Unmanned aerial vehicle air avoidance method and apparatus, unmanned aerial vehicle

Abstract

The application discloses an unmanned aerial vehicle air avoidance method and device and an unmanned aerial vehicle. The method comprises the following steps: a first aerial vehicle acquires wireless signal quality information in a target airspace, and determines a target sensing mode from multiple sensing modes for sensing unmanned aerial vehicles in the target airspace according to the wireless signal quality; the first aerial vehicle detects unmanned aerial vehicles in the target airspace according to the target sensing mode, and acquires flight information of the detected target aerial vehicles, wherein the flight information is used at least for indicating the distance between the first aerial vehicle and the target aerial vehicle; the first aerial vehicle determines an avoidance strategy according to the flight information, and avoids the target aerial vehicle according to the avoidance strategy. The application solves the technical problem of low wall barrier capability caused by difficult sensing of unmanned aerial vehicles in the related art.

Description

Technical Field

[0001] This application relates to the field of unmanned aerial vehicle (UAV) technology, and more specifically, to a method and apparatus for UAV aerial obstacle avoidance, and an UAV. Background Technology

[0002] Currently, with the development of the low-altitude economy and 5G airspace private networks, more and more drones are equipped with 5G communication modules, enabling 5G-based remote drone control, high-definition video transmission, and edge computing services. However, as the density of drones in low-altitude airspace increases, drone flight safety is receiving increasing attention, especially for small and micro drones. Due to limitations in payload and cost, they tend to rely on existing airborne equipment for flight perception and obstacle avoidance. Meanwhile, the industry's management and safe flight of 5G drones depend on platforms, but data from different drone management platforms is not interconnected, creating data silos. Current research is largely based on low-altitude intelligent network scenarios where radar-based perception and machine vision are not applicable to civil aviation aircraft.

[0003] There is currently no effective solution to the above problems. Summary of the Invention

[0004] This application provides an aerial obstacle avoidance method and apparatus for unmanned aerial vehicles (UAVs), and an UAV, to at least solve the technical problem of low obstacle avoidance capability caused by the difficulty of UAV perception in related technologies.

[0005] According to one aspect of the embodiments of this application, an aerial avoidance method for unmanned aerial vehicles (UAVs) is provided, comprising: a first UAV acquiring wireless signal quality information within a target airspace, and determining a target perception method from a variety of perception methods for sensing UAVs within the target airspace based on the wireless signal quality; the first UAV detecting UAVs within the target airspace according to the target perception method, and acquiring flight information of the detected target UAVs, wherein the flight information is at least used to indicate the distance between the first UAV and the target UAV; the first UAV determining an avoidance strategy based on the flight information, and avoiding the target UAV according to the avoidance strategy.

[0006] Optionally, the first aircraft acquires wireless signal quality information within the target airspace and determines the target sensing method from multiple sensing methods for sensing unmanned aerial vehicles (UAVs) within the target airspace based on the wireless signal quality. This includes: the first aircraft acquiring a Channel Quality Indicator (CQI) value and using the CQI value as wireless signal quality information; the first aircraft determining the target sensing method as a first sensing method when the CQI value is greater than a preset threshold; and the first aircraft determining the target sensing method as a second sensing method when the CQI value is less than the preset threshold. The first sensing method involves acquiring UAVs within the target airspace through a target base station, while the second sensing method involves the first aircraft sensing UAVs within the target airspace independently. The target base station is a base station covering the target airspace.

[0007] Optionally, the first aircraft detects unmanned aerial vehicles (UAVs) in the target airspace according to a target perception method and obtains the flight information of the detected target UAVs, including: when the target perception method is a first perception method, the first aircraft obtains a list of UAVs to be matched sent by the target base station, the list of UAVs to be matched contains multiple UAVs sensed by the target base station and the target distance between the first aircraft and multiple UAVs sensed by the target base station; the first aircraft selects the UAV with the closest target distance from the multiple UAVs sensed by the target base station and determines it as the target UAV.

[0008] Optionally, if the CQI value is less than a preset threshold, the first aircraft determines the target perception mode as the second perception mode, including: the first aircraft transmitting a connection signal into the target airspace when the target perception mode is the second perception mode; the first aircraft determining the connection signal power between the first aircraft and multiple unmanned aerial vehicles in the target airspace; and the first aircraft selecting the unmanned aerial vehicle with the largest connection signal power from the multiple unmanned aerial vehicles as the target aircraft.

[0009] Optionally, after determining the target aircraft, the method further includes: the first aircraft acquiring flight information of the target aircraft, the flight information including at least: the target aircraft's position, speed, heading, and flight mode, the flight mode including at least: fixed-path flight and free flight; the first aircraft determining a collision assessment model between the first aircraft and the target aircraft based on the flight information; and the first aircraft determining an avoidance strategy based on the collision assessment model.

[0010] Optionally, the first aircraft determines a collision assessment model between itself and the target aircraft based on flight information, including: when the first aircraft's flight mode is fixed-path flight, determining that the collision assessment model of the first aircraft is a cuboid of a preset size, and the cuboid of the preset size flies in a first preset direction at a first preset speed; when the first aircraft's flight mode is free flight, determining that the collision assessment model of the first aircraft is a sphere of a preset radius, and the sphere of the preset radius flies in multiple directions within the target airspace at a second preset speed.

[0011] Optionally, the first aircraft determines an avoidance strategy based on a collision assessment model, including: when both the first aircraft and the target aircraft are flying on fixed routes, the first aircraft determines the altitude difference between the first aircraft and the target aircraft; if the altitude difference is greater than a preset altitude value, the first aircraft does not need to avoid the target aircraft; if the altitude difference is less than the preset altitude value, the first aircraft determines the earliest collision time between the first aircraft and the target aircraft based on the coordinates and speed of the target aircraft, and determines an avoidance strategy based on the earliest collision time.

[0012] Optionally, the earliest collision time between the first aircraft and the target aircraft is determined based on the coordinates and velocity of the target aircraft, and an avoidance strategy is determined based on the earliest collision time, including: the first aircraft establishing a reference coordinate system with the center coordinates of the collision assessment model corresponding to the first aircraft as the origin of the coordinate system; the first aircraft determining the coordinates of the four vertices of the collision assessment model corresponding to the target aircraft in the reference coordinate system; the first aircraft setting its relative velocity to zero and determining the relative velocity of the target aircraft based on the velocity of the first aircraft and the velocity of the target aircraft; the first aircraft determining four target straight lines based on the relative velocity of the target aircraft and the coordinates of the four vertices of the collision assessment model corresponding to the target aircraft in the reference coordinate system; the first aircraft determining the intersection points of the four target straight lines and the collision assessment model corresponding to the first aircraft, and determining the earliest collision time based on the intersection points; and the first aircraft determining the avoidance strategy as adjusting the flight altitude of the first aircraft at the earliest collision time.

