Flight parameter determination method and device, electronic equipment and storage medium

Abstract

The invention discloses a flight parameter determination method and apparatus, an electronic device and a storage medium. The method comprises the steps of determining a target value of a flight parameter of a flight device by using a link propagation loss model and a coverage radius model; wherein the flight equipment carries an air base station, the link propagation loss model and the coverage radius model are models associated with flight parameters, and the link propagation loss model is a model representing signal propagation loss between the air base station and the terminal; the coverage radius model is a model representing a signal coverage area in the flight process of the flight equipment carrying the air base station. According to the technical scheme, the flight parameters such as the flight height, the circling radius and the rolling of the flight equipment carrying the air base station in the flight process can be planned, the design of the optimal flight scheme in the emergency scene is effectively guided, and efficient application and development of emergency tasks in various scenes are guaranteed.

Description

Technical Field

[0001] Embodiments of the present application relate to the field of communications, and in particular, to a method and apparatus for determining flight parameters, an electronic device, and a storage medium. Background Art

[0002] When natural disasters such as earthquakes, floods, and tsunamis occur, communication devices in the affected areas will be damaged, resulting in a large-scale paralysis of communication links. Using unmanned aerial vehicles (UAVs) can quickly fly to designated locations and carry emergency communication devices to provide wireless network coverage to the ground. However, due to factors such as the payload capacity of UAVs, flight time, base station transmission power, and path loss, the maximum continuous coverage range of UAV aerial base stations to the ground will be restricted. To improve the efficiency of emergency communication rescue, selecting an optimal flight plan to form an optimal UAV communication continuous coverage technology is of great significance for emergency rescue scenarios. Summary of the Invention

[0003] To solve the above technical problems, embodiments of the present application provide a method and apparatus for determining flight parameters, an electronic device, and a storage medium.

[0004] In a first aspect, embodiments of the present application provide a method for determining flight parameters, the method including:

[0005] Determining a target value of flight parameters of a flight device by using a link propagation loss model and a coverage radius model;

[0006] Wherein, the flight device is equipped with an aerial base station, the link propagation loss model and the coverage radius model are models associated with the flight parameters, the link propagation loss model is a model characterizing the signal propagation loss between the aerial base station and the terminal; the coverage radius model is a model characterizing the signal coverage area during the flight of the flight device equipped with the aerial base station.

[0007] In some embodiments, the determining a target value of flight parameters of a flight device by using a link propagation loss model and a coverage radius model includes:

[0008] Taking the coverage radius model as an objective function; wherein, the objective function includes the flight parameters of the flight device; the number of the flight parameters is greater than or equal to 1;

[0009] Taking the link propagation loss model as a first constraint condition, and taking the value range of at least some of the at least one flight parameter as a second constraint condition; the link propagation model includes the flight parameters of the flight device; the number of the second constraint conditions is greater than or equal to 1;

[0010] Construct a Lagrangian function according to the objective function, the first constraint condition, and the second constraint condition; wherein, the Lagrangian function includes the objective function, a first Lagrangian multiplier associated with the flight parameters introduced according to the first constraint condition, and a second Lagrangian multiplier associated with the flight parameters introduced according to the second constraint condition; the number of multipliers of the second Lagrangian is greater than or equal to 1;

[0011] Use the Lagrangian function to solve for the target value of the flight parameters of the flying device.

[0012] In some embodiments, the using the Lagrangian function to solve for the target value of the flight parameters of the flying device includes:

[0013] Solve for the partial derivatives of the flight parameters, the partial derivatives of the first Lagrangian multiplier, and the partial derivatives of the second Lagrangian multiplier included in the Lagrangian function;

[0014] By setting the partial derivatives of the flight parameters, the partial derivatives of the first Lagrangian multiplier, and the partial derivatives of the second Lagrangian multiplier to zero respectively, solve for the extreme values of the flight parameters;

[0015] Determine the extreme values of the solved flight parameters as the target values of the flight parameters of the flying device.

[0016] In some embodiments, the method further includes:

[0017] Substitute the extreme values of the solved flight parameters into the coverage radius model to obtain the maximum coverage radius during the flight of the aerial base station.

[0018] In some embodiments, before using the link propagation loss model and the coverage radius model to determine the target value of the flight parameters of the flying device, the method further includes:

[0019] Use the distance value between the aerial base station and the terminal, the carrier frequency of the aerial base station, and the additional loss of line-of-sight transmission corresponding to the current flight environment to construct a line-of-sight path loss model between the aerial base station and the terminal;

[0020] Use the distance value between the aerial base station and the terminal, the carrier frequency of the aerial base station, and the additional loss of non-line-of-sight transmission corresponding to the current flight environment to construct a non-line-of-sight path loss model between the aerial base station and the terminal;

[0021] Use the current flight environment and the elevation angle of the terminal relative to the aerial base station to construct a first probability model corresponding to the line-of-sight path loss, and determine a second probability model corresponding to the non-line-of-sight path loss according to the first probability model;

[0022] Construct a link propagation loss model between the aerial base station and the terminal by using the line-of-sight path loss model, the first probability model, the non-line-of-sight path loss model, and the second probability model.

[0023] In some embodiments, before determining the target value of the flight parameters of the flying device by using the link propagation loss model and the coverage radius model, the method further includes:

[0024] Construct a coverage radius model of the signal coverage area during the flight of the aerial base station by using the flight parameters of the flying device;

[0025] Wherein, the flying device hovers in the air with a set center and flight radius, and the flight parameters at least include one of the following: flight altitude, flight radius, roll angle, and the planar installation angle between the installed antenna and the flying device.

[0026] In some embodiments, the method further includes:

[0027] Hover and fly in the target area according to the target value of the flight parameters.

