Avoidance method and device based on optical communication unmanned aerial vehicle identification information automatic broadcasting

Abstract

The invention relates to the technical field of unmanned aerial vehicle communication, in particular to an avoidance method and device based on optical communication unmanned aerial vehicle identification information automatic broadcasting, and the method comprises the steps: obtaining the current geographic position information of a target unmanned aerial vehicle, and calculating the kinematics information of the target unmanned aerial vehicle in combination with the historical geographic position information; calculating configuration information of a wireless light source of the target unmanned aerial vehicle according to the kinematics information so as to set a communication boundary of the wireless light source through the configuration information; constructing to-be-transmitted state information, and constructing the to-be-transmitted state information into a data frame conforming to a preset frame structure; controlling a wireless light source to broadcast a data frame into the space; and receiving state information of other unmanned aerial vehicles, and controlling the target unmanned aerial vehicle to avoid according to the state information. Therefore, the interference to the existing radio frequency network is reduced, the security of data transmission is improved, the cooperative control performance of the unmanned aerial vehicle cluster is improved, the real-time monitoring and scheduling capability is enhanced, and the method has important significance for constructing a safe and efficient unmanned aerial vehicle system.

Description

Technical Field

[0001] The present invention relates to the field of unmanned aerial vehicle communication technology, and in particular to an avoidance method and device based on automatic broadcasting of optical communication unmanned aerial vehicle identification information. Background Art

[0002] Typically, UAVs (Unmanned Aerial Vehicles) are controlled by operators via radio. But with the advent of intelligent control technology, drones can use autopilot software to operate out of the operator's field of vision. But these autonomous drones require fine control by software to avoid collisions with buildings and other drones.

[0003] In order to further improve the safety and supervision of drones and ensure their safe coexistence with manned aircraft and ground facilities, the FAA (Federal Aviation Administration) requires all drones in US airspace to autonomously broadcast basic information such as their location, altitude, speed and flight direction. In addition, my country's mandatory national standard for drones GB 42590-2023 also stipulates that drones should automatically broadcast identification information during flight.

[0004] ADS-B (Automatic Dependent Surveillance-Broadcast) technology has been applied in aviation. Aircraft using ADS-B first determine their position from the satellite navigation system and then broadcast this information. At the same time, the aircraft will also receive information from other aircraft. This decentralized technology is suitable for migration to drone scenarios. It can effectively reduce latency in drone clusters, improve network robustness, and adapt to rapidly changing environments.

[0005] However, if traditional radio frequency communication technology is used for broadcasting, drone swarms will face the problem of insufficient spectrum resources or interference with ground equipment, which may make it difficult to transmit control signals, increase signal delays and security risks, and reduce communication reliability. In addition, radio frequency signals can penetrate buildings, which may cause drone status information to be eavesdropped, reducing data security.

[0006] In addition, the rapid increase in the number of drones has also brought severe challenges to air traffic safety. In a complex flight environment, the risk of collision between drones and between drones and other aerial vehicles has increased significantly, which not only threatens the safety of the drones themselves, but may also cause serious harm to people and property on the ground. Traditional drone avoidance technology mainly relies on manual control or preset routes. It has a slow response speed when facing emergencies and is difficult to cope with complex avoidance requirements in multi-machine collaborative scenarios. In addition, the current drone avoidance decision algorithm often has problems such as decision delays and unreasonable planning paths when dealing with multi-target avoidance in a highly dynamic environment, making it difficult to ensure the safety and effectiveness of the avoidance action. In the case of limited communication, the coordinated avoidance between drones faces technical difficulties such as untimely information exchange and asynchronous command execution.

[0007] Therefore, developing a UAV avoidance system that can quickly perceive the environment, accurately assess risks, intelligently plan paths, and achieve multi-machine collaboration has important theoretical value and practical application significance. Summary of the invention

[0008] The present invention provides an avoidance method and device based on automatic broadcasting of optical communication UAV identification information, so as to solve the problems faced by UAV clusters in traditional radio frequency communication broadcasting technology, such as insufficient spectrum resources or interference with ground equipment, as well as the problems that may cause control signaling to be difficult to transmit, signal delay and increased security risks, and reduced communication reliability.

[0009] The first aspect of the present invention provides an avoidance method based on automatic broadcasting of optical communication UAV identification information, comprising the following steps: obtaining the current geographic location information of the target UAV, and calculating the kinematic information of the target UAV in combination with the historical geographic location information; calculating the configuration information of the wireless optical light source of the target UAV according to the kinematic information, so as to set the communication boundary of the wireless optical light source through the configuration information; constructing the state information to be transmitted, and organizing the state information to be transmitted into a data frame conforming to a preset frame structure; based on the configuration information of the wireless optical light source, controlling the wireless optical light source to broadcast the data frame into space; receiving the state information of other UAVs except the target UAV, so as to control the target UAV to avoid according to the state information.

[0010] Optionally, the acquiring current geographic location information of the target UAV and calculating the kinematic information of the target UAV in combination with historical geographic location information includes:

[0011] Use geolocation services to obtain the current geographic location information of the target drone;

[0012] Processing the historical geographic location information and the current geographic location information using a time domain difference method to obtain the speed and direction of the target UAV at multiple historical moments; or

[0013] Smoothing the multiple historical speeds using a Kalman filter method to obtain the current speed and direction of the target UAV; or

[0014] Merging the multiple historical moment speeds by different weights to obtain the average speed and direction of the target UAV; or

[0015] The acceleration of the target UAV at any time is measured by an accelerometer, and the current acceleration is numerically integrated using an acceleration integration method to obtain the instantaneous speed and direction of the target UAV.

[0016] Optionally, the configuration information includes at least one of position, azimuth, half-beam angle, and power allocation.

