Signal transmission method, device and equipment, storage medium and unmanned aerial vehicle take-off and landing platform

Abstract

The invention discloses a signal transmission method, device and equipment, a storage medium and an unmanned aerial vehicle take-off and landing platform. The method comprises the following steps: in response to a received communication signal, determining an unmanned aerial vehicle corresponding to the communication signal, and obtaining unmanned aerial vehicle pose information of the unmanned aerial vehicle; inputting the unmanned aerial vehicle pose information into an unmanned aerial vehicle position prediction model, and predicting the position of the unmanned aerial vehicle through the unmanned aerial vehicle position prediction model to obtain unmanned aerial vehicle predicted position information; determining a phase and an amplitude corresponding to the communication signal according to the predicted position information of the unmanned aerial vehicle; according to the phase and amplitude corresponding to the communication signal, adjusting a signal reflection parameter of the unmanned aerial vehicle take-off and landing platform; and reflecting the communication signal through the unmanned aerial vehicle take-off and landing platform after the signal reflection parameter is adjusted. According to the embodiment of the invention, stable communication of the unmanned aerial vehicle in the take-off and landing process can be realized.

Description

Technical Field

[0001] This application belongs to the field of communication technologies, and particularly relates to a signal transmission method, apparatus, device, storage medium, and UAV takeoff and landing platform. Background Art

[0002] With the rapid development of UAV technologies, UAVs are increasingly widely used in fields such as logistics, inspection, agriculture, and emergency rescue. UAVs have characteristics such as beyond-line-of-sight control, real-time precise control, and high-bandwidth data transmission, and can expand and innovate application scenarios, and may become the core force in the development of the low-altitude economy.

[0003] During the takeoff and landing phases, UAVs have relatively high requirements for the coverage quality of communication networks, and the stability of communication is directly related to the flight safety of UAVs. However, due to problems such as complex low-altitude environments and limited vertical beam widths of base stations, the communication links of UAVs in low-altitude environments are unstable, resulting in unstable communication signals of UAVs and causing accidents.

[0004] Therefore, how to achieve stable communication of UAVs during takeoff and landing is a technical problem that needs to be urgently solved by those skilled in the art. Summary of the Invention

[0005] Embodiments of this application provide a signal transmission method, apparatus, device, storage medium, and UAV takeoff and landing platform, which can achieve stable communication of UAVs during takeoff and landing.

[0006] In a first aspect, embodiments of this application provide a signal transmission method, which is applied to a signal reflection component of a UAV takeoff and landing platform. The method includes: in response to receiving a communication signal, determining the UAV corresponding to the communication signal, and obtaining the UAV pose information of the UAV; inputting the UAV pose information into a UAV position prediction model, and predicting the position of the UAV through the UAV position prediction model to obtain UAV predicted position information; determining the phase and amplitude corresponding to the communication signal according to the UAV predicted position information; adjusting the signal reflection parameters of the UAV takeoff and landing platform according to the phase and amplitude corresponding to the communication signal; and reflecting the communication signal through the UAV takeoff and landing platform with adjusted signal reflection parameters.

[0007] In an implementation, determining the phase and amplitude corresponding to the communication signal according to the UAV predicted position information includes: determining the platform position information of the UAV takeoff and landing platform; determining the pitch angle and azimuth angle corresponding to the communication signal according to the UAV predicted position information and the platform position information; and determining the phase and amplitude corresponding to the communication signal according to the pitch angle and azimuth angle corresponding to the communication signal.

[0008] In one implementation, after adjusting the signal reflection parameters of the UAV takeoff and landing platform according to the phase and amplitude of the communication signal, the method further includes: predicting a predicted signal strength index of the UAV when receiving the communication signal according to the phase and amplitude of the communication signal; determining an initial phase update gradient according to the predicted signal strength index and the phase; determining an initial amplitude update gradient according to the predicted signal strength index and the amplitude; based on the initial phase update gradient and the initial amplitude update gradient, with the goal of maximizing the predicted signal strength index, updating the phase and amplitude of the communication signal multiple times to determine the updated phase and amplitude; adjusting the signal reflection parameters of the UAV takeoff and landing platform according to the updated phase and amplitude.

[0009] In one implementation, based on the initial phase update gradient and the initial amplitude update gradient, with the goal of maximizing the predicted signal strength index, updating the phase and amplitude of the communication signal multiple times to determine the updated phase and amplitude includes: based on the initial phase update gradient, with the goal of maximizing the predicted signal strength index, updating the phase along the positive gradient direction of the predicted signal strength index to obtain the updated phase; based on the initial amplitude update gradient, with the goal of maximizing the predicted signal strength index, updating the amplitude along the positive gradient direction of the predicted signal strength index to obtain the updated amplitude.

[0010] In one implementation, the UAV position prediction model includes a UAV state equation and a UAV observation equation; inputting the UAV pose information into the UAV position prediction model, and predicting the position of the UAV through the UAV position prediction model to obtain the UAV predicted position information, including: inputting the UAV pose information into the UAV state equation and the UAV observation equation respectively to obtain the UAV predicted state corresponding to the UAV state equation and the UAV observation state corresponding to the UAV observation equation; determining covariance information according to the UAV predicted state and the UAV observation state; constructing gain information according to the covariance information corresponding to the UAV state equation and the UAV observation state; determining the UAV predicted position information according to the covariance information, the gain information and the UAV predicted state.

[0011] In one implementation, it further includes: obtaining the communication signal strength index fed back by the UAV when receiving the communication signal; in the case where it is determined that the communication signal strength index does not meet the preset signal strength condition, updating the phase and amplitude of the communication signal according to the predicted signal strength index, where the predicted signal strength index is the signal strength index determined according to the phase and amplitude of the communication signal; adjusting the signal reflection parameters of the UAV takeoff and landing platform according to the updated phase and amplitude; reflecting the communication signal through the UAV takeoff and landing platform with the adjusted signal reflection parameters.

[0012] Second aspect, embodiments of the present application provide an unmanned aerial vehicle (UAV) takeoff and landing platform, which includes: a signal reflection component for implementing the signal transmission method in the first aspect or any one of the embodiments of the first aspect; and a support component for carrying the signal reflection component and the UAV, wherein the signal reflection component is attached to the support component.

[0013] In one embodiment, the signal reflection component includes: a plurality of reflection units arranged in an array for receiving communication signals; and a control unit electrically connected to the plurality of reflection units for determining the signal reflection parameters of the reflection units so that the reflection units reflect the communication signals after being adjusted according to the signal reflection parameters.

[0014] In one embodiment, the control unit includes: a signal input sub-unit electrically connected to the reflection unit;

[0015] a data processing sub-unit connected to the signal input sub-unit; a signal output sub-unit connected to the data processing sub-unit and the reflection unit; and a storage sub-unit connected to the data processing sub-unit for storing data.

[0016] In one embodiment, the control component further includes: a power amplifier for amplifying the power of the communication signal.

[0017] In one embodiment, it further includes: an isolation component sequentially deployed with the signal reflection component in the working direction of the UAV takeoff and landing platform for isolating the communication signal.

[0018] In one embodiment, the signal reflection component is attached to the working plane of the UAV takeoff and landing platform, and the working plane includes at least the plane parallel to the ground in the UAV takeoff and landing platform.

[0019] Third aspect, embodiments of the present application provide a signal transmission method device, which includes:

[0020] An acquisition module for determining the UAV corresponding to the communication signal and acquiring the UAV pose information of the UAV in response to receiving the communication signal;

[0021] A first determination module for inputting the UAV pose information into a UAV position prediction model to predict the position of the UAV through the UAV position prediction model and obtaining the UAV predicted position information;

[0022] A second determination module for determining the phase and amplitude corresponding to the communication signal according to the UAV predicted position information;

[0023] An adjustment module for adjusting the signal reflection parameters of the UAV takeoff and landing platform according to the phase and amplitude corresponding to the communication signal;

[0024] A reflection module is used for a UAV takeoff and landing platform with adjusted signal reflection parameters to reflect communication signals.

[0025] In a fourth aspect, an embodiment of the present application provides a signal transmission method device, which includes: a processor and a memory storing computer program instructions; when the processor executes the computer program instructions, it implements the signal transmission method as in the first aspect or any one of the implementation manners of the first aspect.