[0028] In a second aspect, an embodiment of the present application provides a device for determining flight parameters, and the device includes:

[0029] A determination unit, configured to determine the target value of the flight parameters of the flying device by using the link propagation loss model and the coverage radius model;

[0030] Wherein, the flying device is equipped with an aerial base station, the link propagation loss model and the coverage radius model are models associated with the flight parameters, the link propagation loss model is a model characterizing the signal propagation loss between the aerial base station and the terminal; the coverage radius model is a model characterizing the signal coverage area during the flight of the flying device equipped with the aerial base station.

[0031] In some embodiments, the determining unit is configured to use the coverage radius model as the objective function; wherein, the objective function includes flight parameters of the flying device; the number of the flight parameters is greater than or equal to 1; use the link propagation loss model as the first constraint condition, and use the value ranges of at least some of the at least one flight parameter as the second constraint condition; the link propagation model includes flight parameters of the flying device; the number of the second constraint conditions is greater than or equal to 1; construct a Lagrangian function according to the objective function, the first constraint condition, and the second constraint condition; wherein, the Lagrangian function includes the objective function, a first Lagrange multiplier associated with the flight parameter introduced according to the first constraint condition, and a second Lagrange multiplier associated with the flight parameter introduced according to the second constraint condition; the number of the second Lagrange multipliers is greater than or equal to 1; use the Lagrangian function to solve for the target values of the flight parameters of the flying device.

[0032] In some embodiments, the determining unit is configured to solve for the partial derivatives of the flight parameters, the partial derivatives of the first Lagrange multiplier, and the partial derivatives of the second Lagrange multiplier included in the Lagrangian function; by setting the partial derivatives of the flight parameters, the partial derivatives of the first Lagrange multiplier, and the partial derivatives of the second Lagrange multiplier to zero respectively, solve for the extreme values of the flight parameters; determine the solved extreme values of the flight parameters as the target values of the flight parameters of the flying device.

[0033] In some embodiments, the apparatus further includes:

[0034] A processing unit, configured to substitute the solved extreme values of the flight parameters into the coverage radius model to obtain the maximum coverage radius during the flight of the aerial base station.

[0035] In some embodiments, the apparatus further includes:

[0036] A first constructing unit, configured to construct a line-of-sight path loss model between the aerial base station and the terminal by using the distance value between the aerial base station and the terminal, the carrier frequency of the aerial base station, and the additional loss of line-of-sight transmission corresponding to the current flight environment; construct a non-line-of-sight path loss model between the aerial base station and the terminal by using the distance value between the aerial base station and the terminal, the carrier frequency of the aerial base station, and the additional loss of non-line-of-sight transmission corresponding to the current flight environment; construct a first probability model corresponding to the line-of-sight path loss by using the current flight environment and the elevation angle of the terminal relative to the aerial base station, and determine a second probability model corresponding to the non-line-of-sight path loss according to the first probability model; construct a link propagation loss model between the aerial base station and the terminal by using the line-of-sight path loss model, the first probability model, the non-line-of-sight path loss model, and the second probability model.

[0037] In some embodiments, the device further comprises:

[0038] A second construction unit, configured to construct a coverage radius model of the signal coverage area during the flight of the aerial base station by using the flight parameters of the flying device;

[0039] Wherein, the flying device hovers in the air with a set center and flight radius, and the flight parameters at least include one of the following: flight altitude, flight radius, roll angle, and the planar mounting angle between the mounted antenna and the flying device.

[0040] In some embodiments, the device further comprises:

[0041] A flight unit, configured to hover in a target area according to the target value of the flight parameters.

[0042] In a third aspect, an embodiment of the present application further provides an electronic device, which includes a memory and a processor. A computer executable instruction is stored on the memory, and when the processor runs the computer executable instruction on the memory, the method for determining the flight parameters described in the first aspect embodiment can be implemented.

[0043] In a fourth aspect, an embodiment of the present application further provides a computer storage medium, on which an executable instruction is stored, and when the executable instruction is executed by a processor, the method for determining the flight parameters described in the first aspect embodiment is implemented.

[0044] The technical solution of the embodiment of the present application can plan the flight parameters such as the flight altitude, hovering radius, and roll of the flying device carrying the aerial base station during flight by using the link propagation loss model and the coverage radius model, effectively guiding the design of the optimal flight plan in emergency scenarios, realizing the maximum emergency communication area coverage in scenarios such as earthquakes, floods, forest and grassland disasters, and important activities, and ensuring the efficient development and application of emergency tasks in various scenarios. BRIEF DESCRIPTION OF THE DRAWINGS

[0045] Figure 1 is a schematic flowchart of the method for determining flight parameters provided by an embodiment of the present application Figure 1 ;

[0046] Figure 2 is a schematic diagram of path loss in a flight scenario provided by an embodiment of the present application;

[0047] Figure 3 is a schematic diagram of the coverage radius of a flight scenario provided by an embodiment of the present application;

[0048] Figure 4 Schematic diagram of the construction process of the link propagation loss model provided by the embodiment of the present application;

[0049] Figure 5 Schematic diagram of the construction process of the coverage radius model provided by the embodiment of the present application;

[0050] Figure 6 Schematic diagram of the process of solving flight parameters by using the Lagrange multiplier method provided by the embodiment of the present application;

[0051] Figure 7 Schematic diagram of the process of solving the target value of the flight parameters of the flight device by using the Lagrange function provided by the embodiment of the present application;

[0052] Figure 8 Schematic diagram of the structural composition of the flight parameter determination device provided by the embodiment of the present application;

[0053] Figure 9 Schematic diagram of the structural composition of the electronic device provided by the embodiment of the present application. Detailed implementation manners

[0054] To make the objectives, technical solutions, and advantages of the embodiments of the present application clearer, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present application. Obviously, the described embodiments are only some of the embodiments of the present application, rather than all the embodiments. The components of the embodiments of the present application described and illustrated herein can be arranged and designed in various different configurations. Therefore, the detailed description of the embodiments of the present application provided in the accompanying drawings is not intended to limit the scope of the present application to be protected, but only represents the selected embodiments of the present application. All other embodiments obtained by those skilled in the art based on the embodiments of the present application without creative efforts fall within the scope of protection of the present application.