[0017] Optionally, constructing the state information to be transmitted and constructing the state information to be transmitted into a data frame conforming to a preset frame structure includes:

[0018] Collecting the self-operation information of the target UAV;

[0019] According to the target transmission requirements, identification information is selected from the current geographical location information, the kinematic information and the self-operation information, and the identification information is used to construct the state information to be transmitted, wherein the state information to be transmitted includes at least one of the following: the heading, longitude and latitude, altitude, speed, positioning accuracy, speed accuracy, timestamp, drone identification code, remaining battery power, control mode, and longitude and latitude of the drone control station;

[0020] The state information to be transmitted is organized into a data frame conforming to the preset frame structure.

[0021] Optionally, the preset frame structure should comply with at least one of the requirements for the physical layer and MAC in standards including but not limited to IEEE 802.15.7, CCSDS142.0-B-1, GB / T36628.1-2018, and ITU-T G.709.

[0022] Optionally, the receiving status information of other drones except the target drone includes:

[0023] Based on a half-duplex or full-duplex mode, a photoelectric detector is used to receive status information of other UAVs except the target UAV.

[0024] The second aspect of the present invention provides an avoidance device based on automatic broadcasting of optical communication UAV identification information, including: a calculation module, used to obtain the current geographic location information of the target UAV, and calculate the kinematic information of the target UAV in combination with the historical geographic location information; a configuration module, used to calculate the configuration information of the wireless optical light source of the target UAV according to the kinematic information, so as to set the communication boundary of the wireless optical light source through the configuration information; a framing module, used to construct the state information to be transmitted, and assemble the state information to be transmitted into a data frame that conforms to a preset frame structure; a broadcasting module, used to control the wireless optical light source to broadcast the data frame into space based on the configuration information of the wireless optical light source; an avoidance module, used to receive the state information of other UAVs except the target UAV, so as to control the target UAV to avoid according to the state information.

[0025] The third aspect of the present invention provides an electronic device, comprising: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the avoidance method based on automatic broadcasting of optical communication drone identification information as described in the above embodiment.

[0026] The fourth aspect of the present invention provides a computer program product, which, when executed by a processor, implements the avoidance method based on automatic broadcasting of optical communication drone identification information.

[0027] A fifth aspect of the present invention provides a computer-readable storage medium, which stores a computer program. When the program is executed by a processor, it implements the above-mentioned avoidance method based on automatic broadcasting of optical communication drone identification information.

[0028] The avoidance method and device based on automatic broadcast of optical communication UAV identification information proposed in the embodiments of the present invention avoid the use of radio frequency spectrum, reduce interference to existing networks, improve the security of data transmission, reduce the risk of information leakage and eavesdropping, improve the collaborative control performance of UAV clusters, and enhance real-time monitoring and scheduling capabilities, which is of great significance for building a safe and efficient UAV system.

[0029] Additional aspects and advantages of the present invention will be given in part in the following description and in part will be obvious from the following description, or will be learned through practice of the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0030] The above and / or additional aspects and advantages of the present invention will become apparent and easily understood from the following description of the embodiments in conjunction with the accompanying drawings, in which:

[0031] Figure 1A flow chart of an avoidance method based on automatic broadcasting of optical communication UAV identification information provided by an embodiment of the present invention;

[0032] Figure 2 A schematic diagram of the principle of avoidance based on automatic broadcasting of optical communication UAV identification information provided by an embodiment of the present invention;

[0033] Figure 3 A schematic diagram of the format of a message part in a wireless optical signal frame for avoidance based on automatic broadcast of optical communication drone identification information provided by an embodiment of the present invention;

[0034] Figure 4 A schematic block diagram of an avoidance device based on automatic broadcasting of optical communication UAV identification information provided by an embodiment of the present invention;

[0035] Figure 5 The present invention is a schematic diagram of the structure of an electronic device provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0036] Embodiments of the present invention are described in detail below, examples of which are shown in the accompanying drawings, wherein the same or similar reference numerals throughout represent the same or similar elements or elements having the same or similar functions. The embodiments described below with reference to the accompanying drawings are exemplary and are intended to be used to explain the present invention, and should not be construed as limiting the present invention.

[0037] The following describes an avoidance method and device based on automatic broadcasting of optical communication UAV identification information according to an embodiment of the present invention with reference to the accompanying drawings.

[0038] It should be noted that, in the context of the rapid growth of communication data traffic and the increasingly crowded spectrum, wireless optical communication is being regarded as a highly promising option for future 6G communication technology due to its free band license characteristics. Wireless optical communication mainly uses two light sources: LED (Light Emitting Diode) and laser. LED light sources are favored for their low cost, low power consumption and easy integration; while laser light sources have the advantages of high directivity, excellent monochromaticity and high power density. In terms of frequency band classification, wireless optical communication can be divided into visible light communication, infrared light communication and ultraviolet light communication. Visible light communication uses LED as the transmitting source and PD (Photo Detector) as the receiving device. Its energy efficiency is significantly better than RF (Radio Frequency) communication. Therefore, visible light communication is considered to have great potential in green communication, safe communication and other aspects. Infrared light communication is suitable for applications such as remote controls and infrared data transmission. As an emerging short-distance non-line-of-sight communication technology, ultraviolet light communication shows unique advantages in specific application scenarios. It uses ultraviolet light in the solar blind zone (wavelength range of 200-280nm) for communication, which has the characteristics of strong scattering, strong absorption, and low background noise. These characteristics enable ultraviolet communication to maintain good communication quality in complex environments, especially in the presence of obstructions or non-line-of-sight conditions. The strong scattering characteristics of ultraviolet light also make the communication have good confidentiality, and the signal is difficult to be intercepted from a distance, which is particularly important for military and security applications.