[0026] In a fifth aspect, a computer-readable storage medium stores computer program instructions, and when the computer program instructions are executed by a processor, they implement the signal transmission method as in the first aspect or any one of the implementation manners of the first aspect.

[0027] In a fifth aspect, an embodiment of the present application provides a computer program product. When the instructions in the computer program product are executed by a processor of an electronic device, the electronic device is enabled to execute the signal transmission method as in the first aspect or any one of the implementation manners of the first aspect.

[0028] For the signal transmission method, device, equipment, storage medium and UAV takeoff and landing platform in the embodiments of the present application, the UAV takeoff and landing platform can receive communication signals and directly reflect the communication signals to the UAV, so as to establish a continuous and stable communication link between the UAV and the UAV takeoff and landing platform, avoid signal interruption problems during the takeoff and landing of the UAV, and improve the safety during the takeoff and landing of the UAV. Further, in the process of reflecting the communication signal to the UAV, by predicting the UAV predicted position information at a future moment and using the UAV predicted position information as the target direction, the communication signal is reflected, so as to flexibly adjust the communication signal and enable the communication signal to accurately cover the UAV. Therefore, the communication signal reflected by the UAV takeoff and landing platform can be applicable to the dynamic scenario of the fast movement of the UAV and provide communication support for the whole process of the UAV takeoff and landing. BRIEF DESCRIPTION OF THE DRAWINGS

[0029] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the following will briefly introduce the drawings required to be used in the embodiments of the present application. For those of ordinary skill in the art, other drawings can also be obtained according to these drawings without creative efforts.

[0030] Figure 1 It shows a schematic diagram of low-altitude area network coverage provided by an embodiment of the present application;

[0031] Figure 2 It shows a schematic diagram of the architecture of a UAV takeoff and landing platform provided by an embodiment of the present application;

[0032] Figure 3Shows a schematic structural diagram of a signal reflection component provided by an embodiment of the present application;

[0033] Figure 4 Shows a schematic structural diagram of a signal reflection component provided by an embodiment of the present application;

[0034] Figure 5 Shows a schematic structural diagram of a control unit provided by an embodiment of the present application;

[0035] Figure 6 Shows a schematic structural diagram of a control unit provided by an embodiment of the present application;

[0036] Figure 7 Is a schematic flow diagram of a signal transmission method provided by an embodiment of the present application;

[0037] Figure 8 Is a schematic flow diagram of determining the phase and amplitude corresponding to a communication signal provided by an embodiment of the present application;

[0038] Figure 9 Is a schematic flow diagram of a signal transmission method provided by an embodiment of the present application;

[0039] Figure 10 Is a schematic flow diagram of determining the predicted position information of a drone provided by an embodiment of the present application;

[0040] Figure 11 Is a schematic flow diagram of a signal transmission method provided by an embodiment of the present application;

[0041] Figure 12 Is a schematic flow diagram of a signal transmission method provided by an embodiment of the present application;

[0042] Figure 13 Is a schematic deployment scenario diagram of a drone with a drone takeoff and landing platform provided by an embodiment of the present application;

[0043] Figure 14 Is a schematic structural diagram of a signal transmission device provided by another embodiment of the present application;

[0044] Figure 15 Is a schematic structural diagram of a signal transmission device provided by yet another embodiment of the present application.

[0045] Explanation of reference numerals:

[0046] 100, UAV takeoff and landing platform; 110, signal reflection component; 120, support component; 111, reflection unit; 112, control unit; 113, isolation component; 1121, signal input sub-unit; 1122, data processing sub-unit; 1123, signal output sub-unit; 1124, storage sub-unit; 121, base; 122, cover plate; 601, power interface; 602, network cable interface. Detailed implementation manners

[0047] The features and exemplary embodiments of various aspects of the present application will be described in detail below. To make the objectives, technical solutions and advantages of the present application clearer and more understandable, the present application will be further described in detail below in conjunction with the accompanying drawings and specific embodiments. It should be understood that the specific embodiments described herein are only intended to explain the present application, rather than limiting the present application. For those skilled in the art, the present application can be implemented without some of these specific details. The following description of the embodiments is only intended to provide a better understanding of the present application by showing examples of the present application.

[0048] It should be noted that, in this document, relational terms such as first and second are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variant thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements not only includes those elements, but also includes other elements not expressly listed, or also includes elements inherent to such process, method, article or device. Without further limitation, the elements defined by the statement "including..." do not exclude the existence of additional identical elements in the process, method, article or device including the elements.

[0049] With the rapid development of UAV technology, the advantageous features of UAVs such as beyond visual line of sight control, real-time precise manipulation, and high-bandwidth data transmission have become increasingly prominent. These features can expand and innovate the application scenarios of UAVs, making UAVs the core force in the development of the low-altitude economy.

[0050] During the takeoff and landing phases, drones have high requirements for the coverage quality of communication networks, and the stability of their communication is directly related to the flight safety of drones. Among them, during the communication process of drones, a base station can be used as a signal source to send communication signals to the drones, enabling the drones to perform corresponding operations. However, due to the complex low-altitude environment, for example, there are a large number of obstacles such as buildings and trees in the low-altitude environment, which leads to signal attenuation and multipath interference of communication signals, affecting communication quality. Moreover, due to the limited vertical beamwidth of the base station, the signal coverage connection in the low-altitude area is poor, and signal coverage area stratification is likely to occur, which further leads to signal blind spots during the takeoff and landing of drones, resulting in communication interruption problems. In one example, Figure 1 shows a schematic diagram of network coverage in a low-altitude area provided by an embodiment of the present application. Different base stations have different vertical beamwidths. For example, as Figure 1 shown, limited by the vertical beamwidths of different base stations, the signal coverage range of base station 1 can be the range within the first distance from the drone takeoff and landing point, the signal coverage range of base station 2 can be the range between the second distance and the third distance from the drone takeoff and landing point, and the signal coverage range of base station 3 can be the range greater than the fourth distance from the drone takeoff and landing point. Among them, the first distance, the second distance, the third distance, and the fourth distance increase one by one and are not continuous. In view of this, during the ascent or descent of the drone, when ascending between the first distance and the second distance, there is no corresponding base station to achieve communication, resulting in signal interruption of the drone, unstable communication signals, and causing drone accidents.

[0051] In the related art, it is possible to rely on the base station to add relay devices for drones to supplement the signal coverage range. However, since adding relay devices not only requires high investment but also has a cumbersome deployment process, and moreover, the added relay devices are relatively fixed and are not conducive to being applicable to the dynamic scenarios of fast drones. Therefore, how to achieve signal transmission of drones in a low-cost and easy-to-construct manner is a technical problem that those skilled in the art urgently need to solve.

[0052] To solve the problems of the prior art, the embodiments of the present application provide a signal transmission method, device, equipment, storage medium, and drone takeoff and landing platform. First, the drone takeoff and landing platform provided by the embodiments of the present application will be introduced below.

[0053] Figure 2 shows a schematic diagram of the architecture of a drone takeoff and landing platform provided by an embodiment of the present application. As Figure 2 shown, the drone takeoff and landing platform 100 includes: a signal reflection component 110; and a support component 120.

[0054] Among them, the support component 120 can be used to carry the signal reflection component 110 and the drone. And the signal reflection component 110 is attached to the support component 120.

[0055] In some alternative embodiments, the support structure may include a base 121 and a cover plate 122. Among them, the signal reflection component 110 may be located between the base 121 and the cover plate 122, and the base 121 and the cover plate 122 may be connected by a connecting device, such as a screw. It can be understood that by deploying the signal reflection component 110 between the base 121 and the cover plate 122 and fixing the whole through the connecting device, the overall load-bearing of the platform can be effectively shared.

[0056] Exemplarily, the support component 120 needs to meet the mechanical performance and electromagnetic environment reconstruction performance of the UAV takeoff and landing platform 100.

[0057] In one example, the shape of the support structure may be a structure of any shape that meets the actual application requirements. For example, the support structure may be in the shape of a cuboid, a cube, a cylinder, etc.

[0058] In another example, the material of the support structure can be selected as a material with high strength and light weight to meet the requirements of weighing and impact resistance. For example, to meet the bearing requirements of light and medium-sized UAVs, the load-bearing capacity per square meter is at least 10 kilograms (kg) to 13 kg.

[0059] In another example, a corresponding hollow structure may be provided in the support structure to reduce the weight of the UAV takeoff and landing platform 100.

