Method and device for avoiding based on automatic broadcasting of information for identifying an optical communication drone

Abstract

The present application relates to the technical field of unmanned aerial vehicle communication, in particular to a kind of method and device for avoiding based on optical communication unmanned aerial vehicle identification information automatic broadcast, wherein, method includes: obtaining target unmanned aerial vehicle current geographic location information, and the kinematics information of target unmanned aerial vehicle is calculated in combination with historical geographic location information;According to the configuration information of the wireless light source of target unmanned aerial vehicle calculated kinematics information, to set the communication boundary of the wireless light source by configuration information;To be transmitted state information is constructed, and to be transmitted state information is built into the data frame that meets the preset frame structure;Control wireless light source broadcasts data frame to space;The state information of other unmanned aerial vehicle is received, and target unmanned aerial vehicle is avoided accordingly.Controlled.By doing so, the interference to existing radio frequency network is reduced, the security of data transmission is improved, the cooperative control performance of unmanned aerial vehicle cluster is improved, the real-time monitoring and scheduling capability is enhanced, and it has important significance for building safe, efficient unmanned aerial vehicle system.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of unmanned aerial vehicle communication, and particularly relates to a method and device for avoiding based on automatic broadcasting of identification information of unmanned aerial vehicles by optical communication. BACKGROUND

[0002] Generally, UAVs (Unmanned Aerial Vehicles) are controlled by an operator through radio to control their trajectory. But with the advent of intelligent control technology, unmanned aerial vehicles can use autonomous driving software to operate out of the operator's field of view. But these autonomous unmanned aerial vehicles need fine control of the software to avoid collisions with buildings and other unmanned aerial vehicles.

[0003] In order to further improve the safety and regulatory capabilities of unmanned aerial vehicles, and to ensure their safe coexistence with manned aircraft and ground facilities, the FAA (Federal Aviation Administration) requires all unmanned aerial vehicles in the airspace of the United States to autonomously broadcast their basic information such as position, height, speed and flight direction. In addition, the mandatory national standard GB 42590-2023 of China also stipulates that unmanned aerial vehicles should automatically broadcast identification information during flight.

[0004] ADS-B (Automatic Dependent Surveillance-Broadcast) technology has been applied in aviation. The aircraft using ADS-B first determines its position from the satellite navigation system, and then broadcasts this information, at the same time, the aircraft also receives the information of other aircrafts. This decentralized technology is suitable for migration to unmanned aerial vehicle scenarios, which can effectively reduce the latency in unmanned aerial vehicle clusters, improve network robustness, and adapt to rapidly changing environments.

[0005] However, if broadcast using traditional radio frequency communication technology, the unmanned aerial vehicle cluster will face the problem of insufficient spectrum resources or interference with ground equipment, which may lead to difficulty in transmitting control signaling, increase signal delay and safety risk, and reduce communication reliability. In addition, radio frequency signals can penetrate buildings, which may lead to the eavesdropping of unmanned aerial vehicle state information, reducing data security.

[0006] In addition, the rapid increase in the number of unmanned aerial vehicles also poses serious challenges to air traffic safety. In a complex flight environment, the risk of collision between unmanned aerial vehicles and between unmanned aerial vehicles and other aerial vehicles is significantly increased, which not only threatens the safety of unmanned aerial vehicles themselves, but also can cause serious harm to ground personnel and property. Traditional unmanned aerial vehicle avoidance techniques mainly rely on manual control or pre-set routes, and have slow response speed in the face of unexpected situations, and are difficult to cope with complex avoidance requirements in multi-vehicle coordination scenarios. In addition, the current unmanned aerial vehicle avoidance decision algorithm often has problems such as decision delay and unreasonable planning path when dealing with multi-target avoidance in a high dynamic environment, making it difficult to ensure the safety and effectiveness of avoidance actions. In the case of limited communication, the coordinated avoidance between unmanned aerial vehicles also faces technical problems such as untimely information exchange and unsynchronized instruction execution.

[0007] Therefore, it is of important theoretical value and practical application significance to develop an unmanned aerial vehicle avoidance system that can quickly perceive the environment, accurately assess the risk, intelligently plan the path, and realize multi-vehicle coordination. SUMMARY

[0008] The application provides an avoidance method and device based on automatic broadcasting of unmanned aerial vehicle identification information through optical communication, to solve the problems of insufficient spectrum resources or interference with ground equipment faced by unmanned aerial vehicle clusters in traditional radio frequency communication broadcasting technology, and the problems of difficult transmission of control signaling, signal delay and increased safety risk, and reduced communication reliability.