[0055] It should be noted that: similar reference numerals and letters denote similar items in the following drawings. Therefore, once an item is defined in one drawing, it does not need to be further defined and explained in subsequent drawings.

[0056] The term "and / or" in this article only describes an association relationship and indicates that there can be three relationships. For example, A and / or B can represent: A exists alone, A and B exist simultaneously, and B exists alone. In addition, the term "at least one" in this article means any one of multiple or any combination of at least two of multiple. For example, including at least one of A, B, and C can represent any one or more elements selected from the set composed of A, B, and C.

[0057] When using drones carrying aerial base stations to achieve continuous signal coverage of the ground, the aerial propagation environment is different from the ground propagation environment, and the propagation models are also different. Currently, most of the calculations based on the coverage range of base stations are studies based on ground propagation models, with less research on high-altitude air-ground propagation models. The research on propagation models and continuous coverage methods considering factors such as the flight altitude, hovering radius, and roll angle of drones is almost blank. Currently, the existing aerial emergency communication coverage technologies include one based on the emergency communication deployment of tethered rotor drones. The drones hover at low altitudes, and the coverage range can be estimated according to the geometric coverage model. Another coverage scheme based on drones combines the propagation model applicable to the ground, the COST-231 Hata model, to establish a link particle swarm optimization algorithm to obtain the angle between the installation surface of the directional beam antenna and the zenith.

[0058] The above-mentioned tethered drones do not consider the influence of factors such as flight attitude, antenna installation angle, and high-altitude propagation model on the maximum coverage range. Moreover, in an emergency state, the coverage range of tethered drones is small, the flight altitude is low, and the mobility is poor, so the applicable range in emergency communication is small.

[0059] The coverage model of the particle swarm optimization algorithm does not consider the difference between the path loss of high-altitude air-ground propagation and ground propagation loss, nor does it give the influence of flight parameters such as the optimal flight altitude and hovering radius of drones on the maximum continuous coverage range.

[0060] As the flight altitude of the drone increases, the coverage range of the drone increases, the distance between the drone and the ground terminal also gradually increases, and the path loss increases accordingly. To ensure the call quality of users, the received power Pr must exceed a certain threshold Pr min. This is equivalent to that the path loss from the drone to any user needs to be less than a certain threshold PL max to ensure smooth communication. If the propagation loss of the air-ground link between the drone base station and the ground terminal is greater than this threshold, the link will be interrupted, and continuous coverage of the ground cannot be achieved, affecting the user communication experience. Therefore, it is necessary to reasonably design the flight plan of the drone to improve the coverage range of the drone.

[0061] The technical solution of the embodiment of this application will consider the influence of the path loss of the propagation model in the high-altitude state, combine flight parameter information such as the flight altitude, flight hovering radius, flight roll angle, and antenna installation angle of the drone to construct an air-ground continuous coverage maximization model formula, and use the Lagrange multiplier method and the Karush-Kuhn-Tucker (KKT) conditions for optimization solving to give the optimal deployment plan in the state of maximum continuous coverage of the drone.

[0062] Next, the technical solution of the embodiment of this application will be introduced as follows.

[0063] Figure 1Schematic flow of the method for determining flight parameters provided by the embodiments of the present application Figure 1 , such as Figure 1 shown, including the following steps:

[0064] S101: Determine the target value of the flight parameters of the flight device by using the link propagation loss model and the coverage radius model.

[0065] In the embodiments of the present application, the aerial base station is located on the flight device, that is, the flight device is equipped with an aerial base station. The flight device is a device with a flight function, such as a drone, specifically a fixed-wing drone, or other devices with a flight function. When the base station is carried on the flight device, it can be called a mobile base station or an aerial base station.

[0066] In the embodiments of the present application, the method for determining the flight parameters can be executed by the flight device or by the aerial base station itself carried on the flight device with data processing and calculation functions. It can be understood that if the aerial base station determines the target value of the flight parameters, after the aerial base station determines the target value of the flight parameters, it will transmit the target value of the flight parameters to the flight device, so that the flight device flies in the air according to the target value of the flight parameters.

[0067] When the aerial base station flies in the air to achieve continuous coverage of the ground terminal, the base station transmits signals. The signal finally received by the terminal from the base station is a signal that has already suffered path loss.

[0068] In the embodiments of the present application, the link propagation loss model and the coverage radius model are models associated with the flight parameters of the flight device. The link propagation loss model is a model that characterizes the signal propagation loss between the aerial base station and the terminal; the coverage radius model is a model that characterizes the signal coverage area during the flight of the flight device carrying the aerial base station.

[0069] In the embodiments of the present application, the target value of the flight parameters of the flight device is the optimal flight parameters for achieving the best signal coverage of the aerial base station during the flight of the flight device. When the flight device carrying the aerial base station flies based on the optimal flight parameters, it can achieve the best signal coverage of the target area by the aerial base station.

[0070] Next, in combination with Figure 2 and Figure 3 the path loss and signal coverage area of the signal transmission during the flight of the flight device carrying the aerial base station in a flight scenario are analyzed as follows.