[0013] Optionally, the first aircraft determines an avoidance strategy based on a collision assessment model, including: when the first aircraft's flight mode is free flight and the target aircraft's flight mode is fixed-path flight, determining the distance from the center of the collision assessment model corresponding to the first aircraft to the target aircraft; and when the distance from the center of the collision assessment model corresponding to the first aircraft to the target aircraft is less than a preset distance threshold, determining the avoidance strategy as the first aircraft accelerating towards the direction of the fixed-path normal.

[0014] Optionally, the method further includes: when both the first aircraft and the target aircraft are in free flight mode, the first aircraft determines a safe distance based on a preset altitude value; when the safe distance is less than a preset safe distance threshold, the first aircraft determines an avoidance strategy of accelerating towards the target direction, where the target direction is the direction connecting the centers of the circles in the collision assessment models corresponding to the first aircraft and the target aircraft.

[0015] According to another aspect of the embodiments of this application, an unmanned aerial vehicle (UAV) airborne avoidance device is also provided, comprising: a first acquisition module, configured to acquire wireless signal quality information within a target airspace, and determine a target perception method from a variety of perception methods for sensing UAVs within the target airspace based on the wireless signal quality; a second acquisition module, configured to detect UAVs within the target airspace according to the target perception method, and acquire flight information of the detected target UAVs, wherein the flight information is at least used to indicate the distance between the first UAV and the target UAV; and an avoidance module, configured to determine an avoidance strategy based on the flight information, and avoid the target UAV according to the avoidance strategy.

[0016] According to another aspect of the embodiments of this application, an unmanned aerial vehicle (UAV) is also provided, comprising: a memory for storing program instructions; and a processor connected to the memory for executing the program instructions for performing the following functions: acquiring wireless signal quality information within a target airspace, and determining a target sensing method from a variety of sensing methods for sensing UAVs within the target airspace based on the wireless signal quality; detecting UAVs within the target airspace according to the target sensing method, and acquiring flight information of the detected target UAVs, wherein the flight information is at least used to indicate the distance between a first UAV and the target UAV; determining an avoidance strategy based on the flight information, and avoiding the target UAV according to the avoidance strategy.

[0017] According to another aspect of the embodiments of this application, a non-volatile storage medium is also provided, the non-volatile storage medium including a stored computer program, wherein the device containing the non-volatile storage medium executes the above-described unmanned aerial vehicle aerial avoidance method by running the computer program.

[0018] In this embodiment, a first aircraft acquires wireless signal quality information within the target airspace and determines a target sensing method from multiple sensing methods for sensing unmanned aerial vehicles (UAVs) within the target airspace based on the wireless signal quality. The first aircraft detects UAVs within the target airspace according to the target sensing method and acquires flight information of the detected target UAVs. The flight information is used to at least indicate the distance between the first aircraft and the target UAVs. The first aircraft determines an avoidance strategy based on the flight information and avoids the target UAVs according to the avoidance strategy. By determining the target sensing method from multiple sensing methods for sensing UAVs within the target airspace based on the wireless signal quality, the perception capability of the UAVs within the target airspace is enhanced, thereby achieving the technical effect of improving the obstacle avoidance capability of the UAVs and solving the technical problem of low obstacle avoidance capability caused by the difficulty of UAV perception in related technologies. Attached Figure Description

[0019] The accompanying drawings, which are included to provide a further understanding of this application and form part of this application, illustrate exemplary embodiments of this application and are used to explain this application, but do not constitute an undue limitation of this application. In the drawings:

[0020] Figure 1 This is a hardware structure block diagram of a computer terminal for implementing an aerial avoidance method for unmanned aerial vehicles according to an embodiment of this application.

[0021] Figure 2 This is a flowchart of an aerial avoidance method for unmanned aerial vehicles according to an embodiment of this application;

[0022] Figure 3 This is a schematic diagram of an optional unmanned aerial vehicle signal transmission pairing process according to an embodiment of this application;

[0023] Figure 4 This is a schematic diagram of another optional aerial avoidance method for unmanned aerial vehicles according to an embodiment of this application;

[0024] Figure 5 This is a schematic flowchart of an optional unmanned aerial vehicle perception method according to an embodiment of this application;

[0025] Figure 6 This is a schematic flowchart of another optional unmanned aerial vehicle obstacle avoidance method according to an embodiment of this application;

[0026] Figure 7 This is a structural diagram of an aerial avoidance device for unmanned aerial vehicles according to an embodiment of this application. Detailed Implementation

[0027] To enable those skilled in the art to better understand the present application, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present application, and not all embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of the present application.

[0028] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this application are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of this application described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0029] In related technologies, current research is mostly based on radar-based perception and machine vision for civil aircraft, which have low perception capabilities and are not suitable for low-altitude intelligent network scenarios. To address these issues and improve the obstacle avoidance capabilities of unmanned aerial vehicles (UAVs), this application provides an aerial obstacle avoidance method for UAVs. This method can operate in… Figure 1 The computer terminal shown is described in detail below.

[0030] The vehicle hub quality inspection method provided in this application can be executed on a mobile terminal, computer terminal, or similar computing device. Figure 1 A hardware block diagram of a computer terminal for implementing an aerial obstacle avoidance method for unmanned aerial vehicles is shown. Figure 1 As shown, the computer terminal 10 may include one or more processors (shown as 102a, 102b, ..., 102n in the figure) (the processor may include, but is not limited to, a microprocessor MCU or a programmable logic device FPGA, etc.), a memory 104 for storing data, and a transmission module 106 for communication functions. In addition, it may also include: a display, a keyboard, a cursor control device, an input / output interface (I / O interface), a universal serial bus (USB) port (which may be included as one of the ports of the I / O interface), a network interface, and a BUS bus. Those skilled in the art will understand that... Figure 1 The structure shown is for illustrative purposes only and does not limit the structure of the aforementioned electronic device. For example, computer terminal 10 may also include... Figure 1 The more or fewer components shown, or having the same Figure 1 The different configurations shown.