[0039] Applying ultraviolet communication technology to UAV systems can give full play to its advantages. UAVs often face complex and changing environments during flight, such as building obstructions and changing atmospheric conditions. The non-line-of-sight characteristics of ultraviolet communication can effectively overcome these obstacles and ensure the stability of the communication link. In addition, the short-range characteristics of ultraviolet communication help reduce interference between UAVs, especially in high-density flight environments. Ultraviolet communication equipment is small in size, light in weight, and has low power consumption. These characteristics are highly consistent with the strict requirements of UAVs for payload and energy consumption, which is conducive to improving the endurance of UAVs and the efficiency of mission execution.

[0040] In terms of the safety management of drone clusters, broadcasting identification information (such as location, speed, etc.) through ultraviolet light communication plays an important role. First, real-time sharing of this information allows each drone in the cluster to understand the status of surrounding drones in a timely manner, thereby optimizing the flight path, avoiding collisions, and improving overall flight safety. Secondly, this information sharing mechanism helps to achieve collaborative control of the cluster, allowing the entire cluster to respond to complex tasks and emergencies more flexibly. From a management perspective, broadcasting identification information enables the ground control station to fully grasp the status of each drone, which is conducive to real-time monitoring and command and dispatch, and is of great significance for building a safe and efficient drone application system.

[0041] Specifically, Figure 1 A flowchart of an avoidance method based on automatic broadcasting of optical communication UAV identification information provided by an embodiment of the present invention.

[0042] like Figure 1 As shown, the avoidance method based on automatic broadcasting of optical communication UAV identification information includes the following steps:

[0043] In step S101, the current geographic location information of the target UAV is obtained, and the kinematic information of the target UAV is calculated in combination with the historical geographic location information.

[0044] In some embodiments, obtaining the current geographic location information of the target UAV and calculating the kinematic information of the target UAV in combination with the historical geographic location information includes:

[0045] Use geolocation services to obtain the current geographic location information of the target drone;

[0046] Use the time domain difference method to process the historical geographic location information and the current geographic location information to obtain the speed and direction of the target UAV at multiple historical moments; or

[0047] Use Kalman filtering to smooth multiple historical speeds to obtain the current speed and direction of the target drone; or

[0048] By fusing multiple historical speeds with different weights, the average speed and direction of the target drone can be obtained; or

[0049] The acceleration of the target UAV at any time is measured by an accelerometer, and the current acceleration is numerically integrated using the acceleration integration method to obtain the instantaneous speed and direction of the target UAV.

[0050] In the actual implementation process, the embodiment of the present invention pre-installs all the devices of the geolocation service on the drone, without the need for external devices, to obtain the historical and current geographic location information of the target drone; or only installs the client component on the drone, relying on the server component on other devices to obtain the location information. The geolocation service setting includes at least one of GPS, base station, and geomagnetic field positioning.

[0051] Specifically, Figure 2 As shown in the figure, the GPS receiver on the drone continuously receives signals sent from at least four GPS satellites. Each satellite signal contains the precise position of the satellite and the timestamp of the signal transmission. The receiver calculates the signal propagation time by comparing the signal transmission time and reception time, and then multiplies it by the speed of light to obtain the distance between the receiver and each satellite. Next, the receiver simultaneously determines the three-dimensional coordinates (longitude, latitude, altitude) and clock error of the drone by solving a set of nonlinear equations. This process may require multiple iterations to obtain sufficiently accurate results. Once the position is determined, the GPS module will pass this information to the main control system of the drone. The main control system will fuse this raw data with data from other sensors (such as the inertial measurement unit IMU), and use algorithms such as Kalman filtering to improve the accuracy and reliability of positioning.

[0052] Drones can also use base station positioning, which mainly relies on the signal strength and time difference between the drone and the surrounding mobile communication base stations. Specifically, the drone detects the surrounding base station signals and estimates the distance to each base station based on the received signal strength and arrival time difference. Then, it determines its own position through triangulation. This method works better in places with dense base stations such as cities, but the accuracy is usually not as good as GPS.

[0053] In addition, drones can be positioned without external equipment. For example, geomagnetic field positioning uses changes in the Earth's magnetic field to determine location. The magnetometer on the drone measures the local magnetic field strength and direction, and then compares this data with a pre-stored geomagnetic field map. By finding the best match, the system can estimate the approximate location of the drone.

[0054] Furthermore, the following technologies can be used to calculate kinematic information such as flight speed and direction, including: time domain difference method, which directly compares the position difference with the time difference to obtain the speed and direction of the target drone at multiple historical moments; Kalman filter method, which uses a Kalman filter to smooth the speeds of multiple historical moments and gives the speed and direction at the current moment; hybrid positioning technology, which combines the data of the positioning service system, inertial measurement unit or other sensors to comprehensively calculate the speed and direction, thereby improving the accuracy; acceleration integration method, which measures the acceleration of the drone through an accelerometer and calculates the speed and direction through time integration.

[0055] Specifically, based on the time domain difference method, assuming that x1 and x2 are the positions of the drone at two adjacent moments t1 and t2, then through time domain difference, the speed of the drone can be inferred as:

[0056]

[0057] Based on the Kalman filter method, if the GPS error is taken into account, the Kalman filter is a suitable real-time state estimation algorithm. Assume that the state of the drone can be expressed as a state vector containing position and velocity:

[0058] X=[xyV x V y ] T

[0059] Where (x, y) is the position, (V x ,V y ) is the speed. The state change of the drone in each time step T can be expressed by the following linear model

[0060] X k =FX k-1 +Bu k +w

[0061] Where k is the time, F is the state transfer matrix, B is the control input matrix, u k is the control input, w is the process noise, and it obeys the Gaussian distribution w~N(0,Q). Specifically, in this embodiment,

[0062]

[0063]

[0064] u k =[a x a y ] T

[0065] Among them, (a x ,a y ) is the acceleration. The state vector is mapped to the observed value through the geolocation service:

[0066] z=HX+v

[0067]

[0068] Where v is the observation noise.