[0071] Figure 2 is the path loss schematic diagram in the flight scenario provided by the embodiments of the present application, such as Figure 2As shown, the link between the drone and the ground terminal is called the air-to-ground propagation link (ATG link). Compared with the traditional ground propagation link, this link has the characteristics of high line-of-sight probability, low attenuation, and good stability. Different from traditional base stations, the radio signals emitted by the emergency base station carried by the drone at high altitude first undergo line-of-sight propagation through free space. When the signal propagates to a very low altitude of about ten meters, it will continue to undergo shadowing and scattering caused by various obstacles such as hillsides, buildings, and vehicles, resulting in non-line-of-sight transmission and bringing additional propagation losses to the link. The air-to-ground propagation path generally consists of the line-of-sight path loss in free space and the additional loss caused by the non-line-of-sight path.

[0072] Figure 3 is a schematic diagram of the coverage radius of the flight scenario provided by the embodiment of the present application. As Figure 3 shown, the drone carrying the aerial base station hovers and flies in the target area according to the flight parameters. When the drone carrying the aerial base station and the base station antenna continuously cover the ground, the drone hovers and flies in a circle with a radius of R in the air. The center of the drone's hover is O1, and the hover radius is R uav , and the flight altitude of the drone is h uav . Assume that the normal direction of the drone antenna is HD, the maximum half-power angle of the installed antenna is 2β, the roll angle of the drone is γ, and the plane installation angle between the antenna and the drone is α. The elevation angle of the terminal relative to the drone at the farthest point B in the maximum continuous coverage area is θ.

[0073] When only considering the geometric coverage range of the antenna half-power angle, the coverage range of the drone on the leftmost side in the figure is a circle with B1C1 as the diameter. When the drone is on the rightmost side, the coverage range of the drone is a circle with BC as the diameter. In summary, the area that the drone can form continuous coverage at any time is a circular area with BB1 as the diameter and R max as the radius, that is, the gray area in the figure.

[0074] In the embodiment of the present application, the flight parameters include, but are not limited to, one or more of the following parameters: flight altitude, flight radius, antenna installation angle, and flight roll angle.

[0075] In the embodiment of the present application, based on Figure 2 the path loss of the signal propagation between the aerial base station and the terminal shown, a link propagation loss model is constructed, and, based on Figure 3 the signal coverage area during the flight of the aerial base station shown, a coverage radius model is constructed. Among them, when constructing the link propagation loss model and the coverage radius model, the model includes the flight parameters of the flight device, such as flight altitude, flight radius, flight roll angle, etc.

[0076] In the embodiments of the present application, by considering the path loss of signal propagation for communication coverage and the signal coverage range, the optimal flight parameters of a flying device carrying an aerial base station during flight are determined, effectively guiding the optimal flight plan in service scenarios and achieving the continuous maximum coverage range for the ground.

[0077] In the embodiments of the present application, by using the link propagation loss model and the coverage radius model to determine the target values of the flight parameters of the flying device, it is possible to plan the flight altitude, hovering radius, roll and other flight parameters of the flying device carrying the aerial base station during flight, effectively guiding the design of the optimal flight plan in emergency scenarios, achieving the maximum emergency communication area coverage in scenarios such as earthquakes, floods, forest and grassland disasters, and important events, and ensuring the efficient implementation of emergency tasks in various scenarios.

[0078] Figure 4 FIG. is a schematic diagram of the construction process of the link propagation loss model provided by the embodiments of the present application. As Figure 4 shown, the construction process of the link propagation loss model includes the following steps:

[0079] S401: Using the distance value between the aerial base station and the terminal, the carrier frequency of the aerial base station, and the additional loss corresponding to line-of-sight transmission in the current flight environment, construct a line-of-sight path loss model between the aerial base station and the terminal;

[0080] S402: Using the distance value between the aerial base station and the terminal, the carrier frequency of the aerial base station, and the additional loss corresponding to non-line-of-sight transmission in the current flight environment, construct a non-line-of-sight path loss model between the aerial base station and the terminal;

[0081] S403: Using the current flight environment and the elevation angle of the terminal relative to the aerial base station, construct a first probability model corresponding to the line-of-sight path loss, and determine a second probability model corresponding to the non-line-of-sight path loss according to the first probability model;

[0082] S404: Using the line-of-sight path loss model, the first probability model, the non-line-of-sight path loss model, and the second probability model, construct a link propagation loss model between the aerial base station and the terminal.

[0083] In the embodiments of the present application, the link propagation loss model between the aerial base station and the terminal can also be referred to as the air-ground propagation model. Next, the establishment process of the link propagation loss model is introduced as follows in combination with Figure 2 The signal propagation path of the aerial base station to the ground terminal generally consists of two parts: the line-of-sight path loss in free space and the additional loss caused by the non-line-of-sight route. The line-of-sight loss can be expressed as PL

[0084] The additional loss can be expressed as PL LOS and the additional loss can be expressed as PL NLOS :

[0085]

[0086]

[0087] In the above formulas (1) and (2), η Los and η NLos represent the additional losses during line-of-sight and non-line-of-sight transmissions respectively, and their values are related to the propagation environment. c represents the speed of light, fc represents the carrier frequency, and d represents the 3D distance between the drone and the ground terminal.