[0031] It should be noted that the aforementioned one or more processors and / or other data processing circuits are generally referred to herein as "data processing circuits". These data processing circuits may be implemented wholly or partially as software, hardware, firmware, or any other combination thereof. Furthermore, the data processing circuits may be a single, independent processing module, or may be wholly or partially integrated into any other element in the computer terminal 10. As involved in the embodiments of this application, the data processing circuits serve as processor control (e.g., selection of a variable resistor termination path connected to an interface).

[0032] The memory 104 can be used to store software programs and modules of application software, such as the program instruction / data storage device corresponding to the unmanned aerial vehicle (UAV) air avoidance method in this embodiment. The processor executes various functional applications and data processing by running the software programs and modules stored in the memory 104, thereby realizing the aforementioned UAV air avoidance method. The memory 104 may include high-speed random access memory (RAM) and non-volatile memory, such as one or more magnetic storage devices, flash memory, or other non-volatile solid-state memory. In some instances, the memory 104 may further include memory remotely located relative to the processor, which can be connected to the computer terminal 10 via a network. Examples of such networks include, but are not limited to, the Internet, corporate intranets, local area networks (LANs), mobile communication networks, and combinations thereof.

[0033] The transmission module 106 is used to receive or send data via a network. Specific examples of the network described above may include a wireless network provided by the communication provider of the computer terminal 10. In one example, the transmission module 106 includes a Network Interface Controller (NIC), which can connect to other network devices via a base station to communicate with the Internet. In another example, the transmission module 106 may be a Radio Frequency (RF) module, used for wireless communication with the Internet.

[0034] The display may be, for example, a touchscreen liquid crystal display (LCD) that allows the user to interact with the user interface of the computer terminal 10.

[0035] It should be noted here that, in some optional embodiments, the above... Figure 1The computer device shown may include hardware elements (including circuitry), software elements (including computer code stored on a computer-readable medium), or a combination of both hardware and software elements. It should be noted that... Figure 1 This is only one instance of a specific particular instance, and is intended to illustrate the types of components that may exist in the aforementioned computer devices.

[0036] Under the above operating environment, this application provides an embodiment of an aerial avoidance method for unmanned aerial vehicles. It should be noted that the steps shown in the flowchart in the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions. Furthermore, although a logical order is shown in the flowchart, in some cases, the steps shown or described may be executed in a different order than that shown here.

[0037] Figure 2 This is a flowchart of an aerial obstacle avoidance method for an unmanned aerial vehicle according to an embodiment of this application, such as... Figure 2 As shown, the method includes the following steps:

[0038] Step S202: The first aircraft acquires wireless signal quality information within the target airspace and determines the target sensing method from multiple sensing methods used to sense unmanned aerial vehicles within the target airspace based on the wireless signal quality.

[0039] Step S204: The first aircraft detects unmanned aerial vehicles in the target airspace according to the target perception method, and obtains the flight information of the detected target aircraft. The flight information is used to indicate at least the distance between the first aircraft and the target aircraft.

[0040] In step S206, the first aircraft determines an avoidance strategy based on the flight information and avoids the target aircraft according to the avoidance strategy.

[0041] In steps S202 to S206 above, the executing entity is the first aircraft. In actual application scenarios, the first aircraft can be a locally controlled aircraft.

[0042] It's important to note that current 5G drone control and management methods involve installing 5G modules to upload flight information to a server via base stations, enabling SaaS (Software as a Service) management. However, each drone is an independent entity, with no information exchange between them. Information flow through a platform presents challenges in real-time performance and compatibility. Therefore, multiple drones flying in adjacent airspace pose safety risks. For example, in the airspace available to civil aircraft, a minimum distance of 300 meters must be maintained between aircraft to ensure flight safety, and takeoffs and landings are subject to air traffic control and must be conducted in an orderly manner. Similarly, in the low-altitude airspace below 300 meters, airspace resources are even more strained, and drone flight paths are more unpredictable and chaotic compared to civil aircraft. With the increase in low-altitude aircraft, the probability of collisions will increase rapidly. Therefore, both "sensing" and "avoidance" mechanisms are needed to ensure the flight safety of low-altitude drones.

[0043] Understandably, civilian aircraft typically use weather radar and airborne radar to sense their surroundings. Airborne radar detects objects by emitting electromagnetic waves and measuring the time and intensity of their reflection. Different types of airborne radar have different detection ranges and resolutions, providing the crew with varying levels of object detection and tracking capabilities. Large drones and civilian aircraft also employ advanced LiDAR (Light Detection and Ranging) technology. LiDAR detects objects by outputting light signals and measuring the time and intensity of their reflection, offering advantages such as high precision, high resolution, and long detection range. However, the high cost and weight of LiDAR make it unsuitable for small drones.

[0044] For small drones, sensor configuration needs to be limited by the drone's appearance, payload capacity, power consumption, and battery life. While considering the drone's payload capacity and dynamic characteristics, the system resources occupied by various sensors should be minimized. Therefore, drones rely more on cameras and computer vision technology for target perception. Specifically, in applications that perceive surrounding drones, cameras capture visual information from them, computer vision algorithms convert this information into digital signals, and the main controller on the drone enables autonomous navigation and obstacle avoidance. However, target recognition is easily affected by weather factors such as strong light, fog, and rain. In summary, small drones face the following problems in perception: vision-based perception and obstacle avoidance depend on visibility and algorithm accuracy, and blind spots exist; small drones cannot carry radar or other modules, lacking effective supplementary perception methods; drone cloud platform data is isolated, preventing communication between drones on different platforms and posing a collision risk; adding dedicated location sensing stations such as UWB is costly, difficult to select, and requires modification of existing drones, making implementation challenging.

[0045] The unmanned aerial vehicle (UAV) obstacle avoidance method described in steps S202 to S206 involves a first UAV acquiring wireless signal quality information within the target airspace and determining a target perception method from multiple perception methods for detecting UAVs within the target airspace based on the wireless signal quality. The first UAV detects UAVs within the target airspace according to the target perception method and acquires flight information of the detected target UAVs. This flight information at least indicates the distance between the first UAV and the target UAV. The first UAV determines an avoidance strategy based on the flight information and avoids the target UAV according to the avoidance strategy. By determining the target perception method from multiple perception methods for detecting UAVs within the target airspace based on wireless signal quality, the method aims to enhance the UAV's perception capability, thereby improving its obstacle avoidance capability and solving the technical problem of low obstacle avoidance capability caused by difficult UAV perception in related technologies. The following is a detailed explanation.