[0069] The current state and covariance can be predicted as

[0070] X k|k-1 =FXk-1|k-1 +Bu k

[0071] P k|k-1 =FP k-1|k-1 F T +Q

[0072] The Kalman gain is updated as:

[0073] K k =P k|k-1 H T (HP k|k-1 H T +R) -1

[0074] The state estimate is updated to:

[0075] X k|k =X k|k-1 +K k (z k -HX k|k-1 )

[0076] The covariance is updated as:

[0077] P k|k =(IK k H)P k|k-1

[0078] Through continuous recursion, the Kalman filter algorithm can update the state estimate in real time, effectively filter out the noise in the system, and this estimate is a linear optimal estimate.

[0079] It can be understood that the state vector X of the drone can also include the altitude and the speed corresponding to that direction. The state transfer matrix F, the control input matrix B, the control input u, the process noise w, and the observation noise v all need to perform corresponding dimensionality-increasing operations.

[0080] Based on hybrid positioning technology, it involves weighted averaging or filtering, fusing data from multiple sensors with different weights:

[0081] V fused =w1V GPS +w2V IMU +W3V other

[0082] In the above formula, V GPS 、V IMU and V other They are the speeds calculated by GPS, IMU and other sensors, and w1, w2 and w3 are the corresponding weights.

[0083] Based on the acceleration integration method, a(t) is the acceleration of the drone at time t, which can be obtained through the IMU. After obtaining the acceleration of the drone at any time, the trapezoidal method or Simpson method can be used to achieve numerical integration:

[0084] V=V initial +∫a(t)dt.

[0085] In step S102, the configuration information of the wireless light source of the target UAV is calculated according to the kinematic information, so as to set the safety boundary of the wireless light source through the configuration information.

[0086] In some embodiments, the configuration information includes at least one of a position, an azimuth, a half-beam angle, and a power allocation.

[0087] In the actual implementation process, the configuration information of the wireless light source is calculated to achieve the preset security boundary. The following technologies can be used:

[0088] As for the location of the wireless optical source, the light sources on the side fuselage should be evenly distributed to ensure that all directions on the horizontal plane are covered. In addition, a wide-angle light source should be installed on the top and bottom of the drone to broadcast to drones at different heights.

[0089] Regarding the azimuth of the wireless optical source, the drone may yaw, pitch, and roll during flight, and the light source needs to follow the drone's attitude changes to ensure the accuracy of the forward broadcast. The attitude changes of the drone can be described by Euler angles. Let the yaw angle be ψ, the pitch angle be φ, and the roll angle be γ. The adjustment of the light source direction can be calculated by the rotation matrix R(ψ,φ,γ):

[0090]

[0091] The main axis direction of the light source (usually the direction of the drone's movement) can be adjusted in real time through this rotation matrix to ensure that the light beam is always aligned with the direction of the drone's movement.

[0092] For the half-beam angle of the wireless light source, the half-beam angle determines the horizontal diffusion range of the light beam. Considering the flight speed of the drone and the relative distance from other drones, the half-beam angle needs to be adjusted to ensure that the warning signal can be effectively broadcast to the surrounding area. The half-beam angle Φ 1 / 2 It can be determined by the following formula:

[0093]

[0094] Among them, R s is the safe distance between drones, d is the closest distance to other drones in the corresponding direction, α is a coefficient used to adjust the effect of flight speed on the beam angle, and v relis the relative speed between drones, which can be obtained by the velocity vector v of drone i and drone j i ,v j calculate:

[0095] v rel =v i -v j

[0096] When the relative speed of the drone is high, the half-beam angle will be reduced accordingly to broadcast forward in a more concentrated manner; when the relative speed of the drone is low, the half-beam angle will be increased to cover a wider area.

[0097] For the power of the wireless optical source, it is necessary to consider the flight speed of the drone, the relative distance to other drones, and the environmental factors of signal propagation. In order to avoid excessive or insufficient power, the power needs to be allocated dynamically. Transmitting power P t and received power P r The relationship can be described by the following formula:

[0098] P r =P t ·G

[0099] Among them, G represents the wireless optical gain, which is related to the propagation distance, transmission angle, receiving angle, and frequency. In order to ensure that the broadcast signal can be received by other drones, P r Should not be lower than a certain receiving threshold P min In addition, the transmission power should be based on the relative speed v rel Dynamic adjustment can introduce an adjustment factor β to obtain the dynamic adjustment formula of power distribution:

[0100]

[0101] When the relative speed of the drone is high, the power is appropriately increased to increase the coverage and ensure the effectiveness of the broadcast.

[0102] In step S103, the state information to be transmitted is constructed, and the state information to be transmitted is constructed into a data frame conforming to a preset frame structure.

[0103] In some embodiments, constructing the state information to be transmitted and forming the state information to be transmitted into a data frame conforming to a preset frame structure includes:

[0104] Collect the target drone’s own operating information;

[0105] According to the target transmission requirements, identification information is selected from the current geographic location information, kinematic information and own operation information, and the identification information is used to construct the state information to be transmitted, wherein the state information to be transmitted includes at least one of the following: the heading, longitude and latitude, altitude, speed, positioning accuracy, speed accuracy, timestamp, drone identification code, remaining battery power, control mode, and longitude and latitude of the drone control station;

[0106] The state information to be transmitted is organized into a data frame conforming to a preset frame structure.

[0107] During the actual execution process, the target UAV collects its own operating information, selects the identification information to be transmitted from the current geographic location information, kinematic information and its own operating information according to the target transmission requirements, modifies the information to be transmitted to construct the status information to be transmitted, and then assembles the status information to be transmitted into a data frame that conforms to the preset frame structure.