[0060] In yet another example, the support structure needs to have certain waterproof performance and high-temperature resistance performance. For example, the waterproof level of the support structure should at least reach the protection level (Ingress Protection, IP). For example, it needs to reach IP67, which can effectively resist the invasion of rain and moisture, and can withstand a high temperature of at least 150 degrees Celsius without deformation, providing a safe bearing for the UAV support platform and having the characteristics of waterproof and high-temperature resistance.

[0061] Exemplarily, the signal reflection component 110 can be used to execute a signal transmission method. Among them, the signal transmission method at least includes the following steps: in response to receiving a communication signal, determining the UAV corresponding to the communication signal and obtaining the UAV pose information corresponding to the UAV; inputting the UAV pose information into a UAV position prediction model, predicting the position of the UAV through the UAV position prediction model to obtain UAV predicted position information; determining the phase and amplitude corresponding to the communication signal according to the UAV predicted position information; adjusting the signal reflection parameters of the UAV takeoff and landing platform 100 according to the phase and amplitude corresponding to the communication signal; reflecting the communication signal through the UAV takeoff and landing platform 100 with adjusted signal reflection parameters.

[0062] In the embodiment of the present application, by adding a signal reflection component 110 in the drone landing platform 100, the communication information is directly reflected to the drone through the signal reflection component 110, so that the drone can continuously and stably receive the signal sent by the signal source during the take-off and landing stage, and ensure the safety of the drone during the take-off and landing stage. In addition, by adding a signal reflection component 110 in the drone landing platform 100, the signal direction of the communication signal can be changed, so that the communication signal is directly reflected from the drone landing platform 100 to the drone, and the stability of the communication signal transmission process is enhanced, and the drone can also have the physical bearing function of the drone. That is, multi-functional integration is achieved, resource utilization efficiency is improved, and costs are reduced. In addition, since the signal reflection component 110 is set in the drone landing platform 100, as the drone landing platform 100 moves, the communication stability is enhanced in different scenes, so that the communication link of the drone is quickly built, so that the drone platform with the added signal reflection component 110 is more suitable for the dynamic scene of the drone.

[0063] In order to determine the reflection direction of the communication signal, as another implementation method of the present application, the present application also provides another implementation method of the UAV take-off and landing platform 100, please refer to the following embodiments for details.

[0064] Figure 3 FIG. 1 is a schematic diagram showing the architecture of a signal reflection component 110 provided by an embodiment of the present application. Figure 3 As shown, the signal reflection component 110 includes: a plurality of reflection units 111 arranged in an array; and a control unit 112 , and the control unit 112 is electrically connected to the plurality of reflection units 111 .

[0065] Exemplarily, the reflection unit 111 may be used to receive a communication signal.

[0066] The reflection unit 111 may be composed of a reconfigurable intelligent surface (RIS), wherein the RIS is a two-dimensional planar array composed of a large number of metamaterial units, each of which can independently adjust the phase, amplitude or polarization characteristics of the electromagnetic wave.

[0067] Exemplarily, the control unit 112 may be configured to determine a signal reflection parameter of the reflection unit 111 , so that the reflection unit 111 reflects the communication signal after being adjusted according to the signal reflection parameter.

[0068] By adjusting the signal reflection parameters of the signal reflection unit 111, at least one of the phase, amplitude, and polarization characteristics of the communication signal can be adjusted. In one example, the control unit 112 can adjust the phase and / or amplitude of the reflected signal by adjusting the values of the capacitance, resistance, and inductance of each reflection unit 111, thereby adjusting the direction of the reflected signal.

[0069] The control unit 112 can determine the corresponding phase and / or amplitude through the above signal transmission method, and then determine the corresponding signal reflection parameters according to the determined phase and / or amplitude, and adjust each reflection unit 111 according to the signal reflection parameters to adjust the direction of the communication signal.

[0070] It can be understood that each reflection unit 111 can independently adjust the phase delay of the reflected wave. When the incident signal, that is, the communication signal reaches the RIS surface, the waves reflected by each reflection unit 111 will produce specific phase offsets. By determining and designing these phase differences, the RIS can make the reflected waves undergo constructive interference in the target direction and destructive interference in other directions, thereby reflecting the communication signal. Moreover, each reflection unit 111 can also adjust the amplitude of the reflected wave (i.e., the magnitude of the reflection coefficient), which affects the contribution weight of each reflection unit 111 to the overall communication signal. Among them, by increasing the amplitude weight of the target direction unit, more energy can be concentrated in the target direction to enhance the intensity of the target direction. And by reducing the amplitude of the non-target direction unit, signal leakage can be reduced to suppress the side lobe interference of the communication signal. It can be understood that the reflection unit 111 does not actively transmit signals or amplify power, but only redistributes the energy distribution of the incident signal. And the signal amplitude adjustment is not to actively amplify the signal power, but to optimize the signal distribution in space by controlling the energy ratio reflected by each unit (such as the reflectivity can be adjusted from 0 to 1). For example, if the amplitude of the reflection unit 111 is set to 1, the energy of the incident wave is completely reflected; if the amplitude of the reflection unit 111 is set to 0.5, only 50% of the energy is reflected.

[0071] In some alternative embodiments, the signal reflection component 110 may further include an isolation component 113.

[0072] Among them, the isolation component 113 is sequentially deployed with the signal reflection component 110 in the working direction of the UAV takeoff and landing platform 100 for isolating communication signals.

[0073] Exemplarily, the isolation component 113 may be composed of signal isolation functional elements to achieve its signal isolation function. In one example, the isolation component 113 can be a metal plate. For example, the isolation component 113 can be a copper plate or an aluminum plate, etc.

[0074] In one example, Figure 4The schematic architecture diagram of the signal reflection component 110 provided by an embodiment of the present application is shown. As Figure 4 shown, the isolation component 113 can be deployed between the reflection unit 111 and the control unit 112.

[0075] Exemplarily, the direction of the horizontal plane can be used as the reference direction, and the working direction of the drone can be perpendicular to the reference direction. For example, if the drone takeoff and landing platform 100 is placed on the horizontal plane, the structure of the signal reflection component 110 from top to bottom can be the reflection unit 111, the isolation component 113, and the control unit 112 respectively.

[0076] It can be understood that in the embodiment of the present application, by adding the isolation component 113 in the signal reflection component 110, signal penetration is prevented, and thus communication signal attenuation is avoided.

[0077] Furthermore, in some optional embodiments, Figure 5 The schematic architecture diagram of the control unit 112 provided by an embodiment of the present application is shown. As Figure 5 shown, the control unit 112 includes a signal input sub-unit 1121, connected to the reflection unit 111; a data processing sub-unit 1122, connected to the signal input sub-unit 1121; a signal output sub-unit 1123, connected to the data processing sub-unit 1122 and the reflection unit 111; and a storage sub-unit 1124, connected to the data processing sub-unit 1122 for storing data.

[0078] The signal input sub-unit 1121 can be connected to the reflection unit 111 for transmitting the communication signal acquired by the reflection unit 111. Moreover, the signal input sub-unit 1121 can be electrically connected or communicatively connected to the reflection unit 111.

[0079] The data processing sub-unit 1122 receives the communication signal acquired by the signal input sub-unit 1121 by being connected to the signal input sub-unit 1121.

[0080] Exemplarily, the data processing sub-unit 1122 can be used to execute the above signal transmission method. Among them, the data processing sub-unit 1122 can also include a second pole sub-unit for data acquisition, a second pole sub-unit for data parsing, and a second pole sub-unit for dynamic adjustment.

[0081] Among them, the second pole sub-unit for data acquisition can receive data such as the real-time position, speed, and altitude of the drone. The second pole sub-unit for data parsing can determine the predicted position information of the drone and determine the phase and amplitude of each reflection unit 111 according to the predicted position information of the drone. The second pole sub-unit for dynamic adjustment can determine the configuration of each reflection unit 111 and feedback the communication quality in real time.

[0082] In one example, Figure 6 a schematic architecture diagram of the control unit 112 provided by an embodiment of the present application is shown. As Figure 6 shown, the control unit 112 may further include a power interface 601 and a network cable interface 602. Among them, the power interface 601 is connected to the mains power or a mobile power supply to supply power to the control unit 112 and the reflection unit 111. The network cable interface 602 of the implementation unit can be connected to the front end for debugging the parameters of the reflection unit 111.