[0046] In step S202 of the above-mentioned unmanned aerial vehicle (UAV) airborne avoidance method, wireless signal quality information within the target airspace is acquired, and the target perception method is determined from multiple perception methods for sensing UAVs within the target airspace based on the wireless signal quality. Specifically, this includes the following steps: the first UAV acquires a Channel Quality Indication (CQI) value and uses the CQI value as wireless signal quality information; if the CQI value is greater than a preset threshold, the first UAV determines the target perception method as the first perception method; if the CQI value is less than the preset threshold, the first UAV determines the target perception method as the second perception method. The first perception method involves acquiring UAVs within the target airspace through a target base station, while the second perception method involves the first UAV sensing UAVs within the target airspace independently. The target base station is a base station covering the target airspace.

[0047] In practical applications, the first sensing method involves two approaches: one is a base station-controlled D2D (Device-to-Device) communication mechanism for discovering and pairing users, and the other is a terminal-initiated D2D communication mechanism for discovering and pairing users by actively sending probing signals. 5G drones (drones equipped with 5G communication modules) commonly use the base station-controlled D2D approach. When a terminal sends a D2D communication request, the network reserves D2D communication resources for the user. Upon receiving a request from a device, the base station sends scheduling signals to other devices that meet the pairing criteria, while simultaneously providing feedback to the requesting device to assist in discovering potential pairing targets in the vicinity. Next, devices with D2D communication needs attempt to pair with various potential targets, and then select the optimal partner based on the communication link status and the working status of the other device to complete the D2D user pairing. Under the control and scheduling of the base station, devices can avoid unnecessary energy consumption when detecting potential pairing targets, improving device discovery efficiency and accelerating the D2D user pairing process. The pairing process is as follows: Figure 3 As shown. Using this mechanism, mutual perception and low-level communication between drones based on 5G can be achieved without adding additional equipment. After the connection is established, both parties will actively send key flight path data such as position, altitude, speed, heading, and flight mode.

[0048] Figure 4 An alternative method for unmanned aerial vehicles to avoid obstacles in mid-air is shown, such as... Figure 4 As shown, the first step involves pattern determination. Based on the wireless signal quality, a sensing method is selected for device pairing. After successful pairing, basic flight information is transmitted. The second step involves assessing the collision risk based on the different flight conditions of both devices. If a collision risk is detected, a safe flight route will be replanned to avoid the collision. Throughout the flight, sensing will be continuously performed, constantly detecting other potential unmanned aerial vehicles.

[0049] In some embodiments of this application, when the target perception method is a first perception method, the first aircraft obtains a list of unmanned aerial vehicles (UAVs) to be matched sent by the target base station. The list includes multiple UAVs sensed by the target base station and the target distances between the first aircraft and the multiple UAVs sensed by the target base station. The first aircraft selects the UAV with the closest target distance from the multiple UAVs and determines it as the target aircraft. It is understood that the method proposed in this application is applicable to UAVs equipped with wireless communication modules and using wireless communication.

[0050] It should be noted that, when the target perception mode is the second perception mode, the first aircraft transmits a connection signal into the target airspace; the first aircraft determines the connection signal power between the first aircraft and multiple unmanned aerial vehicles in the target airspace; the first aircraft selects the unmanned aerial vehicle with the largest connection signal power from among the multiple unmanned aerial vehicles and determines it as the target aircraft.

[0051] It should be further explained that, when using the second sensing method, the power of the connection signal transmitted by the first aircraft will increase as the flight speed of the first aircraft increases.

[0052] In another alternative approach, after the first aircraft establishes a connection with the detected unmanned aerial vehicle (UAV), the UAV with the best connection signal quality among the multiple UAVs that have established a connection can be selected as the target aircraft.

[0053] In practical applications, uneven signal distribution at low altitudes can easily lead to signal blind spots. Relying on a single sensing method is insufficient to cover safe flight across all scenarios. Therefore, this application integrates two sensing methods for dynamic sensing of unmanned aerial vehicles (UAVs). Signal quality is assessed before communication is established, followed by sensing operations. Simultaneously, the power output is dynamically adjusted based on speed, thereby dynamically scaling the detection range to achieve safer and more efficient detection and sensing. Figure 5As shown, the process of the first UAV establishing a connection with the target UAV and obtaining the target UAV's flight information is as follows: First, the CQI value reported by the wireless communication module of the current UAV is obtained, and a preset threshold k is set. If the CQI is greater than k, a D2D device discovery mechanism controlled by the base station is adopted (first sensing method). If the CQI is less than k, a matching mechanism actively discovered by the terminal is adopted (second sensing method). A list of devices to be matched is obtained. If it is the first sensing method, distance priority is set, and the base station selects the nearest terminal to establish a connection. If it is the second sensing method, the connection signal transmission power is dynamically adjusted according to the speed of the UAV. That is, when the aircraft is hovering, it can sense UAVs with a radius of d at the transmission power. During flight, the sensing radius r needs to be increased to vt+d, where t is the reaction time of the first UAV and v is the flight speed of the first UAV at this time. To ensure that the UAV can detect other UAVs in the vicinity in a timely manner, the transmission power must be increased to detect UAVs within a larger radius. At the moment of detection, both parties can be approximated as being in a relatively stationary state. Then, the minimum transmission power can be calculated using the spatial propagation loss model. As v increases, the sensing radius r increases. Since the remaining quantities in the spatial propagation loss model can be considered constant in the short term, the minimum transmission power will also increase until it reaches the maximum value limited by the 5G module.

[0054] In one alternative approach, the connection signal power can be determined by the following formula:

[0055] w-w0=PL' RMa-LOS

[0056] In the formula, w represents the power of the connection signal, w0 represents the transmit power of the connection signal, and PL' RMa-LOS Indicates the power loss of the connection signal;

[0057] Among them, PL' RMa-LOS It can be determined by the following formula:

[0058] PL' RMa-LOS =20lg(40πv0tf) c / 3)+min(0.03h 1.72 ,10)lgv0t-min(0.044h 1.72 ,14.77)+0.002lg(h)v0t

[0059] In the formula, v0 represents the flight speed of the first aircraft, t represents the reaction time of the first aircraft, and f c The frequency of the connection signal is represented by h, and the altitude of the first aircraft is represented by h.