[0108] Among them, the preset frame structure should comply with at least one of the requirements for the physical layer and MAC of standards including but not limited to IIEEE 802.15.7, CCSDS142.0-B-1, GB / T36628.1-2018, ITU-T G.709, etc.

[0109] The wireless optical signal frame broadcast of the drone will depend on the communication protocol used, and the drone identification information can be inserted or appended to an existing wireless optical signal frame or a sequence of wireless optical signal frames, or the drone identification information can be sent in a separate wireless optical signal frame.

[0110] like Figure 3 As shown, the structure of the message part of the wireless optical signal frame containing drone identification information includes geographic location, speed, direction and other optional information. A row in the figure shows a 32-bit field, and one, more or part of the 8-bit field can be used to contain the information to be transmitted. It should be noted that these examples are for illustrative purposes only, and other embodiments may have other formats or contain other information.

[0111] The information and format included in the embodiment of the present invention are as follows:

[0112] Message type: 8-bit field used to indicate the type of information provided to prevent confusion with data payload;

[0113] Message length: 8-bit field used to indicate the length of the entire message in bytes;

[0114] Protocol version: 8-bit field used to indicate the format of the transmitted message;

[0115] Lifetime: 8-bit field used to indicate the remaining number of transmissions of a data frame in the information relay;

[0116] Operation status and flag bit: 8-bit field, used to indicate the current operation status of the drone, including normal state, emergency state, and operation identification function failure state;

[0117] Track angle: 8-bit field used to indicate the direction of movement. For example, using degrees as units;

[0118] Ground speed: 8-bit field, used to indicate the current ground speed of the drone;

[0119] Vertical speed: 8-bit field, used to indicate the current vertical speed of the drone. The speed is positive when climbing and negative when descending.

[0120] Longitude: 32-bit field used to indicate the current longitude of the drone;

[0121] Latitude: 32-bit field, used to indicate the current latitude of the drone;

[0122] Barometric altitude: 16-bit field, used to indicate the current barometric altitude of the drone, with 1013.25 millibars as the reference surface;

[0123] Geometry altitude: 16-bit field used to indicate the current pressure altitude of the drone, with 1013.25 millibars as the reference surface;

[0124] Altitude from ground: 16-bit field, used to indicate the current pressure altitude of the drone, with 1013.25 millibars as the reference surface pressure altitude;

[0125] Position accuracy, an 8-bit field, is used to indicate the positioning accuracy of the drone. The first 4 bits represent the vertical accuracy, and the last 4 bits represent the horizontal accuracy.

[0126] Speed ​​accuracy: 8-bit field used to indicate the speed accuracy of the drone;

[0127] Timestamp: 16-bit field, used to indicate the number of 1 / 10 seconds that have passed since the current hour;

[0128] Timestamp precision: 8-bit field used to indicate the range of timestamp precision that can be represented;

[0129] UAV identification code: 32-bit field, used as an identifier for a UAV or wireless optical communication device;

[0130] Remaining battery power: a 16-bit field used to indicate the percentage of remaining battery power of the drone. In other embodiments, it may also indicate the remaining usage time.

[0131] Control mode: 16-bit field, used to indicate the current control state of the drone, including operator control and automatic cruise;

[0132] UAV control station latitude: 32-bit field used to indicate the latitude of the UAV control station;

[0133] UAV control station longitude: 32-bit field used to indicate the longitude of the UAV control station;

[0134] Other information: other control information or identification information other than data payload.

[0135] In step S104, based on the configuration information of the wireless optical source, the wireless optical source is controlled to broadcast data frames into space.

[0136] Among them, the frequency band of wireless optical communication includes at least one of the infrared light band, the visible light band and the ultraviolet light band; the light source of wireless optical communication includes at least one of the light-emitting diode light source and the laser light source; broadcasting refers to the transmission of wireless optical signal frames by the drone to all targets within the signal transmission range, but the technology should also be applicable to multicast transmission or unicast transmission directed to one target.

[0137] In step S105, status information of other drones except the target drone is received to control the target drone to avoid according to the status information.

[0138] In actual implementation, avoidance can be achieved through the following key parts:

[0139] Detection range: Based on half-duplex or full-duplex mode, each target drone uses photodiodes, photoelectric sensors and other photoelectric detectors to receive status information of other drones except the target drone, so as to judge the potential collision threat based on the status information of other drones received. If other drones enter a certain detection range, the drone will execute the following collision prediction and collision strategy.

[0140] Collision Prediction: Predict the possible collision time and location based on the speed and position of other drones.

[0141] Avoidance strategy: Once a possible collision is detected, the drone adjusts its speed, direction or altitude according to certain priority rules and avoidance algorithms to avoid the collision.

[0142] Regarding the detection range, when a drone receives a wireless optical signal from another drone, it considers that there is a potential collision threat and executes collision prediction and collision strategy.

[0143] For collision prediction, each drone determines whether there is a potential collision risk by calculating the Euclidean distance with other drones. Suppose there are two drones A and B, with positions r A =(x A ,y A ,z A ) and rB =(x B ,y B ,z B ), the drone will monitor this distance in real time, and their distance d AB The calculation formula is:

[0144]

[0145] If d AB Less than the safety distance threshold R s , the drone will further predict the collision time. Assume that the speeds of the two drones are v A and v B , the relative velocity v between them can be calculated rel =v A -v B ; Similarly, the relative position r of the drone AB =r A -r B , and then use the relative velocity and relative position to predict the collision time t col :

[0146]

[0147] If t col >0 and d AB <R s , the avoidance strategy is activated.