[0088] Considering the location environment where the ground terminal is located, which may be composed of a combination of line-of-sight and non-line-of-sight links, and combining the probability possibilities of line-of-sight and non-line-of-sight links, for a certain user on the ground, the path loss expectation of the ground user terminal can be expressed as:

[0089] PL = P Los *PL Los + P NLos *PL NLos (3)

[0090] In formula (3), P Los represents the probability value of line-of-sight link propagation, and P NLos represents the probability value of non-line-of-sight link propagation. The International Telecommunication Union has defined the calculation method of the line-of-sight propagation link, which is summarized as:

[0091]

[0092] P NLos = 1 - P Los (5)

[0093] In formula (4), a and b are constant values, depending on the test environment (such as rural, urban, dense urban, etc.), θ represents the elevation angle of the user with respect to the drone base station, and can be calculated as h represents the height of the drone base station, f represents the carrier frequency, c represents the speed of light, and d represents the three-dimensional distance between the drone and the user terminal. Simplifying and calculating the above formula gives:

[0094]

[0095] The above formula (6) is the link propagation loss model. By using this link propagation loss model, the line-of-sight path loss and non-line-of-sight path loss involved in communication coverage can be fully considered when designing the drone flight plan.

[0096] Figure 5 is a schematic diagram of the construction process of the coverage radius model provided by the embodiment of the present application, as Figure 5As shown in the figure, the construction process of the coverage radius model includes the following steps:

[0097] S501: Construct a coverage radius model of the signal coverage area during the flight of the aerial base station by using the flight parameters of the flight device;

[0098] Among them, the flight device hovers in the air with a set center and flight radius, and the flight parameters at least include one of the following: flight altitude, flight radius, roll angle, and the planar installation angle between the installed antenna and the flight device.

[0099] The following is combined with Figure 3 The construction process of the coverage radius model is introduced as follows:

[0100] Based on the above introduction of Figure 3 each parameter in Figure 3 the gray part area in Figure 3 is the ground coverage area of the aerial base station. As

[0101] ∵AB = h uav *tan(β - α + γ)

[0102]

[0103] ∴BB1 = AB + AB1 = 2AB - AA1

[0104] Therefore, the maximum coverage radius R max can be obtained:

[0105] BB1 = 2h uav *tan(β - α + γ) - 2R uav (7)

[0106]

[0107] In addition, according to Figure 3 it can be further obtained:

[0108]

[0109] The above formula (8) is the coverage radius model, which is also called the maximum coverage radius model. Using this maximum coverage radius model can ensure the maximum coverage area of the signal coverage of the UAV when designing the UAV flight plan.

[0110] Figure 6 is a schematic diagram of the process of solving the flight parameters by using the Lagrange multiplier method provided by the embodiment of the present application. As Figure 6 shown, the process of solving the flight parameters by using the Lagrange multiplier method includes the following steps:

[0111] S601: Take the coverage radius model as the objective function;

[0112] S602: Take the link propagation loss model as the first constraint condition, and take the value ranges of at least some of the at least one flight parameter as the second constraint condition;

[0113] S603: Construct a Lagrangian function according to the objective function, the first constraint condition, and the second constraint condition;

[0114] S604: Use the Lagrangian function to solve for the target values of the flight parameters of the flying device.

[0115] In the embodiments of the present application, the objective function includes the flight parameters of the flying device; the number of the flight parameters is greater than or equal to 1; the link propagation model includes the flight parameters of the flying device; the number of the second constraint conditions is greater than or equal to 1; the Lagrangian function includes the objective function, a first Lagrange multiplier associated with the flight parameters introduced according to the first constraint condition, and a second Lagrange multiplier associated with the flight parameters introduced according to the second constraint condition; the number of the multipliers of the second Lagrange is greater than or equal to 1.

[0116] In some embodiments, step S604 includes the following steps:

[0117] S6041: Solve the partial derivatives of the flight parameters, the partial derivatives of the first Lagrange multiplier, and the partial derivatives of the second Lagrange multiplier included in the Lagrangian function;

[0118] S6042: By setting the partial derivatives of the flight parameters, the partial derivatives of the first Lagrange multiplier, and the partial derivatives of the second Lagrange multiplier to zero respectively, solve for the extreme values of the flight parameters;

[0119] S6043: Determine the solved extreme values of the flight parameters as the target values of the flight parameters of the flying device.

[0120] Next, the solution for determining the target values of the flight parameters of the flying device using the Lagrangian function is introduced as follows.

[0121] During the flight of the flying device, to ensure the call quality of users in the continuously covered area, the received power Pr must exceed a certain threshold Pr min. This is equivalent to the path loss from the airborne base station carried by the flying device to any user needing to be less than a certain threshold PL maxTo ensure smooth communication, if the propagation loss of the air-ground link between the airborne base station carried by the flying device and the ground terminal is greater than this threshold, the link is interrupted. This threshold is combined with the maximum coverage radius R of the airborne base station max The objective function corresponding to the maximum propagation path loss PL max , that is, the radius area R that an airborne base station can serve. All path loss values within this radius R area are less than this threshold, then the link propagation loss can be calculated as follows:

[0122]

[0123] d 2 =h uav 2 +(h uav *tan(α - γ + β)) 2 (11)

[0124] Substituting into formula (6) gives the following formula (12):

[0125]

[0126] The above formula (12) is the finally constructed link propagation loss model. It can be seen that formula (12) includes flight parameters such as flight height h uav , antenna installation angle α, roll angle γ, etc.

[0127] The process of solving the optimal value using the Lagrange multiplier method is as follows, which includes the following sub-steps:

[0128] 1) Construct the objective function and constraints

[0129] When designing the maximum coverage radius, it is necessary to comprehensively consider information such as the flight height, flight radius, roll angle, installation angle, etc. of the flying device. A maximization optimization model composed of these factors is a multi-parameter function optimization model. Combining the maximum coverage radius calculated by formula (8), the model objective function is constructed as R max :

[0130] R max (h uav ,R uav ,α,γ)=h uav *tan(α - γ + β)-R uav (13)

[0131] The constraints are:

[0132]

[0133]

[0134]

[0135] Among them, in a given environment and scenario: the maximum path loss PL max , the test environment constants a, b; the additional losses η during line-of-sight and non-line-of-sight transmissions Los , η NLos ; the speed of light c, the carrier frequency fc, the half-power angle β of the installed antenna, etc. are all known quantities.