[0009] The first aspect of the application provides an avoidance method based on automatic broadcasting of unmanned aerial vehicle identification information through optical communication, comprising the following steps: obtaining current geographic position information of a target unmanned aerial vehicle, and calculating kinematic information of the target unmanned aerial vehicle in combination with historical geographic position information; calculating configuration information of a wireless optical light source of the target unmanned aerial vehicle according to the kinematic information, to set a communication boundary of the wireless optical light source through the configuration information; constructing state information to be transmitted, and assembling the state information to be transmitted into a data frame conforming to a pre-set frame structure; controlling the wireless optical light source to broadcast the data frame into space based on the configuration information of the wireless optical light source; receiving state information of other unmanned aerial vehicles except the target unmanned aerial vehicle, to control the target unmanned aerial vehicle to avoid according to the state information.

[0010] Optionally, the obtaining of the current geographic position information of the target unmanned aerial vehicle and the calculation of the kinematic information of the target unmanned aerial vehicle in combination with the historical geographic position information comprise:

[0011] The current geographic position information of the target unmanned aerial vehicle is obtained by using a geographic positioning service;

[0012] processing the historical geographic position information and the current geographic position information by using a time domain difference method to obtain a plurality of historical time speed and direction of the target UAV; or

[0013] smoothing the plurality of historical time speed by using a Kalman filter method to obtain a current time speed and direction of the target UAV; or

[0014] fusing the plurality of historical time speed by different weights to obtain an average speed and direction of the target UAV; or

[0015] measuring acceleration of the target UAV at any time by using an accelerometer, and performing numerical integration on the current acceleration by using an acceleration integration method to obtain an instantaneous speed and direction of the target UAV.

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

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

[0018] acquiring self-running information of the target UAV;

[0019] selecting identification information from the current geographic position information, the kinematic information, and the self-running information according to target transmission requirements, and constructing the identification information into to-be-transmitted state information, wherein the to-be-transmitted state information includes at least one of forward direction, latitude and longitude, height, speed, positioning accuracy, speed accuracy, time stamp, UAV identification code, battery remaining capacity, control mode, and latitude and longitude of a UAV control station;

[0020] assembling the to-be-transmitted state information into a data frame conforming to the preset frame structure.

[0021] Optionally, the preset frame structure should conform to at least one of requirements for a physical layer and a MAC in IEEE 802.15.7, CCSDS 142.0-B-1, GB / T 36628.1-2018, and ITU-T G.709 standards, but is not limited thereto.

[0022] Optionally, the receiving state information of other UAVs except the target UAV comprises:

[0023] based on a half-duplex or full-duplex mode, receiving state information of other UAVs except the target UAV by using a photoelectric detector.

[0024] The second aspect embodiment of the present application provides an avoiding device based on automatic broadcasting of unmanned aerial vehicle identification information of optical communication, comprising: a calculation module, configured to obtain current geographic position information of a target unmanned aerial vehicle, and calculate kinematic information of the target unmanned aerial vehicle in combination with historical geographic position information; a configuration module, configured to calculate configuration information of a wireless optical light source of the target unmanned aerial vehicle 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, configured to construct to-be-transmitted state information, and assemble the to-be-transmitted state information into a data frame conforming to a preset frame structure; a broadcasting module, configured 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; and an avoiding module, configured to receive state information of unmanned aerial vehicles other than the target unmanned aerial vehicle, so as to control the target unmanned aerial vehicle to avoid according to the state information.

[0025] The third aspect embodiment of the present application 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 avoiding method based on automatic broadcasting of unmanned aerial vehicle identification information of optical communication as described in the above embodiments.

[0026] The fourth aspect embodiment of the present application provides a computer program product, wherein the computer program / instruction is executed by a processor to implement the avoiding method based on automatic broadcasting of unmanned aerial vehicle identification information of optical communication as described above.

[0027] The fifth aspect embodiment of the present application provides a computer readable storage medium, wherein the computer readable storage medium stores a computer program, and the program is executed by a processor to implement the avoiding method based on automatic broadcasting of unmanned aerial vehicle identification information of optical communication as described above.