[0148] For avoidance strategies, the drone needs to change its motion parameters (speed, direction or altitude) to avoid collision. Avoidance strategies can be implemented in the following ways:

[0149] Horizontal avoidance: The drone prefers to avoid on the horizontal plane. In this case, it can avoid by adjusting the direction of the velocity vector. First, calculate the minimum steering angle Δθ that can avoid collision. Assuming that drone A needs to avoid drone B, it can adjust its velocity vector v A direction, avoiding the velocity vector v of B B The minimum steering angle Δθ can be given by the following formula:

[0150]

[0151] According to the relative position, decide to turn left or right. Usually, it is stipulated that when the drone is in front, choose to turn right to avoid collision. This can be determined by judging the vertical component of the relative position: if y A -y B >0, turn right, otherwise turn left.

[0152] Altitude avoidance: If horizontal avoidance is difficult to achieve (for example, multiple drones are flying in a similar direction), the drone can also avoid by adjusting its altitude. The altitude adjustment Δz can be calculated based on the current flight altitude layer and the distance to other drones. Usually, a minimum altitude difference Δz=±H can be set. min Drones can prioritize adjusting their altitude according to the set altitude layer rules. Usually, drones at higher altitudes have priority and do not need to adjust their altitude, while drones at lower altitudes need to avoid rising.

[0153] Speed ​​adjustment: When necessary, the drone can also avoid collisions by adjusting its speed. By slowing down or speeding up, it can avoid the moment of encountering other drones. If the drone predicts that a collision will occur in the near future, it can slow down to delay the encounter and avoid a collision. The deceleration amount Δv can be calculated based on the collision time t col calculate:

[0154] Δv=(d AB -R s ) / (t col )

[0155] On the other hand, if the drone predicts that it can pass within a safe distance, it can also choose to accelerate and leave the potential collision area.

[0156] In addition, the drone not only has the ability to broadcast its own identification information, but also can relay the received broadcast by retransmitting the information of another drone. In one embodiment, when preparing the wireless optical signal frame, the information of another drone can be sent as an optional information part. This technology allows the drone to expand the broadcast area in physical distance. In another embodiment, the drone has the ability to broadcast using multiple protocols. In this embodiment, the drone can receive the broadcast of other drones using one communication protocol and retransmit the broadcast using another protocol, which facilitates drones using different protocols to operate in the same area.

[0157] In summary, according to the avoidance method based on automatic broadcasting of optical communication drone identification information proposed in an embodiment of the present invention, the drone can determine the current geographical location based on the information of the geolocation service, and calculate the kinematic information such as flight speed and direction in combination with the location information at historical moments, and at the same time calculate the configuration information of the wireless optical light source to achieve the preset safety boundary, and organize the various status information to be transmitted into data frames that conform to the preset frame structure, and use wireless light to broadcast the above data frames into space, and at the same time avoid according to the status information of other drones received. In this way, the use of radio frequency spectrum is avoided, interference with existing networks is reduced, the security of data transmission is improved, and the risk of information leakage and eavesdropping is reduced. In addition, after receiving the status information of other drones, the target drone will perform intelligent obstacle avoidance, thereby improving the collaborative control performance of the drone cluster and enhancing the real-time monitoring and scheduling capabilities, which is of great significance for building a safe and efficient drone system.

[0158] Next, an avoidance device based on automatic broadcasting of optical communication UAV identification information proposed in an embodiment of the present invention will be described with reference to the accompanying drawings.

[0159] Figure 4 A block diagram of an avoidance device based on automatic broadcasting of optical communication UAV identification information provided by an embodiment of the present invention.

[0160] like Figure 4 As shown, the avoidance device 40 based on automatic broadcasting of optical communication UAV identification information includes: a calculation module 401, a configuration module 402, a framing module 403, a broadcasting module 404 and an avoidance module 405.

[0161] Among them, the calculation module 401 is used to obtain the current geographic location information of the target drone, and calculate the kinematic information of the target drone in combination with the historical geographic location information. The configuration module 402 is used to calculate the configuration information of the wireless light source of the target drone based on the kinematic information, so as to set the communication boundary of the wireless light source through the configuration information. The frame assembly module 403 is used to construct the state information to be transmitted, and assemble the state information to be transmitted into a data frame that conforms to the preset frame structure. The broadcast module 404 is used to control the wireless light source to broadcast data frames into space based on the configuration information of the wireless light source. The avoidance module 405 is used to receive the state information of other drones except the target drone, so as to control the target drone to avoid according to the state information.

[0162] In some embodiments, the calculation module 401 includes:

[0163] Use geolocation services to obtain the current geographic location information of the target drone;

[0164] Use the time domain difference method to process the historical geographic location information and the current geographic location information to obtain the speed and direction of the target UAV at multiple historical moments; or

[0165] Use Kalman filtering to smooth multiple historical speeds to obtain the current speed and direction of the target drone; or

[0166] By fusing multiple historical speeds with different weights, the average speed and direction of the target drone can be obtained; or

[0167] The acceleration of the target UAV at any time is measured by an accelerometer, and the current acceleration is numerically integrated using the acceleration integration method to obtain the instantaneous speed and direction of the target UAV.

[0168] In some embodiments, the configuration information includes at least one of a position, an azimuth, a half-beam angle, and a power allocation.

[0169] In some embodiments, the framing module 403 includes:

[0170] A collection unit, used to collect the target UAV's own operating information;

[0171] A selection unit, configured to select identification information from the current geographic location information, kinematic information, and self-operation information according to target transmission requirements, and construct state information to be transmitted from the identification information, wherein the state information to be transmitted includes at least one of the following: the heading, longitude and latitude, altitude, speed, positioning accuracy, speed accuracy, timestamp, drone identification code, remaining battery power, control mode, and longitude and latitude of the drone control station;

[0172] The assembly unit is used to assemble the state information to be transmitted into a data frame that conforms to a preset frame structure.