[0136] 2) Introduce the Lagrange multiplier and construct the Lagrangian function

[0137] Introduce the Lagrange multiplier Define the Lagrangian function L under inequality constraints for solution:

[0138]

[0139] 3) Solve the partial derivatives of all variables (including various flight parameters) and the Lagrange multiplier in all Lagrangian functions, set the partial derivatives to 0, and solve for the Lagrange multiplier.

[0140] Satisfy the KKT conditions, and the partial derivative calculation is as follows:

[0141]

[0142] After satisfying the KKT conditions, the feasible solution under the inequality constraint conditions can be obtained. By introducing the Lagrange multiplier, the constrained optimization problem with variables and constraint conditions is transformed into an unconstrained optimization problem.

[0143] Through solving the function, the extreme value at the point where the partial derivative is 0 is Obtain the maximum coverage distance R max Under the conditions, the optimal attitude scheme of the flying device {flight height, flight radius, antenna installation angle, flight roll angle}, that is, {h uav_0 , R uav_0 , α0, γ0}.

[0144] In the embodiments of the present application, by substituting the extreme values of the at least one variable obtained by solving, that is, {h uav_0 , R uav_0 , α0, γ0} into the coverage radius model, the maximum coverage radius during the flight of the aerial base station is obtained. This maximum coverage radius is the optimal coverage radius under the optimal coverage scheme.

[0145] The technical solution of the embodiment of the present application can design parameters such as the optimal flight height, hovering radius, antenna installation angle, and flight roll angle of the flying device when there is no ground signal by constructing an air-to-ground continuous coverage solution based on the air-to-ground propagation model, and effectively guide the design of the optimal flight plan in emergency scenarios. The constructed air-to-ground continuous coverage solution based on the air-to-ground propagation model mainly includes steps such as constructing the air-to-ground propagation model, constructing the geometric formula for continuous coverage of the air base station, and solving the optimal coverage plan by the Lagrange multiplier method.

[0146] The technical solution of the embodiment of the present application considers the influence of the path loss of the propagation model in the high-altitude state, and proposes a new air-to-ground continuous coverage maximization model formula in combination with the information of the flight height, flight hovering radius, flight roll angle, and antenna installation angle of the flying device. The Lagrange multiplier method and the KKT condition are used for optimization solution to give the optimal deployment plan under the maximum continuous coverage state of the air base station, which can effectively guide the design of the optimal flight plan in emergency scenarios, realize the maximum emergency communication area coverage in scenarios such as earthquakes, floods, forest and grassland disasters, and important activities, and ensure the efficient implementation of emergency tasks in various scenarios.

[0147] Figure 8 It is a schematic structural diagram of the device for determining flight parameters provided by the embodiment of the present application, as Figure 8 shown, the device for determining flight parameters includes:

[0148] A determination unit 801, configured to determine the target value of the flight parameters of the flying device by using a link propagation loss model and a coverage radius model;

[0149] Wherein, the flying device is equipped with an air base station, the link propagation loss model and the coverage radius model are models associated with the flight parameters, the link propagation loss model is a model characterizing the signal propagation loss between the air base station and the terminal; the coverage radius model is a model characterizing the signal coverage area during the flight of the flying device equipped with the air base station.

[0150] In some embodiments, the determining unit is configured to use the coverage radius model as the objective function; wherein, the objective function includes flight parameters of the flying device; the number of the flight parameters is greater than or equal to 1; use the link propagation loss model as the first constraint condition, and use the value range of at least some of the at least one flight parameter as the second constraint condition; the link propagation model includes flight parameters of the flying device; the number of the second constraint conditions is greater than or equal to 1; construct a Lagrangian function according to the objective function, the first constraint condition, and the second constraint condition; wherein, the Lagrangian function includes the objective function, a first Lagrange multiplier associated with the flight parameter introduced according to the first constraint condition, and a second Lagrange multiplier associated with the flight parameter introduced according to the second constraint condition; the number of the multipliers of the second Lagrange is greater than or equal to 1; use the Lagrangian function to solve for the target value of the flight parameters of the flying device.

[0151] In some embodiments, the determining unit is configured to solve the partial derivatives of the flight parameters, the partial derivatives of the first Lagrange multiplier, and the partial derivatives of the second Lagrange multiplier included in the Lagrangian function; by respectively setting the partial derivatives of the flight parameters, the partial derivatives of the first Lagrange multiplier, and the partial derivatives of the second Lagrange multiplier to zero, solve for the extreme values of the flight parameters; determine the solved extreme values of the flight parameters as the target values of the flight parameters of the flying device.

[0152] In some embodiments, the apparatus further includes:

[0153] The processing unit is configured to substitute the solved extreme values of the flight parameters into the coverage radius model to obtain the maximum coverage radius during the flight of the aerial base station.

[0154] In some embodiments, the apparatus further includes:

[0155] The first constructing unit is configured to construct a line-of-sight path loss model between the aerial base station and the terminal by using the distance value between the aerial base station and the terminal, the carrier frequency of the aerial base station, and the additional loss of line-of-sight transmission corresponding to the current flight environment; construct a non-line-of-sight path loss model between the aerial base station and the terminal by using the distance value between the aerial base station and the terminal, the carrier frequency of the aerial base station, and the additional loss of non-line-of-sight transmission corresponding to the current flight environment; construct a first probability model corresponding to the line-of-sight path loss by using the current flight environment and the elevation angle of the terminal relative to the aerial base station, and determine a second probability model corresponding to the non-line-of-sight path loss according to the first probability model; construct a link propagation loss model between the aerial base station and the terminal by using the line-of-sight path loss model, the first probability model, the non-line-of-sight path loss model, and the second probability model.

