below a first threshold.

62. The electronic device of claim 59, wherein the signal quality distribution information is for a target drone to avoid areas where signal quality is below a second threshold when planning a route.

63. The electronic device of claim 59, wherein the signal quality distribution information is used to send alert information to the control terminal when the target drone is near an area where signal quality is below a second threshold.

64. The electronic device of claim 59, wherein the signal quality distribution information is used to disconnect a communication connection with a base station and establish a communication connection with a control terminal of the target drone when the target drone is located in an area where signal quality is below a second threshold.

65. The electronic device of claim 59, wherein the signal quality distribution information is used to stop sending the collected image through the base station when the target drone is located in an area with signal quality below the second threshold, and to resume sending the collected image through the base station after leaving the area with signal quality below the second threshold.

66. The electronic device of claim 59, wherein the processor is further configured to:

67. The electronic device of claim 66, wherein the communication policy model comprises a deep learning based communication parameter prediction model.

68. The electronic device of claim 67, wherein the processor is configured to:

adding the training samples to a training set;

69. The electronic device of claim 66, wherein the communication policy model includes a mapping table of location information and communication parameters.

70. The electronic device of claim 69, wherein the processor is configured to:

71. The electronic device of any one of claims 59-70, wherein the target drone is a drone flying within the target spatial region.

72. An unmanned aerial vehicle, comprising:

the communication module is used for sending the signal quality information and the position information to a server, wherein the signal quality information and the position information are used for determining signal quality distribution information by the server;

73. The unmanned aerial vehicle of claim 72, wherein the signal quality distribution information is used by the target unmanned aerial vehicle to select a route with the best signal quality from among a plurality of routes based on the signal quality information for each waypoint on the route.

74. The unmanned aerial vehicle of claim 72, wherein the signal quality distribution information is used for a target unmanned aerial vehicle to evade waypoints on a preset route for which signal quality is below a first threshold.

75. The drone of claim 72, wherein the signal quality distribution information is used to avoid areas where signal quality is below a second threshold when the target drone is planning a route.

76. The unmanned aerial vehicle of claim 72, wherein the signal quality distribution information is used to send alert information to the control terminal when the target unmanned aerial vehicle is approaching an area where signal quality is below a second threshold.

77. The drone of claim 72, wherein the signal quality distribution information is used to disconnect a communication connection with a base station and establish a communication connection with a control terminal of the target drone when the target drone is located in an area where signal quality is below a second threshold.

78. The drone of claim 72, wherein the signal quality distribution information is used to stop sending the captured image through the base station when the target drone is located in an area with a signal quality below a second threshold, and to resume sending the captured image through the base station after leaving the area with the signal quality below the second threshold.

79. The drone of claim 72, wherein the signal quality information and the location information are further used by the server to update a communication policy model that is used by a target drone to determine communication parameters for communicating with a base station.

80. The drone of claim 79, wherein the communication strategy model includes a deep learning based communication parameter prediction model.

81. The drone of claim 79, wherein the communication policy model includes a mapping table of location information and communication parameters.

82. The drone of any one of claims 72-81, wherein the target drone is a drone flying within the target spatial region.

83. The unmanned aerial vehicle of any of claims 72-81, wherein the communication module is configured to:

84. A server, comprising:

the communication module is used for receiving signal quality information and position information sent by the unmanned aerial vehicle, wherein the signal quality information is obtained by measuring the signal quality information based on communication connection with a base station in the flight process of the unmanned aerial vehicle, and the position information is the position information of the unmanned aerial vehicle when the signal quality information is measured;

A processor for determining signal quality distribution information based on the signal quality information and the location information;

85. The server according to claim 84, wherein the signal quality distribution information is used by the target drone to select a route with the best signal quality from among the plurality of routes based on the signal quality information for each waypoint on the route.

86. The server of claim 84, wherein the signal quality distribution information is used to target unmanned aerial vehicle avoid waypoints on a preset route for which signal quality is below a first threshold.

87. The server of claim 84, wherein the signal quality distribution information is used to avoid areas where signal quality is below a second threshold when the target drone is planning the route.

88. The server of claim 84, wherein the signal quality distribution information is used to send alert information to the control terminal when the target drone is near an area where signal quality is below a second threshold.

89. The server of claim 84, wherein the signal quality distribution information is used to disconnect the communication connection with the base station and establish the communication connection with the control terminal of the target drone when the target drone is located in an area where signal quality is below a second threshold.

90. The server of claim 84, wherein the signal quality distribution information is used to stop transmitting the collected image by the base station when the target drone is located in an area having a signal quality below a second threshold, and to resume transmitting the collected image by the base station after leaving the area having a signal quality below the second threshold.

91. The server according to claim 84, wherein the processor is configured to

92. The server of claim 91, wherein said communication strategy model comprises a deep learning based communication parameter prediction model.

93. The server of claim 92, wherein the processor is configured to:

adding the training samples to a training set;

94. The server of claim 91, wherein said communication policy model includes a mapping table of location information and communication parameters.

95. The server of claim 94, wherein the processor is configured to:

96. The server according to any one of claims 84-95, wherein the target drone is a drone flying within the target spatial region.

97. The server according to any of the claims 84-95, wherein the communication module is configured to:

98. An unmanned aerial vehicle, comprising:

a processor, configured to select a base station for establishing a communication connection according to the signal quality distribution information;

99. The drone of claim 98, wherein the processor is configured to:

100. The drone of claim 98, wherein the processor is further configured to:

101. The unmanned aerial vehicle of claim 100, wherein the processor is configured to:

102. The drone of claim 98, wherein the processor is further configured to:

103. The drone of claim 98, wherein the processor is further configured to:

104. The drone of claim 98, wherein the processor is further configured to:

105. The drone of claim 98, wherein the processor is further configured to:

106. The drone of claim 98, wherein the processor is further configured to:

107. The drone of any one of claims 98-106, wherein the processor is further configured to:

108. The drone of claim 107, wherein the communication policy model is preset or sent by the server.

109. The drone of claim 107, wherein the communication policy model includes a deep learning based communication parameter prediction model.

110. The drone of claim 107, wherein the communication policy model includes a mapping table of location information and communication parameters.

111. The unmanned aerial vehicle of claim 107, wherein the processor is configured to:

determining a target position point of the unmanned aerial vehicle flight;

112. The unmanned aerial vehicle of claim 107, wherein the processor is configured to:

acquiring current position information of the unmanned aerial vehicle;

113. A server, comprising:

114. The server of claim 113, wherein the communication module is further configured to:

115. The server of claim 113 or 114, wherein the communication strategy model comprises a deep learning based communication parameter prediction model.

116. The server according to claim 113 or 114, wherein the communication policy model comprises a mapping table of location information and communication parameters.