[0173] In some embodiments, the preset frame structure should comply with at least one of the requirements for the physical layer and MAC of standards including but not limited to IEEE 802.15.7, CCSDS142.0-B-1, GB / T 36628.1-2018, ITU-T G.709, etc.

[0174] In some embodiments, the avoidance module 405 includes:

[0175] Based on half-duplex or full-duplex mode, a photoelectric detector is used to receive the status information of other UAVs except the target UAV.

[0176] It should be noted that the aforementioned explanation of the embodiment of the avoidance method based on automatic broadcasting of optical communication UAV identification information is also applicable to the avoidance device based on automatic broadcasting of optical communication UAV identification information of this embodiment, and will not be repeated here.

[0177] According to the avoidance device based on automatic broadcast of optical communication drone identification information proposed in the embodiment of the present invention, the drone can determine the current geographical location based on the information of the geolocation service, calculate the kinematic information such as flight speed and direction in combination with the location information at historical moments, and calculate the configuration information of the wireless optical light source to achieve the preset safety boundary, organize the various status information to be transmitted into data frames that conform to the preset frame structure, broadcast the above data frames into space using wireless light, and avoid according to the status information of other drones received. In this way, the use of radio frequency spectrum is avoided, interference with existing networks is reduced, the security of data transmission is improved, and the risk of information leakage and eavesdropping is reduced. In addition, after receiving the status information of other drones, the target drone will perform intelligent obstacle avoidance, thereby improving the collaborative control performance of the drone cluster and enhancing the real-time monitoring and scheduling capabilities, which is of great significance for building a safe and efficient drone system.

[0178] Figure 5 A schematic diagram of the structure of an electronic device provided by an embodiment of the present invention. The electronic device may include:

[0179] A memory 501 , a processor 502 , and a computer program stored in the memory 501 and executable on the processor 502 .

[0180] When the processor 502 executes the program, the avoidance method based on automatic broadcasting of optical communication drone identification information provided in the above embodiment is implemented.

[0181] Furthermore, the electronic device further comprises:

[0182] The communication interface 503 is used for communication between the memory 501 and the processor 502 .

[0183] The memory 501 is used to store computer programs that can be executed on the processor 502 .

[0184] The memory 501 may include a high-speed RAM memory, and may also include a non-volatile memory (non-volatile memory), such as at least one disk memory.

[0185] If the memory 501, the processor 502 and the communication interface 503 are implemented independently, the communication interface 503, the memory 501 and the processor 502 can be connected to each other through a bus and communicate with each other. The bus can be an Industry Standard Architecture (ISA) bus, a Peripheral Component (PCI) bus or an Extended Industry Standard Architecture (EISA) bus. The bus can be divided into an address bus, a data bus, a control bus, etc. For ease of representation, Figure 5 Only one thick line is used in the diagram, but this does not mean that there is only one bus or only one type of bus.

[0186] Optionally, in a specific implementation, if the memory 501, the processor 502 and the communication interface 503 are integrated on a chip, the memory 501, the processor 502 and the communication interface 503 can communicate with each other through an internal interface.

[0187] The processor 502 may be a central processing unit (CPU), or an application specific integrated circuit (ASIC), or one or more integrated circuits configured to implement the embodiments of the present invention.

[0188] An embodiment of the present invention also provides a computer program product, which, when executed by a processor, implements the above-mentioned avoidance method based on automatic broadcasting of optical communication drone identification information.

[0189] An embodiment of the present invention also provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the above-mentioned avoidance method based on automatic broadcasting of optical communication drone identification information.

[0190] In the description of this specification, the description with reference to the terms "one embodiment", "some embodiments", "example", "specific example", or "some examples" etc. means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic representations of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described may be combined in any one or N embodiments or examples in a suitable manner. In addition, those skilled in the art may combine and combine the different embodiments or examples described in this specification and the features of the different embodiments or examples, without contradiction.

[0191] In addition, the terms "first" and "second" are used for descriptive purposes only and should not be understood as indicating or implying relative importance or implicitly indicating the number of the indicated technical features. Therefore, the features defined as "first" and "second" may explicitly or implicitly include at least one of the features. In the description of the present invention, the meaning of "N" is at least two, such as two, three, etc., unless otherwise clearly and specifically defined.

[0192] Any process or method description in a flowchart or otherwise described herein may be understood to represent a module, fragment or portion of code comprising one or N executable instructions for implementing the steps of a custom logical function or process, and the scope of the preferred embodiments of the present invention includes alternative implementations in which functions may not be performed in the order shown or discussed, including performing functions in a substantially simultaneous manner or in reverse order depending on the functions involved, which should be understood by technicians in the technical field to which the embodiments of the present invention belong.

[0193] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as an ordered list of executable instructions for implementing logical functions, and can be embodied in any computer-readable medium for use by an instruction execution system, device or apparatus (such as a computer-based system, a system including a processor, or other system that can fetch instructions from an instruction execution system, device or apparatus and execute instructions), or in combination with these instruction execution systems, devices or apparatuses. For the purpose of this specification, "computer-readable medium" can be any device that can contain, store, communicate, propagate or transmit a program for use by an instruction execution system, device or apparatus, or in combination with these instruction execution systems, devices or apparatuses. More specific examples of computer-readable media (a non-exhaustive list) include the following: an electrical connection with one or N wirings (electronic devices), a portable computer disk box (magnetic device), a random access memory (RAM), a read-only memory (ROM), an erasable and programmable read-only memory (EPROM or flash memory), a fiber optic device, and a portable compact disk read-only memory (CDROM). In addition, the computer-readable medium may even be paper or other suitable medium on which the program is printed, since the program may be obtained electronically by optically scanning the paper or other medium and then editing, interpreting or processing in other suitable ways as necessary and then storing it in a computer memory.