[0060] After identifying the target aircraft, the first aircraft acquires the target aircraft's flight information, which includes at least the target aircraft's position, speed, heading, and flight mode. The flight mode includes at least fixed-path flight and free flight. Based on the flight information, the first aircraft determines a collision assessment model between itself and the target aircraft. The first aircraft then determines an avoidance strategy based on the collision assessment model.

[0061] An optional method for creating a collision assessment model is as follows: when the aircraft's flight mode is fixed-path flight, the collision assessment model of the aircraft is determined to be a cuboid of a preset size, and the cuboid of the preset size flies in a first preset direction at a first preset speed; when the aircraft's flight mode is free flight, the collision assessment model of the aircraft is determined to be a sphere of a preset radius, and the sphere of the preset radius flies in multiple directions within the target airspace at a second preset speed.

[0062] It should be noted that there are four flight modes for both the first aircraft and the target aircraft: fixed flight path (first aircraft) and free flight (target aircraft). Both free flight (first aircraft) and fixed flight path (target aircraft) are either free flight or fixed flight path.

[0063] In fixed-route flight mode, the collision assessment model for the unmanned aerial vehicle has length, width, and height λ respectively. x , λ y and λ z If the cuboid is a fixed-path flight model, it can be abstracted as the cuboid flying along vector A(x1,y1,z1) at a fixed speed v1 (first preset speed) per unit time.

[0064] In free flight mode, the collision assessment model corresponding to the unmanned aerial vehicle flies randomly in all directions of space at a speed of v2 (the second preset speed), and the speed follows [v 2min ,v 2max The distribution is uniform, but it can be considered as linear motion in the short term, and can be abstractly constructed as a radius of λ² = max{λ 2x ,λ 2y ,λ 2z} is a spherical shape, where v 2min Let v represent the minimum speed of v2. 2max λ represents the maximum speed of v2. 2x λ represents the length of the unmanned aerial vehicle. 2y λ represents the width of the unmanned aerial vehicle. 2z This indicates the altitude of the unmanned aerial vehicle.

[0065] The first aircraft determines its avoidance strategy based on the collision assessment model as follows: Firstly, assuming both the first and target aircraft are flying on fixed routes, the first aircraft determines the altitude difference between them. If the altitude difference is greater than a preset altitude value, the first aircraft does not need to avoid the target aircraft. If the altitude difference is less than the preset altitude value, the first aircraft determines the earliest collision time based on the target aircraft's coordinates and speed, and then determines the avoidance strategy based on that earliest collision time. The first aircraft establishes a reference coordinate system with the center coordinates of its corresponding collision assessment model as the origin. The system consists of: a reference coordinate system; the first aircraft determining the coordinates of the four vertices of the collision assessment model corresponding to the target aircraft in the reference coordinate system; the first aircraft setting its relative velocity to zero and determining the relative velocity of the target aircraft based on its own velocity and the target aircraft's velocity; the first aircraft determining four target straight lines based on the target aircraft's relative velocity and the coordinates of the four vertices of the collision assessment model corresponding to the target aircraft in the reference coordinate system; the first aircraft determining the intersection points of the four target straight lines with the collision assessment model corresponding to its own aircraft and determining the earliest collision time based on the intersection points; and the first aircraft determining its avoidance strategy as adjusting its flight altitude at the earliest collision time.

[0066] The second method involves determining the distance from the center of the collision assessment model corresponding to the first aircraft to the target aircraft when the first aircraft is in free flight mode and the target aircraft is in fixed flight mode. If the distance from the center of the collision assessment model corresponding to the first aircraft to the target aircraft is less than a preset distance threshold, the avoidance strategy is to accelerate the first aircraft in the direction of the fixed flight path normal.

[0067] The third method involves determining a safe distance based on a preset altitude value when both the first and target aircraft are in free flight mode. If the safe distance is less than a preset safe distance threshold, the first aircraft determines an avoidance strategy whereby both the first and target aircraft accelerate towards the target direction, which is the direction connecting the centers of the corresponding collision assessment models of the first and target aircraft.

[0068] Specifically, such as Figure 6 As shown, when the first aircraft and the target aircraft are on a fixed flight path and in a fixed flight path mode, since the UAV usually travels at a fixed altitude and at a constant speed in the fixed flight path mode, the first step is to determine whether the altitude difference meets the requirements. The determination method is shown in the following formula:

[0069]

[0070] In the formula, hdiff λ represents the altitude difference between the collision assessment model corresponding to the first aircraft and the collision assessment model corresponding to the target aircraft, h2 represents the flight altitude of the target aircraft, h1 represents the flight altitude of the first aircraft, and λ represents the altitude difference between the collision assessment model corresponding to the first aircraft and the collision assessment model corresponding to the target aircraft. z1 λ represents the altitude of the collision assessment model corresponding to the first aircraft. z2 The altitude of the collision assessment model corresponding to the target aircraft is represented by Δd, which represents the preset distance value.

[0071] Understandably, the preset height value is equal to

[0072] If the altitude difference between the first aircraft and the target aircraft does not meet the above conditions, the speed of the first aircraft is taken as... The target aircraft's speed is For example, if a reference coordinate system is established with the first aircraft as the origin, then the coordinates of the first aircraft in the reference coordinate system are (0, 0), and its velocity is 0. The velocity of the target aircraft is... If the center coordinates of the collision model corresponding to the target aircraft are (x1, y1), then the coordinates of the four vertices of the collision model corresponding to the target aircraft are:

[0073]

[0074]

[0075]

[0076]

[0077] Combined velocity vector By using the coordinates of four peer drones, four straight line equations can be constructed. The existence of an intersection point between each of these straight line equations and the rectangle constructed by the local drone is then calculated. If an intersection point exists, the earliest collision time is calculated. If the time is within a threshold, a collision is prioritized or the altitude is adjusted to avoid collision.

[0078] When the first aircraft is in free flight mode and the target aircraft is in fixed flight mode, a reference coordinate system is constructed with the local end as the center of the collision evaluation model corresponding to the first aircraft. The collision evaluation model corresponding to the first aircraft is converted into a sphere with a radius of λ2+Δd. The distance D from the center of the collision evaluation model corresponding to the first aircraft to the fixed flight path should satisfy the following condition:

[0079] D<λ2+Δd+max{λ 1x ,λ 1y ,λ 1z}+(v1+v2)t

[0080] In the formula, λ 1xλ represents the length of the target aircraft. 1y λ represents the width of the target aircraft. 1z The altitude of the target aircraft.