[0028] The avoiding method and device based on automatic broadcasting of unmanned aerial vehicle identification information of optical communication provided by the embodiments of the present application avoid the use of radio frequency spectrum, reduce the interference to the existing network, improve the security of data transmission, reduce the risk of information leakage and eavesdropping, improve the cooperative control performance of unmanned aerial vehicle clusters, enhance the real-time monitoring and scheduling capability, and have important significance for constructing a safe and efficient unmanned aerial vehicle system.

[0029] Additional aspects and advantages of the present application will be in part apparent and in part pointed out hereinafter. BRIEF DESCRIPTION OF DRAWINGS

[0030] The above and / or additional aspects and advantages of the present application will become apparent and be readily appreciated from the following description, taken in conjunction with the accompanying drawings, in which:

[0031] Figure 1A flow chart of a method for avoiding based on automatic broadcasting of unmanned aerial vehicle identification information by optical communication according to an embodiment of the present application;

[0032] Figure 2 A schematic diagram of the principle of avoiding based on automatic broadcasting of unmanned aerial vehicle identification information by optical communication according to an embodiment of the present application;

[0033] Figure 3 A schematic diagram of the format of the message part in a wireless optical signal frame for avoiding based on automatic broadcasting of unmanned aerial vehicle identification information by optical communication according to an embodiment of the present application;

[0034] Figure 4 A block schematic diagram of a device for avoiding based on automatic broadcasting of unmanned aerial vehicle identification information by optical communication according to an embodiment of the present application;

[0035] Figure 5 A schematic diagram of the structure of an electronic device according to an embodiment of the present application. DETAILED DESCRIPTION

[0036] Embodiments of the present application are described in detail below with reference to the attached drawings, which show by way of example, embodiments in which the same or similar elements or elements having the same or similar functions are denoted by the same reference numerals throughout the drawings and identical or similar components are denoted by the same reference numerals. The embodiments described below by reference to the drawings are exemplary and are intended to explain the present application, and are not to be understood as limiting the present application.

[0037] A method and device for avoiding based on automatic broadcasting of unmanned aerial vehicle identification information by optical communication according to an embodiment of the present application are described below with reference to the drawings.

[0038] It should be noted that in the context of rapidly growing communication data traffic and increasingly crowded spectrum, wireless optical communication is being considered as a highly potential option for future 6G communication technology due to its license-free nature. Wireless optical communication mainly utilizes two types of light sources: LED (Light Emitting Diode) and laser. LED light sources are favored for their low cost, low power consumption, and ease of integration; while laser light sources have 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, and its energy efficiency is significantly better than RF (Radio Frequency) communication. Therefore, visible light communication is considered to have great potential in green communication, secure communication, etc. Infrared light communication is suitable for remote control, infrared data transmission, etc. Ultraviolet light communication, as a new short-range non-line-of-sight communication technology, has unique advantages in specific application scenarios. It uses ultraviolet light in the solar blind region (wavelength range of 200-280nm) for communication, with strong scattering, strong absorption, low background noise, etc. These characteristics enable ultraviolet communication to maintain good communication quality in complex environments, especially in obstructed or non-line-of-sight conditions. The strong scattering characteristics of ultraviolet light also make the communication have good security, and the signal is difficult to be intercepted from a distance, which is particularly important for military and security applications.

[0039] The application of ultraviolet communication technology to unmanned aerial vehicle systems can fully exploit its advantages. Unmanned aerial vehicles often face complex and changing environments during flight, such as building obstructions and atmospheric condition changes. 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 to reduce interference between unmanned aerial vehicles, especially in high-density flight environments. Ultraviolet communication devices are small in size, light in weight, and low in power consumption, which are highly consistent with the strict requirements of unmanned aerial vehicles for payload and energy consumption, and are conducive to improving the endurance and mission execution efficiency of unmanned aerial vehicles.

[0040] In the safety management of the UAV cluster, broadcasting the identification information (such as position, speed, etc.) through the ultraviolet light communication plays an important role. Firstly, sharing these information in real time can make each UAV in the cluster know the status of the surrounding UAVs in time, so as to optimize the flight path, avoid collision, and improve the overall flight safety. Secondly, this information sharing mechanism helps to realize the cooperative control of the cluster, so that the whole cluster can more flexibly cope with complex tasks and unexpected situations. From the management point of view, the broadcast identification information enables the ground control station to fully grasp the status of each UAV, which is beneficial to real-time monitoring and command scheduling, and is of great significance to the construction of a safe and efficient UAV application system.