[0194] It should be understood that the various parts of the present invention can be implemented by hardware, software, firmware or a combination thereof. In the above embodiment, the N steps or methods can be implemented by software or firmware stored in a memory and executed by a suitable instruction execution system. If implemented by hardware, as in another embodiment, it can be implemented by any one of the following technologies known in the art or their combination: a discrete logic circuit having a logic gate circuit for implementing a logic function for a data signal, a dedicated integrated circuit having a suitable combination of logic gate circuits, a programmable gate array (PGA), a field programmable gate array (FPGA), etc.

[0195] A person skilled in the art may understand that all or part of the steps in the method for implementing the above-mentioned embodiment may be completed by instructing related hardware through a program, and the program may be stored in a computer-readable storage medium, which, when executed, includes one or a combination of the steps of the method embodiment.

[0196] In addition, each functional unit in each embodiment of the present invention may be integrated into a processing module, or each unit may exist physically separately, or two or more units may be integrated into one module. The above-mentioned integrated module may be implemented in the form of hardware or in the form of a software functional module. If the integrated module is implemented in the form of a software functional module and sold or used as an independent product, it may also be stored in a computer-readable storage medium.

[0197] The storage medium mentioned above may be a read-only memory, a magnetic disk or an optical disk, etc. Although the embodiments of the present invention have been shown and described above, it can be understood that the above embodiments are exemplary and cannot be understood as limiting the present invention. A person of ordinary skill in the art may change, modify, replace and modify the above embodiments within the scope of the present invention.

Claims

1. A method for avoiding unmanned aerial vehicles based on automatic broadcasting of optical communication identification information, characterized in that: The following steps are involved: Obtaining current geographic location information of the target UAV, and calculating kinematic information of the target UAV in combination with historical geographic location information; Calculating configuration information of the wireless optical light source of the target UAV according to the kinematic information, so as to set a communication boundary of the wireless optical light source through the configuration information; Constructing state information to be transmitted, and constructing the state information to be transmitted into a data frame conforming to a preset frame structure; Based on the configuration information of the wireless optical light source, controlling the wireless optical light source to broadcast the data frame into space; Receive status information of other drones except the target drone, so as to control the target drone to avoid according to the status information.

2. The method for avoiding the automatic broadcast of optical communication drone identification information according to claim 1, characterized in that: The obtaining of the current geographic location information of the target UAV and calculating the kinematic information of the target UAV in combination with the historical geographic location information includes: Use geolocation services to obtain the current geographic location information of the target drone; Processing the historical geographic location information and the current geographic location information using a time domain difference method to obtain the speed and direction of the target UAV at multiple historical moments; or Smoothing the multiple historical speeds using a Kalman filter method to obtain the current speed and direction of the target UAV; or Merging the multiple historical moment speeds by different weights to obtain the average speed and direction of the target UAV; or The acceleration of the target UAV at any time is measured by an accelerometer, and the current acceleration is numerically integrated using an acceleration integration method to obtain the instantaneous speed and direction of the target UAV.

3. The avoidance method based on automatic broadcasting of optical communication drone identification information according to claim 1 is characterized in that: The configuration information includes at least one of position, azimuth, half-beam angle, and power allocation.

4. The avoidance method based on automatic broadcasting of optical communication drone identification information according to claim 1 is characterized in that: The step of constructing the state information to be transmitted and forming the state information to be transmitted into a data frame conforming to a preset frame structure includes: Collecting the self-operation information of the target UAV; According to the target transmission requirements, identification information is selected from the current geographical location information, the kinematic information and the self-operation information, and the identification information is used to construct the state information to be transmitted, wherein the state information to be transmitted includes at least one of the following: the heading, longitude and latitude, altitude, speed, positioning accuracy, speed accuracy, timestamp, drone identification code, remaining battery power, control mode, and longitude and latitude of the drone control station; The state information to be transmitted is organized into a data frame conforming to the preset frame structure.

5. The avoidance method based on automatic broadcasting of optical communication drone identification information according to claim 4 is characterized in that: The preset frame structure should comply with at least one of the physical layer and MAC requirements of IEEE 802.15.7, CCSDS142.0-B-1, GB / T36628.1-2018, and ITU-T G.709 standards.

6. The avoidance method based on automatic broadcasting of optical communication drone identification information according to claim 1 is characterized in that: The receiving status information of other drones except the target drone includes: Based on a half-duplex or full-duplex mode, a photoelectric detector is used to receive status information of other UAVs except the target UAV.

7. An avoidance device based on automatic broadcasting of optical communication drone identification information, characterized in that: include: A calculation module, used to obtain the current geographic location information of the target UAV, and calculate the kinematic information of the target UAV in combination with the historical geographic location information; A configuration module, configured to calculate configuration information of the wireless optical light source of the target UAV according to the kinematic information, so as to set a communication boundary of the wireless optical light source through the configuration information; A framing module, used to construct the state information to be transmitted, and assemble the state information to be transmitted into a data frame conforming to a preset frame structure; A broadcast module, configured to control the wireless optical source to broadcast the data frame into space based on the configuration information of the wireless optical source; The avoidance module is used to receive status information of other drones except the target drone, so as to control the target drone to avoid according to the status information.

8. An electronic device, characterized in that: include: A memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the avoidance method based on automatic broadcasting of optical communication UAV identification information as described in any one of claims 1 to 6.

9. A computer program product, characterized in that When the computer program / instruction is executed by the processor, the avoidance method based on automatic broadcasting of optical communication UAV identification information as described in any one of claims 1 to 6 is implemented.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: The program is executed by a processor to implement the avoidance method based on automatic broadcasting of optical communication drone identification information as described in any one of claims 1 to 6.

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