[0083] The storage subunit 1124 is connected to the data processing subunit 1122 to store the control parameters, system parameters, and control parameters of the reflection unit 111.

[0084] In addition, in some other alternative embodiments, the control unit 112 may further include a power amplifier for power amplifying the communication signal. In one example, the power amplifier may include an input end, a control end, and an output end. Among them, the input end can be connected to the power interface 601 and is powered by the mains power or a mobile power supply. The control end can be connected to the data processing subunit 1122, and the data processing subunit 1122 can control the power amplifier by outputting a control signal. The output end can be connected to the signal output subunit 1123 for outputting the power-amplified signal reflection parameters to the reflection unit 111.

[0085] It can be understood that by adding a power amplifier in the control unit 112, the communication signal can be power amplified, thereby improving the signal coverage range and solving the problem of signal attenuation.

[0086] In the embodiment of the present application, the signal input subunit 1121 can transmit the received communication signal in the reflection unit 111 to the data processing subunit 1122, so that the data processing subunit 1122 can determine the signal reflection parameters of each reflection unit 111 by invoking the corresponding signal transmission method of the storage subunit 1124, and transmit the signal reflection parameters to the reflection unit 111 through the signal output subunit 1123, so that the transmitting unit can be adjusted based on the signal reflection parameters, thereby realizing the reflection of the signal.

[0087] In some alternative embodiments, the signal reflection component 110 is attached to the working plane of the UAV takeoff and landing platform 100. Among them, the working plane at least includes the plane parallel to the ground in the UAV takeoff and landing platform 100.

[0088] Exemplarily, the working plane of the UAV takeoff and landing platform 100 can be a plane for supporting the UAV. The signal reflection component 110 can be attached to the working plane. To ensure the performance of the signal reflection component 110, a protective shell, i.e., the cover plate 122, can be added between the signal reflection component 110 and the UAV. Further, the working plane can be a plane parallel to the ground in the UAV takeoff and landing platform 100. It can be understood that due to the flight characteristics of the UAV, generally, the signal needs to be reflected into the air. Therefore, the signal reflection component 110 can be deployed on a plane parallel to the bottom surface so that the communication signal can be better reflected into the air.

[0089] In one example, the signal reflection component 110 can be deployed at any position on the working plane according to different requirements. For example, the signal reflection component 110 can be deployed at the central position of the working plane.

[0090] Further, the signal transmission method provided by the embodiments of the present application will be introduced.

[0091] Figure 7 is a schematic flowchart of the signal transmission method provided by an embodiment of the present application. As Figure 7 shown, the signal transmission method includes the following steps S710 - S750:

[0092] S710. In response to receiving a communication signal, determine the UAV corresponding to the communication signal, and obtain the UAV pose information of the UAV.

[0093] Exemplarily, the communication signal sent by the signal source can be received by the signal reflection component 110 of the UAV takeoff and landing platform 100. Among them, the signal source can be a base station; or, the signal source can be a UAV control system, for example, a UAV control handle.

[0094] Exemplarily, after the UAV takeoff and landing platform 100 receives the communication signal, the UAV corresponding to the communication signal can be determined. After determining the UAV corresponding to the communication signal, the UAV pose information corresponding to the UAV can be obtained.

[0095] In one example, each UAV has a uniquely corresponding UAV identification information. And, the communication signal can include the UAV identification information to determine the UAV that the communication signal acts on. Further, the signal reflection component 110 can receive the UAV pose information sent by one or more UAVs, where the UAV pose information can include the UAV identification information corresponding to the UAV. After the signal reflection component 110 of the UAV takeoff and landing platform 100 receives the communication signal, the UAV that the communication signal acts on can be determined, that is, the UAV identification information can be determined. And from the one or more pieces of UAV pose information received, select the UAV pose information that matches the UAV identification information.

[0096] The UAV pose information includes at least one of the parameters such as the position (x, y, z) of the UAV and the speed (vx, vy, vz) of the UAV.

[0097] S720. Input the UAV pose information into the UAV position prediction model, and predict the position of the UAV through the UAV position prediction model to obtain the UAV predicted position information.

[0098] Exemplarily, the UAV pose information can be the UAV pose information at the current moment. The UAV position information at the current moment can be input into the UAV position prediction model, so that the UAV position prediction model predicts the position of the UAV at the next moment through the input UAV pose information to obtain the UAV predicted position information.

[0099] Exemplarily, the UAV position information is used to characterize the position of the UAV at a future moment.

[0100] S730. Determine the phase and amplitude corresponding to the communication signal according to the UAV predicted position information.

[0101] Exemplarily, the reflection direction of the communication signal can be determined according to the UAV predicted position information, and the phase and amplitude corresponding to the communication signal can be determined through the reflection direction of the communication signal. It can be understood that since the determined UAV predicted position information corresponds to the next moment of the current moment of the UAV, the reflection direction corresponding to the communication signal can be the direction of the position that the UAV can reach at the next moment.

[0102] Exemplarily, the direction of the communication signal can be changed by changing the phase and / or amplitude corresponding to the communication signal.

[0103] S740. Adjust the signal reflection parameters of the UAV takeoff and landing platform according to the phase and amplitude corresponding to the communication signal.

[0104] Exemplarily, after determining the phase and amplitude corresponding to the communication signal, determine the signal reflection parameters of each reflection unit 111 in the signal reflection component 110.

[0105] In one example, the signal reflection parameters at least include the parameter values corresponding to the capacitance, resistance, and inductance parameters corresponding to each reflection unit 111.

[0106] S750. The UAV takeoff and landing platform 100 with adjusted signal reflection parameters reflects the communication signal.

[0107] Exemplarily, the signal parameters of each reflection unit 111 in the UAV takeoff and landing platform 100 can be adjusted according to the signal reflection parameters, so that the UAV takeoff and landing platform 100 with adjusted parameters reflects the communication signal.

[0108] Exemplarily, after the signal reflection component 110 in the UAV takeoff and landing platform 100 receives the communication signal sent by the signal source, it can determine the UAV corresponding to the communication signal and obtain the UAV pose information of the UAV. Further, the UAV pose information is input into the UAV position prediction model to determine the UAV predicted position information of the UAV. According to the UAV predicted position information, the phase and amplitude corresponding to the communication signal are determined, and the signal reflection parameters of the UAV takeoff and landing platform 100 are adjusted according to the phase and amplitude corresponding to the communication signal, so that the UAV takeoff and landing platform 100 can reflect according to the UAV predicted position.

[0109] In the embodiments of the present application, the UAV takeoff and landing platform 100 can receive the communication signal and directly reflect the communication signal to the UAV, which can establish a continuous and stable communication link between the UAV and the UAV takeoff and landing platform 100, avoid the signal interruption problem during the takeoff and landing of the UAV, and improve the safety during the takeoff and landing of the UAV. Further, during the process of reflecting the communication signal to the UAV, by predicting the UAV predicted position information of the UAV at a future moment and using the UAV predicted position information as the target direction, the communication signal is reflected, so as to flexibly adjust the communication signal and make the communication signal accurately cover the UAV. Therefore, the communication signal reflected by the UAV takeoff and landing platform 100 can be applied to the dynamic scenario of the rapid movement of the UAV and provide communication support for the whole process of the UAV takeoff and landing.

[0110] Exemplarily, the position of the UAV can be characterized by the pitch angle and azimuth angle of the UAV relative to the UAV takeoff and landing platform 100. After determining the position of the UAV relative to the UAV takeoff and landing platform 100, the reflection direction of the communication signal can be determined.

[0111] Further, in order to determine the phase and amplitude corresponding to the communication signal, as another implementation manner of the present application, the present application also provides another implementation manner of the signal transmission method, which is specifically described in the following embodiments.

[0112] Figure 8 It is a schematic flowchart of the process for determining the phase and amplitude corresponding to the communication signal provided by an embodiment of the present application. As Figure 8 shown, the signal transmission method includes the following steps S731-S733:

[0113] S731. Determine the platform position information of the UAV takeoff and landing platform.

[0114] Exemplarily, the UAV takeoff and landing platform 100 can obtain its own platform position information (x RIS , y RIS , z RIS ).

[0115] In one example, the platform position information of the UAV takeoff and landing platform 100 can be determined by technologies such as the Global Navigation Satellite System (GNSS) and radio positioning technology.

[0116] S732. Determine the pitch angle and azimuth angle corresponding to the communication signal according to the predicted UAV position information and the platform position information.