[0041] Specifically, Figure 1 A flowchart of a UAV identification information automatic broadcasting-based avoidance method provided by an embodiment of the present application is shown in FIG. 1.

[0042] As Figure 1 shown, the UAV identification information automatic broadcasting-based avoidance method includes the following steps:

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

[0044] In some embodiments, the current geographic position information of the target UAV is obtained, and the kinematic information of the target UAV is calculated in combination with the historical geographic position information, including:

[0045] The current geographic position information of the target UAV is obtained by using a geographic positioning service;

[0046] The historical geographic position information and the current geographic position information are processed by using a time domain difference method to obtain a plurality of historical time speed and direction of the target UAV; or

[0047] The plurality of historical time speed is smoothed by using a Kalman filtering method to obtain the current time speed and direction of the target UAV; or

[0048] The plurality of historical time speed is fused by using different weights to obtain the average speed and direction of the target UAV; or

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

[0050] In actual implementation, the embodiment of the application pre-installs all the geographic positioning service devices on the unmanned aerial vehicle, without external equipment, to obtain the historical geographic position and the current geographic position information of the target unmanned aerial vehicle; or only installs the client component on the unmanned aerial vehicle, and relies on the server component on other equipment to obtain the position information. The geographic positioning service includes at least one of GPS, base station, and geomagnetic field positioning.

[0051] Specifically, as shown in Figure 2 The GPS receiver on the unmanned aerial vehicle 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 the receiving time, and then multiplies the speed of light to obtain the distance between the receiver and each satellite. Next, the receiver determines the three-dimensional coordinates (longitude, latitude, and altitude) of the unmanned aerial vehicle and the clock error by solving a set of nonlinear equations. This process may need to be iterated multiple times to obtain a sufficiently accurate result. Once the position is determined, the GPS module transmits this information to the main control system of the unmanned aerial vehicle. The main control system fuses these raw data with the data of other sensors (such as the inertial measurement unit IMU), and uses algorithms such as Kalman filtering to improve the accuracy and reliability of positioning.

[0052] The unmanned aerial vehicle can also use base station positioning, which mainly relies on the signal strength and time difference between the unmanned aerial vehicle and the surrounding mobile communication base stations. Specifically, the unmanned aerial vehicle detects the surrounding base station signals and estimates the distance to each base station according to the received signal strength and time difference. Then, the position of the unmanned aerial vehicle is determined by triangulation. This method works well in cities and other places with dense base stations, but the accuracy is usually not as good as GPS.

[0053] In addition, the unmanned aerial vehicle can also be positioned without external equipment, for example, geomagnetic field positioning uses the changes in the Earth's magnetic field to determine the position. The magnetometer on the unmanned aerial vehicle measures the local magnetic field strength and direction, and then compares these data with the pre-stored geomagnetic field map. By finding the best match, the system can estimate the approximate position of the unmanned aerial vehicle.

[0054] Further, to calculate the kinematic information such as flight speed and direction, the following techniques can be used, including: time difference method, which directly compares the position difference with the time difference to obtain the speed and direction of the target unmanned aerial vehicle at multiple historical moments; Kalman filtering method, which uses a Kalman filter to smooth the speed at multiple historical moments to give the speed and direction at the current moment; hybrid positioning technology, which combines the data of the positioning service system, the 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 unmanned aerial vehicle through an accelerometer and calculates the speed and direction through time integration.

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

[0056]

[0057] Based on the Kalman filtering method, if the error of GPS is considered, Kalman filtering is a suitable real-time state estimation algorithm, assuming that the state of the UAV can be represented as a state vector containing position and speed:

[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 UAV within each time step T can be represented by the following linear model

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

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

[0062]

[0063]

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

[0065] Where (a x ,a y ) is the acceleration. The state vector is mapped to the observation value by the geographic positioning 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 as:

[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 = (I-K k H)P k|k-1

[0078] Through continuous recursion, the Kalman filtering 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 unmanned aerial vehicle can also include the height and the corresponding speed in the direction, and the state transition matrix F, the control input matrix B, the control input u, the process noise w, and the observation noise v all need to be upgraded accordingly.