[0081] If the distance D from the center of the collision assessment model corresponding to the first aircraft to the fixed flight path does not meet the above conditions, the first aircraft will accelerate away in the direction of the normal corresponding to the heading of the target aircraft.

[0082] When the first aircraft is in fixed-course flight mode and the target aircraft is in free flight mode, the method for determining the avoidance strategy is similar to the above method, and the party that initiates the communication connection avoids the target aircraft according to the above avoidance strategy.

[0083] When both the first aircraft and the target aircraft are in free flight mode, the distance M between them should satisfy the following formula:

[0084] M≥λ²+2Δd+λ²′

[0085] In the formula, λ2′ represents the radius of the collision assessment model corresponding to the target aircraft.

[0086] If M is less than the distance mentioned above, both parties will receive a prompt to accelerate away in the direction where the centers of the circles are connected.

[0087] Figure 7 This is a structural diagram of an unmanned aerial vehicle (UAV) aerial avoidance device according to an embodiment of this application, as shown below. Figure 7 As shown, the device includes:

[0088] The first acquisition module 70 is used to acquire wireless signal quality information in the target airspace and determine the target perception method from a variety of perception methods used to perceive unmanned aerial vehicles in the target airspace based on the wireless signal quality.

[0089] The second acquisition module 72 is used to detect unmanned aerial vehicles in the target airspace according to the target perception method, and acquire the flight information of the detected target aircraft. The flight information is used to indicate at least the distance between the first aircraft and the target aircraft.

[0090] The avoidance module 74 is used to determine the avoidance strategy based on the flight information and avoid the target aircraft according to the avoidance strategy.

[0091] The first acquisition module 70 of the aforementioned unmanned aerial vehicle (UAV) airborne avoidance device includes: a perception submodule, used for the first UAV to acquire a Channel Quality Indicator (CQI) value and use the CQI value as wireless signal quality information; when the CQI value is greater than a preset threshold, the first UAV determines the target perception mode as a first perception mode; when the CQI value is less than the preset threshold, the first UAV determines the target perception mode as a second perception mode, wherein the first perception mode acquires the UAV in the target airspace through a target base station, and the second perception mode is for the first UAV to perceive the UAV in the target airspace on its own, and the target base station is a base station covering the target airspace;

[0092] The perception submodule includes: a first determining unit and a second determining unit. The first determining unit is used to obtain a list of unmanned aerial vehicles (UAVs) to be matched sent by the target base station when the target perception mode is the first perception mode. The list of UAVs to be matched contains multiple UAVs sensed by the target base station and the target distance between the first aircraft and the multiple UAVs sensed by the target base station. The first aircraft selects the UAV with the closest target distance from the multiple UAVs and determines it as the target aircraft.

[0093] The second determining unit is configured to: transmit a connection signal into the target airspace when the first aircraft is using the second target perception mode; determine the connection signal power between the first aircraft and multiple unmanned aerial vehicles (UAVs) in the target airspace; and select the UAV with the highest connection signal power from among the multiple UAVs as the target aircraft.

[0094] The perception submodule also includes: a third determining unit, used by the first aircraft to acquire flight information of the target aircraft, the flight information including at least: the target aircraft's position, speed, heading and flight mode, the flight mode including at least: fixed route flight and free flight; the first aircraft determines a collision assessment model between the first aircraft and the target aircraft based on the flight information; the first aircraft determines an avoidance strategy based on the collision assessment model;

[0095] The third determining unit includes: a first determining subunit, a second determining subunit, and a third determining subunit. The first determining subunit is used to determine the collision evaluation model of the first aircraft as a cuboid of a preset size when the aircraft's flight mode is fixed-path flight, and the cuboid of the preset size flies in a first preset direction at a first preset speed; and to determine the collision evaluation model of the first aircraft as a sphere of a preset radius when the aircraft's flight mode is free flight, and the sphere of the preset radius flies in multiple directions within the target airspace at a second preset speed.

[0096] The second determining subunit is used to determine the altitude difference between the first aircraft and the target aircraft when both the first aircraft and the target aircraft are flying in fixed flight modes; if the altitude difference is greater than a preset altitude value, the first aircraft does not need to avoid the target aircraft; if the altitude difference is less than the preset altitude value, the first aircraft determines the earliest collision time between the first aircraft and the target aircraft based on the coordinates and speed of the target aircraft, and determines an avoidance strategy based on the earliest collision time.

[0097] The third determining subunit is used for the first aircraft to establish a reference coordinate system with the center coordinates of the collision assessment model corresponding to the first aircraft as the origin of the coordinate system; the first aircraft determines the coordinates of the four vertices of the collision assessment model corresponding to the target aircraft in the reference coordinate system; the first aircraft determines the relative velocity of the first aircraft as zero, and determines the relative velocity of the target aircraft based on the velocity of the first aircraft and the velocity of the target aircraft; the first aircraft determines four target straight lines based on the relative velocity of the target aircraft and the coordinates of the four vertices of the collision assessment model corresponding to the target aircraft in the reference coordinate system; the first aircraft determines the intersection points of the four target straight lines and the collision assessment model corresponding to the first aircraft, and determines the earliest collision time based on the intersection points; the first aircraft determines the avoidance strategy as adjusting the flight altitude of the first aircraft at the earliest collision time.

[0098] The aforementioned unmanned aerial vehicle (UAV) aerial avoidance device further includes: a fourth determining subunit and a fifth determining subunit. The fourth subunit is used to determine the distance from the center of the collision assessment model corresponding to the first UAV to the target UAV when the first UAV's flight mode is free flight and the target UAV's flight mode is fixed flight. When the distance from the center of the collision assessment model corresponding to the first UAV to the target UAV is less than a preset distance threshold, the first UAV determines the avoidance strategy as accelerating towards the direction of the fixed flight path normal.

[0099] The fifth determining subunit is used to determine a safe distance based on a preset altitude value when both the first aircraft and the target aircraft are in free flight mode; when the safe distance is less than a preset safe distance threshold, the first aircraft determines an avoidance strategy of accelerating towards the target direction, where the target direction is the direction connecting the centers of the circles in the collision assessment models corresponding to the first aircraft and the target aircraft.

[0100] It should be noted that, Figure 7 The unmanned aerial vehicle (UAV) aerial avoidance device shown is used to perform Figure 2 The above-described method for aerial avoidance of unmanned aerial vehicles (UAVs) also applies to this type of UAV aerial avoidance device, and will not be repeated here.