[0117] Exemplarily, the horizontal plane where the UAV takeoff and landing platform 100 is located can be used as a reference. The pitch angle can represent the angle between the UAV and the horizontal plane where the UAV takeoff and landing platform 100 is located. The azimuth angle can be used to represent the orientation of the UAV in the horizontal direction.

[0118] In one example, the pitch angle θ can be represented by the following formula (1) respectively, and the azimuth angle can be represented by the following formula (2).

[0119]

[0120] Exemplarily, after determining the pitch angle and phase angle of the UAV relative to the UAV takeoff and landing platform, the direction represented by the pitch angle and phase angle can be used as the reflection direction of the communication signal. It can be understood that the communication signal needs to cover the UAV. Therefore, the reflection direction of the communication signal needs to cover the position of the UAV at a future moment. In view of this, the pitch angle and azimuth angle of the predicted UAV position relative to the UAV takeoff and landing platform 100 can be used as the pitch angle and range angle of the communication signal.

[0121] S733. Determine the phase and amplitude corresponding to the communication signal according to the pitch angle and azimuth angle corresponding to the communication signal.

[0122] Exemplarily, after determining the pitch angle and azimuth angle of the communication signal, the phase and amplitude corresponding to the communication signal can be determined so that the communication signal can be reflected to the position corresponding to the predicted UAV position information.

[0123] Exemplarily, the platform position information of the UAV takeoff and landing platform 100 can be obtained, and according to the predicted UAV position information and the platform position information, the azimuth angle and pitch angle corresponding to the communication signal can be calculated, so as to determine the phase and amplitude of the communication signal, and then determine the signal reflection parameters for each reflection unit, and adjust according to the determined signal reflection parameters, so that the communication signal can be transmitted to the position corresponding to the predicted UAV position information.

[0124] In the embodiments of the present application, the pitch angle and azimuth angle corresponding to the communication signal are determined through the predicted UAV position information and the platform position information, which can clearly and accurately represent the reflection direction of the communication signal, thereby realizing the precise reflection of the communication signal.

[0125] Further, in order to provide stable communication support throughout the process of the UAV taking off and landing, as another implementation manner of this application, this application also provides another implementation manner of the signal transmission method. For specific details, refer to the following embodiments.

[0126] Figure 9 It is a schematic flowchart of the signal transmission method provided by an embodiment of this application. As Figure 9 shown, the signal transmission method further includes the following steps S910 - S950:

[0127] S910. Predict the predicted signal strength index of the UAV when receiving the communication signal according to the phase and amplitude corresponding to the communication signal.

[0128] S920. Determine the initial phase update gradient according to the predicted signal strength index and the phase.

[0129] S930. Determine the initial amplitude update gradient according to the predicted signal strength index and the amplitude.

[0130] S940. Based on the initial phase update gradient and the initial amplitude update gradient, with the goal of maximizing the predicted signal strength index, update the phase and amplitude of the communication signal multiple times to determine the updated phase and amplitude.

[0131] S950. Adjust the signal reflection parameters of the UAV take - off and landing platform according to the updated phase and amplitude.

[0132] In some embodiments, in S910, the predicted signal strength index of the UAV when receiving the communication signal can be predicted according to the phase and amplitude corresponding to the communication signal.

[0133] Exemplarily, the signal reflection component can predict the strength index of the communication signal when the UAV receives the communication signal according to the phase and amplitude corresponding to the communication signal, that is, the predicted signal strength index. The predicted signal strength index can be the Reference Signal Receiving Power (RSRP).

[0134] In one example, the predicted signal strength index r can be calculated by the following formula (3):

[0135]

[0136] Among them, N reflection units 111 are deployed in the UAV take - off and landing platform 100, and α i is the phase of the i - th reflection unit 111; is the amplitude of the i - th reflection unit 111. h ih_i is the channel coefficient from the i-th reflection unit 111 to the UAV, ρ is the transmission power of the signal reflection component 110, and n represents noise.

[0137] In some embodiments, in S920, the initial phase update gradient can be determined according to the predicted signal strength index and the phase.

[0138] Exemplarily, the objective function can be constructed according to the predicted signal strength index, and the initial phase update gradient can be determined according to the objective function constructed based on the predicted signal strength index and the phase.

[0139] In one example, the objective function J can be defined by the following formula (4):

[0140] J = |r| 2 (4)

[0141] Furthermore, the initial phase update gradient can be represented by the following formula (5)

[0142]

[0143] where r * represents the conjugate complex number of the predicted signal strength index, and j represents the imaginary part of the complex number.

[0144] In some embodiments, in S930, the initial amplitude update gradient can be determined according to the predicted signal strength index and the amplitude.

[0145] Exemplarily, the initial amplitude update gradient can be determined according to the objective function constructed based on the predicted signal strength index and the amplitude.

[0146] In one example, the initial amplitude update gradient can be represented by the following formula (6)

[0147]

[0148] where e represents the rotation factor or phase shift.

[0149] In some embodiments, in S930, based on the initial phase update gradient and the initial amplitude update gradient, with the goal of maximizing the predicted signal strength index, the phase and amplitude of the communication signal are updated multiple times to determine the updated phase and amplitude.

[0150] Exemplarily, after determining the initial phase update gradient and the initial amplitude update gradient, with the goal of maximizing the predicted signal strength index, the phase and amplitude of the communication signal are updated multiple times through the initial phase update gradient and the initial amplitude update gradient to obtain the updated phase and amplitude.

[0151] In one example, when updating the phase and amplitude of a communication signal, the phase and amplitude of the communication signal can also be updated multiple times by using the initial phase update gradient and the initial amplitude update gradient with the goal of maximizing the objective function, so as to obtain the updated phase and amplitude.

[0152] In some alternative embodiments, based on the initial phase update gradient, with the goal of maximizing the predicted signal strength metric, the phase can be updated along the positive gradient direction of the predicted signal strength metric to obtain the updated phase. And based on the initial amplitude update gradient, with the goal of maximizing the predicted signal strength metric, the amplitude can be updated along the positive gradient direction of the predicted signal strength metric to obtain the updated amplitude.

[0153] In one example, the updated phase can be characterized by the following formula (7), and the updated amplitude can be characterized by the following formula (8):

[0154]

[0155] where, (t) represents the t-th iteration, and (t + 1) represents the (t + 1)-th iteration; represents the learning rate of the phase, μ α represents the learning rate of the amplitude.

[0156] It can be understood that by using the initial phase update gradient and gradually updating the phase along the positive gradient direction of the predicted signal strength metric, the optimal solution, that is, the phase corresponding to the maximized predicted signal strength metric, can be determined efficiently and quickly. Similarly for the amplitude, according to the initial amplitude update gradient and gradually updating the amplitude along the positive gradient direction of the predicted signal strength metric, the amplitude corresponding to the maximized predicted signal strength metric can be obtained efficiently and quickly. Furthermore, by using the gradient descent method, the optimal solutions of the phase and amplitude are gradually determined, improving the calculation efficiency of the phase and amplitude corresponding to the communication signal.

[0157] Furthermore, in the embodiments of the present application, based on the phase and amplitude corresponding to the communication signal, the predicted signal strength metric of the drone when receiving the communication signal can be predicted. And based on the predicted signal strength metric, phase, and amplitude, the initial phase update gradient and the initial amplitude update gradient can be determined respectively. Further, based on the initial phase update gradient and the initial amplitude update gradient, with the goal of maximizing the predicted signal strength metric, the phase and amplitude of the communication signal can be updated multiple times to determine the updated phase and amplitude. And with the updated phase and amplitude, the signal reflection parameters of the drone takeoff and landing platform 100 can be adjusted. It can be understood that by gradually optimizing the phase and amplitude of the communication signal with the goal of maximizing the predicted signal strength metric, the adjustment of the adaptive communication signal of the drone can be realized, enabling the communication signal to be reflected in the optimal direction.

[0158] Further, in order to accurately predict the drone prediction position information corresponding to the drone, as another implementation manner of the present application, the present application also provides another implementation manner of the signal transmission method. For details, refer to the following embodiments.

[0159] Figure 10 is a schematic flowchart of determining the drone prediction position information provided by an embodiment of the present application. As Figure 10 shown, the signal transmission method includes the following steps S721 - S724:

[0160] S721. Input the drone pose information into the drone state equation and the drone observation equation respectively to obtain the drone prediction state corresponding to the drone state equation and the drone observation state corresponding to the drone observation equation.