[0156] In some embodiments, the apparatus further comprises:

[0157] a second construction unit, configured to construct a coverage radius model of a signal coverage area during the flight of the aerial base station by using flight parameters of the flying device;

[0158] wherein the flying device hovers in the air with a set center and flight radius, and the flight parameters include at least one of the following: flight altitude, flight radius, roll angle, and a planar installation angle between the installed antenna and the flying device.

[0159] In some embodiments, the apparatus further comprises:

[0160] a flight unit, configured to hover in a target area according to target values of the flight parameters.

[0161] Those skilled in the art should understand that Figure 8 the implementation functions of the units in the determined device of the flight parameters shown can be understood with reference to the relevant descriptions of the foregoing method for determining flight parameters. Figure 8 The functions of the units in the determined device of the flight parameters shown can be implemented by a program running on a processor, or can be implemented by specific logic circuits.

[0162] The embodiments of the present application further provide an electronic device. Figure 9 As the schematic hardware structure diagram of the electronic device according to the embodiments of the present application, as Figure 9 shown, the electronic device includes: a communication component 903 for data transmission, at least one processor 901, and a memory 902 for storing a computer program that can run on the processor 901. Each component in the terminal is coupled together through a bus system 904. It can be understood that the bus system 904 is used to realize the connection and communication between these components. In addition to a data bus, the bus system 904 further includes a power bus, a control bus, and a status signal bus. However, for the sake of clear description, in Figure 9 all kinds of buses are labeled as the bus system 904.

[0163] Wherein, when the processor 901 executes the computer program, it at least executes Figure 1 the steps of the method for determining flight parameters shown.

[0164] It can be understood that the memory 902 can be a volatile memory or a non-volatile memory, or can include both volatile and non-volatile memories. Among them, the non-volatile memory can be a read-only memory (ROM, Read Only Memory), a programmable read-only memory (PROM, Programmable Read-Only Memory), an erasable programmable read-only memory (EPROM, Erasable Programmable Read-Only Memory), an electrically erasable programmable read-only memory (EEPROM, Electrically Erasable Programmable Read-Only Memory), a ferromagnetic random access memory (FRAM, ferromagnetic random access memory), a flash memory (Flash Memory), a magnetic surface memory, an optical disc, or a compact disc read-only memory (CD-ROM, Compact Disc Read-Only Memory); the magnetic surface memory can be a disk memory or a tape memory. The volatile memory can be a random access memory (RAM, Random Access Memory), which is used as an external cache. By way of example but not limitation, many forms of RAM are available, such as a static random access memory (SRAM, Static Random Access Memory), a synchronous static random access memory (SSRAM, Synchronous Static Random Access Memory), a dynamic random access memory (DRAM, Dynamic Random Access Memory), a synchronous dynamic random access memory (SDRAM, Synchronous Dynamic Random Access Memory), a double data rate synchronous dynamic random access memory (DDR SDRAM, Double Data Rate Synchronous Dynamic Random Access Memory), an enhanced synchronous dynamic random access memory (ESDRAM, Enhanced Synchronous Dynamic Random Access Memory), a sync link dynamic random access memory (SLDRAM, SyncLink Dynamic Random Access Memory), a direct rambus random access memory (DRRAM, Direct Rambus Random Access Memory).The memory 902 described in the embodiments of the present application is intended to include, but not limited to, these and any other suitable types of memories.

[0165] The methods disclosed in the embodiments of the present application above can be applied to the processor 901 or implemented by the processor 901. The processor 901 may be an integrated circuit chip with signal processing capabilities. In the implementation process, each step of the above method can be completed by the integrated logic circuit in the hardware of the processor 901 or the instructions in the form of software. The above-mentioned processor 901 may be a general-purpose processor, a DSP, or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The processor 901 can implement or execute each method, step, and logic block diagram disclosed in the embodiments of the present application. The general-purpose processor may be a microprocessor or any conventional processor, etc. Combining the steps of the method disclosed in the embodiments of the present application, it can be directly embodied as being executed and completed by the hardware decoding processor, or executed and completed by the combination of the hardware and software modules in the decoding processor. The software module may be located in the storage medium, and this storage medium is located in the memory 902. The processor 901 reads the information in the memory 902 and combines its hardware to complete the steps of the foregoing method.

[0166] In an exemplary embodiment, the electronic device can be implemented by one or more application-specific integrated circuits (ASICs, Application Specific Integrated Circuits), DSPs, programmable logic devices (PLDs, Programmable Logic Devices), complex programmable logic devices (CPLDs, Complex Programmable Logic Devices), FPGAs, general-purpose processors, controllers, MCUs, microprocessors (Microprocessors), or other electronic components, and is used to execute the foregoing method for determining flight parameters.

[0167] The embodiments of the present application also provide a computer-readable storage medium, on which a computer program is stored, and is characterized in that when the program is executed by a processor, it is at least used to execute Figure 1 the steps of the method for determining the flight parameters shown. The computer-readable storage medium may specifically be a memory. The memory may be the Figure 9 memory 902 shown.

[0168] Among the technical solutions described in the embodiments of the present application, they can be combined arbitrarily without conflict.