[0101] This application also provides an unmanned aerial vehicle (UAV), including: a memory for storing program instructions; acquiring wireless signal quality information within a target airspace, and determining a target sensing method from multiple sensing methods for sensing UAVs within the target airspace based on the wireless signal quality; detecting UAVs within the target airspace according to the target sensing method, and acquiring flight information of the detected target UAVs, wherein the flight information is at least used to indicate the distance between a first UAV and the target UAV; determining an avoidance strategy based on the flight information, and avoiding the target UAV according to the avoidance strategy.

[0102] It should be noted that the aforementioned electronic equipment is used to perform Figure 2 The above-described method for aerial obstacle avoidance by unmanned aerial vehicles also applies to this electronic device, and will not be repeated here.

[0103] This application embodiment also provides a non-volatile storage medium, which includes a stored computer program. The device containing the non-volatile storage medium executes the following file migration method by running the computer program: acquiring wireless signal quality information within a target airspace, and determining a target sensing method from multiple sensing methods for sensing unmanned aerial vehicles (UAVs) within the target airspace based on the wireless signal quality; detecting UAVs within the target airspace according to the target sensing method, and acquiring flight information of the detected target UAVs, the flight information being at least used to indicate the distance between a first UAV and the target UAV; determining an avoidance strategy based on the flight information, and avoiding the target UAV according to the avoidance strategy.

[0104] It should be noted that the aforementioned non-volatile storage media is used for execution. Figure 2 The above-described method for aerial obstacle avoidance by unmanned aerial vehicles also applies to this non-volatile storage medium, and will not be repeated here.

[0105] The sequence numbers of the embodiments in this application are for descriptive purposes only and do not represent the superiority or inferiority of the embodiments.

[0106] In the above embodiments of this application, the descriptions of each embodiment have different focuses. For parts not described in detail in a certain embodiment, please refer to the relevant descriptions of other embodiments.

[0107] In the several embodiments provided in this application, it should be understood that the disclosed technical content can be implemented in other ways. The device embodiments described above are merely illustrative; for example, the division of units can be a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the displayed or discussed mutual couplings, direct couplings, or communication connections may be through some interfaces; indirect couplings or communication connections between units or modules may be electrical or other forms.

[0108] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0109] Furthermore, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0110] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods of the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as a USB flash drive, read-only memory (ROM), random access memory (RAM), portable hard drive, magnetic disk, or optical disk.

[0111] The above are merely preferred embodiments of this application. It should be noted that those skilled in the art can make various improvements and modifications without departing from the principles of this application, and these improvements and modifications should also be considered within the scope of protection of this application.

Claims

1. A method for aerial obstacle avoidance by unmanned aerial vehicles, characterized in that, include: The first aircraft acquires wireless signal quality information within the target airspace and determines the target sensing method from multiple sensing methods used to sense unmanned aerial vehicles within the target airspace based on the wireless signal quality. The first aircraft detects unmanned aerial vehicles in the target airspace according to the target perception method, and acquires the flight information of the detected target aircraft. The flight information is used to indicate at least the distance between the first aircraft and the target aircraft. The first aircraft determines an avoidance strategy based on the flight information and avoids the target aircraft according to the avoidance strategy; After determining the target aircraft, the method further includes: the first aircraft acquiring flight information of the target aircraft, the flight information including at least: the target aircraft's position, speed, heading, and flight mode, the flight mode including at least: fixed-path flight and free flight; the first aircraft determining a collision assessment model between the first aircraft and the target aircraft based on the flight information; and the first aircraft determining the avoidance strategy according to the collision assessment model. The first aircraft acquires wireless signal quality information within the target airspace and determines a target sensing method from multiple sensing methods for sensing unmanned aerial vehicles (UAVs) within the target airspace based on the wireless signal quality. This includes: the first aircraft acquiring a Channel Quality Indicator (CQI) value and using the CQI value as the wireless signal quality information; the first aircraft determining the target sensing method as a first sensing method when the CQI value is greater than a preset threshold; and the first aircraft determining the target sensing method as a second sensing method when the CQI value is less than the preset threshold. The first sensing method involves acquiring UAVs within the target airspace through a target base station, while the second sensing method involves the first aircraft sensing UAVs within the target airspace independently. The target base station is a base station covering the target airspace. The first aircraft detects unmanned aerial vehicles (UAVs) in the target airspace according to the target perception method and obtains the flight information of the detected target UAVs, including: when the target perception method is the first perception method, the first aircraft obtains a list of UAVs to be matched sent by the target base station, the list of UAVs to be matched contains multiple UAVs sensed by the target base station and the target distance between the first aircraft and the multiple UAVs sensed by the target base station; the first aircraft selects the UAV with the closest target distance from the multiple UAVs sensed by the target base station and determines it as the target UAV.

2. The method according to claim 1, characterized in that, When the CQI value is less than the preset threshold, the first aircraft determines the target perception method to be the second perception method, including: When the target perception mode is the second perception mode, the first aircraft transmits a connection signal into the target airspace; The first aircraft determines the connection signal power between itself and multiple unmanned aerial vehicles in the target airspace; The first aircraft selects the unmanned aerial vehicle with the highest connection signal power from among the plurality of unmanned aerial vehicles and determines it as the target aircraft.

3. The method according to claim 1, characterized in that, The first aircraft determines a collision assessment model between itself and the target aircraft based on the flight information, including: When the first aircraft is flying in a fixed flight path mode, the collision assessment model of the aircraft is determined to be a cuboid of a preset size, and the cuboid of the preset size flies in a first preset direction at a first preset speed. When the first aircraft is in free flight mode, the collision assessment model of the aircraft is determined to be a sphere with a preset radius, and the sphere with the preset radius flies in multiple directions within the target airspace at a second preset speed.

4. The method according to claim 3, characterized in that, The first aircraft determines the avoidance strategy based on the collision assessment model, including: When both the first aircraft and the target aircraft are flying on fixed routes, the altitude difference between the first aircraft and the target aircraft is determined. If the altitude difference is greater than a preset altitude value, the first aircraft does not need to avoid the target aircraft; When the altitude difference is less than the preset altitude value, the first aircraft determines the earliest collision time between the first aircraft and the target aircraft based on the coordinates and speed of the target aircraft, and determines the avoidance strategy based on the earliest collision time.