[0161] Exemplarily, the drone position prediction model may include a drone state equation and a drone observation equation.

[0162] The drone state equation can be used to describe the motion state of the drone over time. Among them, the drone state equation can be expressed by the following formula (9):

[0163] x k = Fx k-1 + Bu k-1 + w k-1 (9)

[0164] Among them, F is the state transition matrix, and Bu k-1 can represent the control input, such as the drone acceleration, etc. w k-1 is the process noise. k can be used to represent the moment. Among them, x k can include information such as the drone position and the drone speed, and it can be represented as x k = (x, y, z, vx, vy, vz) T . The process noise follows a Gaussian distribution, that is Q is the process noise covariance matrix.

[0165] The drone observation equation can be used to characterize the drone state actually detected by the sensing device. Among them, the drone observation equation can be expressed by the following formula (10):

[0166] z k = Hx k + v k (10)

[0167] Among them, H represents the observation matrix, and v k is the observation noise. For example, v kIt may include positioning errors, etc. Among them, the observation noise follows a Gaussian distribution, that is R is the observation noise covariance matrix.

[0168] S722. Determine the covariance information according to the predicted state of the UAV and the observed state of the UAV.

[0169] Exemplarily, the predicted state of the UAV can be corrected according to the observed state of the UAV, and the prediction error covariance can be determined.

[0170] In one example, the prediction error covariance P can be expressed by the following formula (11) k|k-1 :

[0171] P k|k-1 = FP k-1 F T + Q (11)

[0172] where P k|k-1 is the prediction error covariance of the single-step prediction of the UAV state.

[0173] S723. Construct the gain information according to the covariance information corresponding to the UAV state equation and the observed state of the UAV.

[0174] In one example, the gain information K can be expressed by the following formula (12) k :

[0175] K k = P k|k-1 H T (HP k|k-1 H T + R) -1 (12)

[0176] S724. Determine the predicted position information of the UAV according to the covariance information, the gain information and the predicted state of the UAV.

[0177] Furthermore, the UAV state prediction equation can be updated according to the covariance information, the gain information and the predicted state of the UAV, so as to determine the predicted position information of the UAV.

[0178] In one example, the updated UAV state prediction equation can be expressed by the following formula (13):

[0179] x k = x k|k-1 + K k (z k - Hx k|k-1 ) (13)

[0180] where x k|k-1 represents x at the current moment k-1The next moment.

[0181] Furthermore, the position of the UAV can be predicted according to the updated UAV state prediction equation.

[0182] In the embodiments of the present application, by inputting the UAV pose information into the UAV state equation and the UAV observation equation respectively, the predicted UAV state corresponding to the UAV state equation and the observed UAV state corresponding to the UAV observation equation are obtained; and according to the predicted UAV state and the observed UAV state, covariance information is determined. According to the covariance information corresponding to the UAV state equation and the observed UAV state, gain information is constructed. Furthermore, according to the covariance information, the gain information and the predicted UAV state, the predicted UAV position information is determined. In this way, the accuracy, robustness and real-time performance of UAV positioning are improved. And it can achieve stable and reliable UAV positioning in complex environments.

[0183] Furthermore, in order to realize the closed-loop dynamic optimization of communication signals, as another implementation manner of the present application, the present application also provides another implementation manner of the signal transmission method, which is specifically described in the following embodiments.

[0184] Figure 11 is a schematic flowchart of the signal transmission method provided by an embodiment of the present application. As Figure 11 shown, the signal transmission method further includes the following steps S1110 - S1140:

[0185] S1110. Obtain the communication signal strength index fed back by the UAV when receiving the communication signal.

[0186] Exemplarily, the signal reflection component 110 can receive the communication signal strength index fed back by the UAV.

[0187] Wherein, the communication signal strength index can be the reference signal received power.

[0188] In one example, after the UAV receives the communication signal reflected by the signal reflection component 110, it can feed back the communication signal strength index corresponding to the communication signal to the signal reflection component.

[0189] S1120. When it is determined that the communication signal strength index does not meet the preset signal strength condition, update the phase and amplitude of the communication signal according to the predicted signal strength index.

[0190] Wherein, the predicted signal strength index is the signal strength index determined according to the phase and amplitude of the communication signal.

[0191] Exemplarily, the preset signal strength condition is determined by those skilled in the art according to different communication requirements.

[0192] In one example, a power threshold can be set as the signal strength condition. When it is determined that the received power of the reference signal received by the reflection component is less than or equal to the preset power threshold, it is determined that the communication signal strength index does not meet the preset signal strength condition.

[0193] Furthermore, when it is determined that the communication signal strength index does not meet the preset signal strength condition, the phase and amplitude corresponding to the communication signal can be updated according to the predicted signal strength index.

[0194] In one example, the initial phase update gradient and the initial amplitude update gradient can be determined respectively according to the predicted signal strength index, phase and amplitude. Then, according to the initial phase update gradient and the initial amplitude update gradient, with the goal of maximizing the predicted signal strength index, the phase and amplitude of the communication signal are updated multiple times to determine the updated phase and amplitude.

[0195] In some embodiments, the amplitude and phase of the communication signal can also be updated according to the signal strength condition. For example, with the goal of maximizing the signal strength, the phase and amplitude of the communication signal are gradually updated in the way of gradient descent.

[0196] S1130. Adjust the signal reflection parameters of the UAV takeoff and landing platform according to the updated phase and amplitude.

[0197] Exemplarily, the signal reflection parameters of each reflection unit 111 can be determined according to the updated phase and amplitude of the communication signal, and then each reflection unit is adjusted according to the signal reflection parameters.

[0198] S1140. Reflect the communication signal through the UAV takeoff and landing platform with adjusted signal reflection parameters.

[0199] Exemplarily, the communication signal can be transmitted through the UAV takeoff and landing platform with adjusted signal reflection parameters.

[0200] Exemplarily, the communication signal strength index fed back by the UAV when receiving the communication signal can be obtained. And it is judged that the communication signal strength index does not meet the preset signal strength condition. When it is determined that the communication signal strength index does not meet the preset signal strength condition, according to the predicted signal strength index, the phase and amplitude corresponding to the communication signal are updated, and then according to the updated phase and amplitude, the signal reflection parameters of the UAV takeoff and landing platform 100 are adjusted; and the communication signal is reflected through the UAV takeoff and landing platform with adjusted signal reflection parameters.

[0201] In the embodiments of the present application, by determining whether the communication signal strength index fed back by the drone meets the preset signal strength condition, and in the case where the preset signal strength condition is not met, readjusting the phase and amplitude of the communication signal, the closed-loop dynamic optimization process between the drone and the drone takeoff and landing platform 100 is realized, ensuring stable communication during the takeoff and landing process of the drone.

[0202] Exemplarily, in combination with Figure 12 and Figure 13 the signal transmission method will be described.

[0203] Figure 12 FIG. is a schematic flowchart of a signal transmission method provided by an embodiment of the present application; Figure 13 FIG. is a schematic deployment scenario diagram of a drone with a drone takeoff and landing platform 100 provided by an embodiment of the present application.

[0204] Exemplarily, as Figure 12 shown, first, step S1201 can be executed to obtain real-time drone data information. Among them, the real-time drone data information can include drone position information, speed information, etc. Next, S1202 is executed to predict the position of the drone at a future moment. In one example, the future position of the drone can be predicted by the Kalman filter algorithm. Further, in S1203, the reflection direction of the communication signal can be determined according to the future position of the drone. The reflection direction of the communication signal can be characterized by calculating the pitch angle and the azimuth angle. In step S1204, based on the gradient optimization algorithm, the phase and amplitude of the communication signal can be optimized. Further still, in S1205, the dynamic adjustment of the communication signal can be realized by detecting the communication quality.

[0205] Further, as Figure 13 shown, one or more drone takeoff and landing platforms 100 can be deployed simultaneously in the same area. Among them, one or more drone takeoff and landing platforms can be deployed to designated points according to requirements to meet the takeoff and landing needs of a large number of drones. And when deploying the drone takeoff and landing platform 100, attention should be paid to the physical interval between the platforms to avoid collisions between drones.

[0206] Based on the signal transmission method provided in the above embodiments, correspondingly, the present application also provides a specific implementation manner of a signal transmission device. Please refer to the following embodiments.