[0169] In several embodiments provided in this application, it should be understood that the disclosed methods and intelligent devices can be implemented in other ways. The device embodiments described above are merely illustrative. For example, the division of the units is only a logical function division. In actual implementation, there may be other division methods. For example, multiple units or components can be combined, or can be integrated into another system, or some features can be ignored, or not executed. In addition, the coupling, direct coupling, or communication connection between the displayed or discussed components can be through some interfaces. The indirect coupling or communication connection of devices or units can be electrical, mechanical, or other forms.

[0170] The units described above as separate components may or may not be physically separated. The components displayed as units may or may not be physical units, that is, they can be located in one place or distributed to multiple network units; some or all of the units can be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0171] In addition, each functional unit in the embodiments of this application can be all integrated in a second processing unit, or each unit can be separately used as a unit, or two or more units can be integrated in one unit; the above integrated unit can be implemented in the form of hardware, or in the form of hardware plus software functional units.

[0172] The above is only the specific implementation manner of this application, but the protection scope of this application is not limited thereto. Any person skilled in the art within the technical scope disclosed in this application can easily think of changes or substitutions, which should all be covered within the protection scope of this application.

Claims

1. A method for determining flight parameters, characterized in that, The method includes: Determining a target value of a flight parameter of a flight device by using a link propagation loss model and a coverage radius model; Wherein, the flight device is equipped with an aerial base station, the link propagation loss model and the coverage radius model are models associated with the flight parameter, the link propagation loss model is a model characterizing the signal propagation loss between the aerial base station and the terminal; the coverage radius model is a model characterizing the signal coverage area during the flight of the flight device equipped with the aerial base station.

2. The method according to claim 1, wherein The determining the target value of the flight parameter of the flight device by using the link propagation loss model and the coverage radius model includes: Taking the coverage radius model as an objective function; wherein, the objective function includes the flight parameter of the flight device; the number of the flight parameters is greater than or equal to 1; Taking the link propagation loss model as a first constraint condition, and taking the value range of at least some of the at least one flight parameter as a second constraint condition; the link propagation model includes the flight parameter of the flight device; the number of the second constraint conditions is greater than or equal to 1; Constructing a Lagrangian function according to the objective function, the first constraint condition and the second constraint condition; wherein, the Lagrangian function includes the objective function, a first Lagrangian multiplier associated with the flight parameter introduced according to the first constraint condition, and a second Lagrangian multiplier associated with the flight parameter introduced according to the second constraint condition; the number of the multipliers of the second Lagrangian is greater than or equal to 1; Solving the target value of the flight parameter of the flight device by using the Lagrangian function.

3. The method according to claim 2, wherein The solving the target value of the flight parameter of the flight device by using the Lagrangian function includes: Solving the partial derivatives of the flight parameter, the partial derivative of the first Lagrangian multiplier and the partial derivative of the second Lagrangian multiplier included in the Lagrangian function; Solving the extreme value of the flight parameter by respectively setting the partial derivatives of the flight parameter, the partial derivative of the first Lagrangian multiplier and the partial derivative of the second Lagrangian multiplier to zero; Determining the solved extreme value of the flight parameter as the target value of the flight parameter of the flight device.

4. The method according to claim 3, characterized in that The method further includes: Substituting the solved extreme value of the flight parameter into the coverage radius model to obtain the maximum coverage radius during the flight of the aerial base station.

5. The method according to any one of claims 1 to 4, characterized in that Before the determining the target value of the flight parameter of the flight device by using the link propagation loss model and the coverage radius model, the method further includes: Constructing a line-of-sight path loss model between the aerial base station and the terminal by using the distance value between the aerial base station and the terminal, the carrier frequency of the aerial base station, and the additional loss of line-of-sight transmission corresponding to the current flight environment; Constructing a non-line-of-sight path loss model between the aerial base station and the terminal by using the distance value between the aerial base station and the terminal, the carrier frequency of the aerial base station, and the additional loss of non-line-of-sight transmission corresponding to the current flight environment; Construct a first probability model corresponding to the line-of-sight path loss by using the current flight environment and the elevation angle of the terminal relative to the aerial base station, and determine a second probability model corresponding to the non-line-of-sight path loss according to the first probability model; Construct a link propagation loss model between the aerial base station and the terminal by using the line-of-sight path loss model, the first probability model, the non-line-of-sight path loss model, and the second probability model.

6. The method according to any one of claims 1 to 4, characterized in that, Before determining the target value of the flight parameters of the flying device by using the link propagation loss model and the coverage radius model, the method further includes: Construct a coverage radius model of the signal coverage area during the flight of the aerial base station by using the flight parameters of the flying device; Wherein, the flying device hovers in the air with a set center and flight radius, and the flight parameters at least include one of the following: flight altitude, flight radius, roll angle, and the planar installation angle between the installed antenna and the flying device.

7. The method according to any one of claims 1 to 4, characterized in that The method further includes: Hover in the target area according to the target value of the flight parameters.

8. A device for determining flight parameters, characterized in that, The device includes: A determination unit, configured to determine the target value of the flight parameters of the flying device by using the link propagation loss model and the coverage radius model; Wherein, the flying device is equipped with an aerial base station, the link propagation loss model and the coverage radius model are models associated with the flight parameters, the link propagation loss model is a model characterizing the signal propagation loss between the aerial base station and the terminal; the coverage radius model is a model characterizing the signal coverage area during the flight of the flying device equipped with the aerial base station.

9. An electronic device, characterized in that, The electronic device includes: a memory and a processor, and a computer-executable instruction is stored on the memory, and when the processor runs the computer-executable instruction on the memory, the method according to any one of claims 1 to 7 can be implemented.

10. A computer storage medium, characterized in that, An executable instruction is stored on the storage medium, and when the executable instruction is executed by a processor, the method according to any one of claims 1 to 7 is implemented.

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