5. The method according to claim 4, characterized in that, Based on the coordinates and velocity of the target aircraft, the earliest collision time between the first aircraft and the target aircraft is determined, and the avoidance strategy is determined according to the earliest collision time, including: The first aircraft establishes a reference coordinate system with the center coordinates of the collision assessment model corresponding to the first aircraft as the origin of the coordinate system; The first aircraft determines the coordinates of the four vertices of the collision assessment model corresponding to the target aircraft in the reference coordinate system; The first aircraft sets its relative velocity to zero and determines the relative velocity of the target aircraft based on the velocity of the first aircraft and the velocity of the target aircraft. The first aircraft determines four target straight lines based on the relative velocity of the target aircraft and the coordinates of the four vertices of the collision evaluation model corresponding to the target aircraft in the reference coordinate system. The first aircraft determines the intersection points of the four target straight lines with the collision assessment model corresponding to the first aircraft, and determines the earliest collision time based on the intersection points; The first aircraft determines that the avoidance strategy is to adjust the flight altitude of the first aircraft at the earliest collision time.

6. The method according to claim 4, characterized in that, The first aircraft determines the avoidance strategy based on the collision assessment model, including: When the first aircraft is in free flight mode and the target aircraft is in fixed flight mode, the distance from the center of the collision assessment model corresponding to the first aircraft to the target aircraft is determined. If the distance from the center of the collision assessment model corresponding to the first aircraft to the target aircraft is less than a preset distance threshold, the avoidance strategy is determined to be that the first aircraft accelerates in the direction of the fixed flight path normal.

7. The method according to claim 6, characterized in that, The method further includes: When both the first aircraft and the target aircraft are in free flight mode, the first aircraft determines a safe distance based on the preset altitude value; If the first aircraft is within a safe distance of less than a preset safe distance threshold, the avoidance strategy is determined to be that the first aircraft and the target aircraft accelerate towards the target direction, where the target direction is the direction connecting the centers of the circles in the collision assessment models corresponding to the first aircraft and the target aircraft.

8. An aerial obstacle avoidance device for unmanned aerial vehicles, characterized in that, include: The first acquisition module is used to acquire wireless signal quality information within the target airspace, and determine the target perception method from a variety of perception methods for sensing unmanned aerial vehicles within the target airspace based on the wireless signal quality. The second acquisition module is used to detect unmanned aerial vehicles in the target airspace according to the target perception method, and acquire the flight information of the detected target aircraft, wherein the flight information is used to indicate at least the distance between the first aircraft and the target aircraft; An avoidance module is used to determine an avoidance strategy based on the flight information, and to avoid the target aircraft according to the avoidance strategy. After determining the target aircraft, the first aircraft acquires the flight information of the target aircraft, which includes at least: the target aircraft's position, speed, heading, and flight mode, and the flight mode includes at least: fixed-path flight and free flight; the first aircraft determines a collision assessment model between the first aircraft and the target aircraft based on the flight information; the first aircraft determines the avoidance strategy according to the collision assessment model. The first aircraft acquires wireless signal quality information within the target airspace and determines a target sensing method from multiple sensing methods for sensing unmanned aerial vehicles (UAVs) within the target airspace based on the wireless signal quality. This includes: the first aircraft acquiring a Channel Quality Indicator (CQI) value and using the CQI value as the wireless signal quality information; the first aircraft determining the target sensing method as a first sensing method when the CQI value is greater than a preset threshold; and the first aircraft determining the target sensing method as a second sensing method when the CQI value is less than the preset threshold. The first sensing method involves acquiring UAVs within the target airspace through a target base station, while the second sensing method involves the first aircraft sensing UAVs within the target airspace independently. The target base station is a base station covering the target airspace. The first aircraft detects unmanned aerial vehicles (UAVs) in the target airspace according to the target perception method and obtains the flight information of the detected target UAVs, including: when the target perception method is the first perception method, the first aircraft obtains a list of UAVs to be matched sent by the target base station, the list of UAVs to be matched contains multiple UAVs sensed by the target base station and the target distance between the first aircraft and the multiple UAVs sensed by the target base station; the first aircraft selects the UAV with the closest target distance from the multiple UAVs sensed by the target base station and determines it as the target UAV.

9. An unmanned aerial vehicle, characterized in that, include: Memory, used to store program instructions; A processor, connected to the memory, is configured to execute program instructions for the following functions: acquiring wireless signal quality information within a target airspace, and determining a target sensing method from multiple sensing methods for sensing unmanned aerial vehicles (UAVs) within the target airspace based on the wireless signal quality; detecting UAVs within the target airspace according to the target sensing method, and acquiring flight information of the detected target UAVs, the flight information being at least used to indicate the distance between a first aircraft and the target UAV; determining an avoidance strategy based on the flight information, and avoiding the target UAV according to the avoidance strategy; after identifying the target UAV, the first aircraft acquires flight information of the target UAV, the flight information including at least: the target UAV's position, speed, heading, and flight mode, the flight mode including at least: fixed-path flight and free flight; the first aircraft determines a collision assessment model between the first aircraft and the target UAV based on the flight information; the first aircraft determines the avoidance strategy based on the collision assessment model. The first aircraft acquires wireless signal quality information within the target airspace and determines a target sensing method from multiple sensing methods for sensing unmanned aerial vehicles (UAVs) within the target airspace based on the wireless signal quality. This includes: the first aircraft acquiring a Channel Quality Indicator (CQI) value and using the CQI value as the wireless signal quality information; the first aircraft determining the target sensing method as a first sensing method when the CQI value is greater than a preset threshold; and the first aircraft determining the target sensing method as a second sensing method when the CQI value is less than the preset threshold. The first sensing method involves acquiring UAVs within the target airspace through a target base station, while the second sensing method involves the first aircraft sensing UAVs within the target airspace independently. The target base station is a base station covering the target airspace. The first aircraft detects unmanned aerial vehicles (UAVs) in the target airspace according to the target perception method and obtains the flight information of the detected target UAVs, including: when the target perception method is the first perception method, the first aircraft obtains a list of UAVs to be matched sent by the target base station, the list of UAVs to be matched contains multiple UAVs sensed by the target base station and the target distance between the first aircraft and the multiple UAVs sensed by the target base station; the first aircraft selects the UAV with the closest target distance from the multiple UAVs sensed by the target base station and determines it as the target UAV.

10. A non-volatile storage medium, characterized in that, The non-volatile storage medium includes a stored computer program, wherein the device containing the non-volatile storage medium executes the unmanned aerial vehicle aerial avoidance method according to any one of claims 1 to 7 by running the computer program.

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