[0207] First, refer to Figure 14 , the signal transmission device provided by the embodiment of the present application includes the following modules:

[0208] An acquisition module 1401, configured to determine the drone corresponding to the communication signal and acquire the drone pose information of the drone in response to receiving the communication signal;

[0209] The first determination module 1402 is configured to input the UAV pose information into a UAV position prediction model, and predict the position of the UAV through the UAV position prediction model to obtain UAV predicted position information;

[0210] The second determination module 1403 is configured to determine the phase and amplitude corresponding to the communication signal according to the UAV predicted position information;

[0211] The adjustment module 1404 is configured to adjust the signal reflection parameters of the UAV takeoff and landing platform according to the phase and amplitude corresponding to the communication signal;

[0212] The reflection module 1405 is configured to reflect the communication signal through the UAV takeoff and landing platform with adjusted signal reflection parameters.

[0213] As an implementation manner of this application, the second determination module 1403 determines the phase and amplitude corresponding to the communication signal according to the UAV predicted position information in the following manner: determining the platform position information of the UAV takeoff and landing platform; determining the pitch angle and azimuth angle corresponding to the communication signal according to the UAV predicted position information and the platform position information; determining the phase and amplitude corresponding to the communication signal according to the pitch angle and azimuth angle corresponding to the communication signal.

[0214] As an implementation manner of this application, after adjusting the signal reflection parameters of the UAV takeoff and landing platform according to the phase and amplitude corresponding to the communication signal, the device further includes: an update module, configured to predict a predicted signal strength index of the UAV in the case of receiving the communication signal according to the phase and amplitude corresponding to the communication signal; determining an initial phase update gradient according to the predicted signal strength index and the phase; determining an initial amplitude update gradient according to the predicted signal strength index and the amplitude; based on the initial phase update gradient and the initial amplitude update gradient, with the goal of maximizing the predicted signal strength index, updating the phase and amplitude of the communication signal multiple times to determine the updated phase and amplitude; adjusting the signal reflection parameters of the UAV takeoff and landing platform according to the updated phase and amplitude.

[0215] As an implementation manner of the present application, the updating module updates the phase and amplitude of the communication signal multiple times based on the initial phase update gradient and the initial amplitude update gradient, with the goal of maximizing the predicted signal strength index, to determine the updated phase and amplitude: Based on the initial phase update gradient, with the goal of maximizing the predicted signal strength index, update the phase along the positive gradient direction of the predicted signal strength index to obtain the updated phase; Based on the initial amplitude update gradient, with the goal of maximizing the predicted signal strength index, update the amplitude along the positive gradient direction of the predicted signal strength index to obtain the updated amplitude.

[0216] As an implementation manner of the present application, the UAV position prediction model includes a UAV state equation and a UAV observation equation; The first determination module 1402 predicts the position of the UAV by inputting the UAV pose information into the UAV position prediction model in the following manner to obtain the UAV predicted position information: Input the UAV pose information into the UAV state equation and the UAV observation equation respectively to obtain the UAV predicted state corresponding to the UAV state equation and the UAV observation state corresponding to the UAV observation equation; Determine the covariance information according to the UAV predicted state and the UAV observation state; Construct the gain information according to the covariance information corresponding to the UAV state equation and the UAV observation state; Determine the UAV predicted position information according to the covariance information, the gain information and the UAV predicted state.

[0217] As an implementation manner of the present application, the updating module is further configured to: Obtain the communication signal strength index fed back by the UAV when receiving the communication signal; When it is determined that the communication signal strength index does not meet the preset signal strength condition, update the phase and amplitude corresponding to the communication signal according to the predicted signal strength index, where the predicted signal strength index is a signal strength index determined according to the phase and amplitude corresponding to the communication signal; Adjust the signal reflection parameter of the UAV takeoff and landing platform according to the updated phase and amplitude; Reflect the communication signal through the UAV takeoff and landing platform with the adjusted signal reflection parameter.

[0218] Figure 15 The hardware structure diagram of the signal transmission device provided by the embodiment of the present application is shown.

[0219] In the signal transmission device 1500, it may include a processor 1501 and a memory 1502 storing computer program instructions.

[0220] Specifically, the above-mentioned processor 1501 may include a central processing unit (CPU), or an application specific integrated circuit (ASIC), or may be configured as one or more integrated circuits for implementing the embodiments of the present application.

[0221] The memory 1502 may include a mass storage for data or instructions. By way of example and not limitation, the memory 1502 may include a hard disk drive (HDD), a floppy disk drive, a flash memory, an optical disk, a magneto-optical disk, a magnetic tape, or a universal serial bus (USB) drive, or a combination of two or more of these. In a suitable case, the memory 1502 may include a removable or non-removable (or fixed) medium. In a suitable case, the memory 1502 may be inside or outside the integrated gateway disaster recovery device. In a specific embodiment, the memory 1502 is a non-volatile solid state memory.

[0222] The memory may include a read-only memory (ROM), a random access memory (RAM), a magnetic disk storage media device, an optical storage media device, a flash memory device, an electrical, optical, or other physical / tangible memory storage device. Thus, in general, the memory includes one or more tangible (non-transitory) computer-readable storage media (e.g., memory devices) encoded with software including computer-executable instructions, and when the software is executed (e.g., by one or more processors), it is operable to perform the operations described with reference to the method according to an aspect of the present disclosure.

[0223] The processor 1501 reads and executes the computer program instructions stored in the memory 1502 to implement any one of the signal transmission methods in the above embodiments.

[0224] In one example, the signal transmission device may further include a communication interface 1503 and a bus 1510. Among them, as Figure 15 shown, the processor 1501, the memory 1502, and the communication interface 1503 are connected through the bus 1510 and complete communication with each other.

[0225] The communication interface 1503 is mainly used to implement communication between the modules, devices, units, and / or devices in the embodiments of the present application.

[0226] The bus 1510 includes hardware, software, or both, and couples the components of the online data flow metering device to each other. By way of example and not limitation, the bus may include an Accelerated Graphics Port (AGP) or other graphics bus, an Enhanced Industry Standard Architecture (EISA) bus, a Front Side Bus (FSB), a HyperTransport (HT) interconnect, an Industry Standard Architecture (ISA) bus, an InfiniBand interconnect, a Low Pin Count (LPC) bus, a memory bus, a MicroChannel Architecture (MCA) bus, a Peripheral Component Interconnect (PCI) bus, a PCI-Express (PCI-X) bus, a Serial Advanced Technology Attachment (SATA) bus, a Video Electronics Standards Association Local (VLB) bus, or other suitable buses, or a combination of two or more of these. Where appropriate, the bus 1510 may include one or more buses. Although the embodiments of the present application describe and illustrate specific buses, the present application contemplates any suitable bus or interconnect.

[0227] The signal transmission device can execute the online data flow metering method in the embodiments of the present application based on the communication signal and the UAV pose information, so as to implement the combination Figure 9 and Figure 14 the signal transmission method described.

[0228] In addition, in combination with the signal transmission method in the above embodiments, the embodiments of the present application can provide a computer storage medium to implement. Computer program instructions are stored on the computer storage medium; when the computer program instructions are executed by a processor, any one of the signal transmission methods in the above embodiments is implemented.

[0229] The embodiments of the present application also provide a computer program product, including a computer program, and when the computer program is executed by a processor, any one of the signal transmission methods in the above embodiments is implemented.

[0230] It should be clear that the present application is not limited to the specific configurations and processes described above and illustrated in the figures. For the sake of brevity, detailed descriptions of known methods are omitted here. In the above embodiments, several specific steps are described and illustrated as examples. However, the method process of the present application is not limited to the specific steps described and illustrated, and those skilled in the art can make various changes, modifications, and additions, or change the order between steps after understanding the spirit of the present application.

[0231] The functional blocks shown in the above structural block diagram can be implemented as hardware, software, firmware, or a combination thereof. When implemented in hardware, it can be, for example, an electronic circuit, an application-specific integrated circuit (ASIC), appropriate firmware, a plug-in, a functional card, and so on. When implemented in software, the elements of the present application are programs or code segments used to perform the required tasks. The program or code segment can be stored in a machine-readable medium or transmitted via a data signal carried in a carrier wave over a transmission medium or a communication link. "Machine-readable medium" can include any medium capable of storing or transmitting information. Examples of machine-readable media include electronic circuits, semiconductor memory devices, ROM, flash memory, erasable ROM (EROM), floppy disks, CD-ROMs, optical discs, hard disks, fiber optic media, radio frequency (RF) links, and so on. The code segment can be downloaded via a computer network such as the Internet, an intranet, and so on.

[0232] It should also be noted that in the exemplary embodiments mentioned in the present application, some methods or systems are described based on a series of steps or devices. However, the present application is not limited to the order of the above steps. That is to say, the steps can be executed in the order mentioned in the embodiments, can be different from the order in the embodiments, or several steps can be executed simultaneously.

[0233] As described above with reference to the flowcharts and / or block diagrams of methods, apparatuses (systems), and computer program products according to embodiments of the present disclosure. It should be understood that each block in the flowchart and / or block diagram, and the combination of blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing devices to generate a machine such that these instructions executed by the processor of the computer or other programmable data processing devices enable the implementation of the functions / actions specified in one or more blocks of the flowchart and / or block diagram. Such a processor can be, but is not limited to, a general-purpose processor, a special-purpose processor, a special application processor, or a field programmable logic circuit. It can also be understood that each block in the block diagram and / or flowchart, and the combination of blocks in the block diagram and / or flowchart, can also be implemented by dedicated hardware that performs the specified functions or actions, or can be implemented by a combination of dedicated hardware and computer instructions.

[0234] The above is only the specific implementation manner of the present application. Those skilled in the art can clearly understand that for the convenience and brevity of description, the specific working processes of the above-described systems, modules, and units can refer to the corresponding processes in the foregoing method embodiments and will not be elaborated herein. It should be understood that the protection scope of the present application is not limited thereto. Any person skilled in the art within the technical scope disclosed in the present application can easily think of various equivalent modifications or substitutions, and these modifications or substitutions should all be covered within the protection scope of the present application.

Claims

1. A signal transmission method, characterized in that A signal reflection component applied to a UAV takeoff and landing platform, the method comprising: In response to receiving a communication signal, determining the UAV corresponding to the communication signal, and obtaining the UAV pose information of the UAV; Inputting the UAV pose information into a UAV position prediction model, and predicting the position of the UAV through the UAV position prediction model to obtain UAV predicted position information; Determining the phase and amplitude corresponding to the communication signal according to the UAV predicted position information; Adjusting the signal reflection parameters of the UAV takeoff and landing platform according to the phase and amplitude corresponding to the communication signal; Reflecting the communication signal through the UAV takeoff and landing platform with the signal reflection parameters adjusted.

2. The method according to claim 1, wherein The determining the phase and amplitude corresponding to the communication signal according to the UAV predicted position information includes: Determining the platform position information of the UAV takeoff and landing platform; Determining the pitch angle and azimuth angle corresponding to the communication signal according to the UAV predicted position information and the platform position information; Determining the phase and amplitude corresponding to the communication signal according to the pitch angle and azimuth angle corresponding to the communication signal.

3. The method according to claim 1, wherein After the adjusting the signal reflection parameters of the UAV takeoff and landing platform according to the phase and amplitude corresponding to the communication signal, the method further includes: Predicting the predicted signal strength index of the UAV in the case of receiving the communication signal according to the phase and amplitude corresponding to the communication signal; Determining an initial phase update gradient according to the predicted signal strength index and the phase; Determining an initial amplitude update gradient according to the predicted signal strength index and the amplitude; Based on the initial phase update gradient and the initial amplitude update gradient, with the goal of maximizing the predicted signal strength index, updating the phase and amplitude of the communication signal multiple times to determine the updated phase and amplitude; Adjusting the signal reflection parameters of the UAV takeoff and landing platform according to the updated phase and amplitude.

4. The method according to claim 3, characterized in that The based on the initial phase update gradient and the initial amplitude update gradient, with the goal of maximizing the predicted signal strength index, updating the phase and amplitude of the communication signal multiple times to determine the updated phase and amplitude includes: Based on the initial phase update gradient, with the goal of maximizing the predicted signal strength index, updating the phase along the positive gradient direction of the predicted signal strength index to obtain the updated phase; Based on the initial amplitude update gradient, with the goal of maximizing the predicted signal strength index, updating the amplitude along the positive gradient direction of the predicted signal strength index to obtain the updated amplitude.

5. The method according to claim 1, wherein The UAV position prediction model includes a UAV state equation and a UAV observation equation; The inputting the UAV pose information into a UAV position prediction model, and predicting the position of the UAV through the UAV position prediction model to obtain UAV predicted position information includes: Input the UAV pose information into the UAV state equation and the UAV observation equation respectively to obtain the UAV predicted state corresponding to the UAV state equation and the UAV observation state corresponding to the UAV observation equation; Determine the covariance information according to the UAV predicted state and the UAV observation state; Construct the gain information according to the covariance information corresponding to the UAV state equation and the UAV observation state; Determine the UAV predicted position information according to the covariance information, the gain information and the UAV predicted state.

6. The method according to claim 1, characterized in that Further includes: Obtain the communication signal strength index fed back by the UAV when receiving the communication signal; When it is determined that the communication signal strength index does not meet the preset signal strength condition, update the phase and amplitude of the communication signal according to the predicted signal strength index, where the predicted signal strength index is the signal strength index determined according to the phase and amplitude of the communication signal; Adjust the signal reflection parameters of the UAV takeoff and landing platform according to the updated phase and amplitude; Reflect the communication signal through the UAV takeoff and landing platform with adjusted signal reflection parameters.

7. An unmanned aerial vehicle takeoff and landing platform, characterized in that, The UAV takeoff and landing platform includes: A signal reflection component for performing the signal transmission method according to any one of claims 1-6; A support component for carrying the signal reflection component and the UAV, wherein the signal reflection component is attached to the support component.

8. The UAV takeoff and landing platform according to claim 7, characterized in that, The signal reflection component includes: A plurality of reflection units arranged in an array for receiving the communication signal; And a control unit, the control unit is connected to a plurality of the reflection units for determining the signal reflection parameters of the reflection units so that the reflection units adjusted according to the signal reflection parameters reflect the communication signal.

9. The drone takeoff and landing platform according to claim 8, wherein, The control unit includes: A signal input sub-unit connected to the reflection unit; A data processing sub-unit connected to the signal input sub-unit; A signal output sub-unit connected to the data processing sub-unit and the reflection unit; A storage sub-unit connected to the data processing sub-unit for storing data.

10. The drone takeoff and landing platform according to claim 9, characterized in that, The control unit further includes: A power amplifier for power amplifying the communication signal.

11. The drone takeoff and landing platform according to claim 8, characterized in that, The signal reflection component further includes: An isolation component, the isolation component is sequentially deployed with the reflection unit in the working direction of the UAV takeoff and landing platform for isolating the communication signal.

12. The drone takeoff and landing platform according to any one of claims 7-11, wherein The signal reflection component is attached to the working plane of the UAV takeoff and landing platform, and the working plane at least includes the plane parallel to the ground in the UAV takeoff and landing platform.

13. A signal transmission method and apparatus, characterized in that, A signal reflection component applied to a UAV takeoff and landing platform, the device includes: An acquisition module for determining the UAV corresponding to the communication signal and acquiring the UAV pose information of the UAV in response to receiving the communication signal; A first determination module for inputting the UAV pose information into a UAV position prediction model, predicting the position of the UAV through the UAV position prediction model, and obtaining the UAV predicted position information; A second determination module, configured to determine a phase and an amplitude corresponding to the communication signal according to the predicted position information of the drone; An adjustment module, configured to adjust signal reflection parameters of the drone takeoff and landing platform according to the phase and the amplitude corresponding to the communication signal; A reflection module, configured to reflect the communication signal through the drone takeoff and landing platform with adjusted signal reflection parameters.

14. A signal transmission method and device, characterized in that, The device includes: a processor and a memory storing computer program instructions; When the processor executes the computer program instructions, the signal transmission method according to any one of claims 1-6 is implemented.

15. A computer-readable storage medium, characterized in that, Computer program instructions are stored on the computer-readable storage medium, and when the computer program instructions are executed by a processor, the signal transmission method according to any one of claims 1-6 is implemented.

16. A computer program product, characterized in that, When the instructions in the computer program product are executed by a processor of an electronic device, the electronic device is caused to execute the signal transmission method according to any one of claims 1-6.

Images