[0080] Based on the hybrid positioning technology, it involves weighted average or filtering, and the data of multiple sensors are fused through different weights:

[0081] V fused = w1V GPS +w2V IMU +w3V other

[0082] In the above formula, V GPS , V IMU and V other are the speeds calculated according to 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 UAV at time t, which can be obtained by IMU. After obtaining the acceleration of the UAV at any time, numerical integration can be realized by using trapezoidal method or Simpson method:

[0084] V = V initial +∫a(t)dt.

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

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

[0087] In actual implementation process, the configuration information of the wireless light source is calculated to realize the preset safety boundary, which can utilize the following technologies:

[0088] For the position of the wireless light source, the light sources on the lateral fuselage should be uniformly distributed to ensure that all directions on the horizontal plane are covered. In addition, a light source with a wide emission angle should also be installed on the top and bottom of the UAV to broadcast to UAVs at different heights.

[0089] For the azimuth angle of the wireless light source, the UAV may experience yaw, pitch, and roll during flight, and the light source needs to follow the attitude change of the UAV to ensure the accuracy of the forward broadcast. The attitude change of the UAV can be described by Euler angles, and 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 forward direction of the UAV) can be adjusted in real time through this rotation matrix to ensure that the light beam is always aligned with the forward direction of the UAV.

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

[0093]

[0094] where R s is the safety distance between UAVs, d is the nearest distance to other UAVs in the corresponding direction, and α is a coefficient for adjusting the influence of flight speed on beam angle, 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 decrease accordingly, broadcasting forward in a more concentrated manner; when the relative speed of the drone is low, the half-beam angle will increase to cover a wider area.

[0097] The power of the wireless optical source needs to take into account the flight speed of the drone, the relative distance to other drones, and the environmental factors of signal propagation. In order to avoid excessive power waste or insufficient power, power needs to be dynamically allocated. 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, reception 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 For dynamic adjustment, an adjustment factor β can be introduced 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 range 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 assembling 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] Select identification information from the current geographic location information, kinematic information, and self-operation information according to the target transmission requirements, and construct the state information to be transmitted from the identification information, wherein the state information to be transmitted includes at least one of the following: heading, latitude and longitude, altitude, speed, positioning accuracy, speed accuracy, timestamp, drone identification code, remaining battery power, control mode, and latitude and longitude 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 construct the status information to be transmitted, and then organizes 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 physical layer and MAC requirements of standards including but not limited to IIEEE 802.15.7, CCSDS142.0-B-1, GB / T36628.1-2018, and ITU-T G.709.

[0109] The drone's wireless optical signal frame broadcast 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 Figure 1 shows the structure of the message portion of a wireless optical signal frame containing drone identification information, including geographic location, speed, direction, and other optional information. Each row in the figure displays a 32-bit field; one, multiple, or a subset of 8-bit fields can be used to contain the transmitted information. Note that these examples are for illustrative purposes only; other embodiments may have different 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 the 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] Running state and flag bit: 8-bit field, used to indicate the current running state of the UAV, including normal state, emergency state, and running identification function failure state;

[0117] Track angle: 8-bit field, used to indicate the moving direction. For example, using angle degree as unit;

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

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

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

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

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

[0123] Geometric altitude: 16-bit field, used to indicate the current barometric altitude of the UAV, with 1013.25 mbar as reference surface air pressure altitude;

[0124] Height above ground: 16-bit field, used to indicate the current barometric altitude of the UAV, with 1013.25 mbar as reference surface air pressure altitude;

[0125] Position accuracy: 8-bit field, used to indicate the positioning accuracy of the UAV, the first 4 bits represent vertical accuracy and the last 4 bits represent horizontal accuracy;

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

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

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

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

[0130] Battery remaining capacity: 16-bit field, used to indicate the percentage of remaining power of the UAV, in other embodiments, it can also indicate the remaining use time;

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

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

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

[0134] Other information: other control information or identification information of non-data payload.

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

[0136] Wherein, the frequency band of the wireless optical communication includes at least one of the infrared light frequency band, the visible light frequency band and the ultraviolet light frequency band; the light source of the wireless optical communication includes at least one of the light-emitting diode light source and the laser light source; the broadcast means that the UAV transmits the wireless optical signal frame 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, the state information of other UAVs except the target UAV is received to control the target UAV to avoid.

[0138] In actual execution process, the avoidance can be realized through the following key parts:

[0139] Detection range: based on half-duplex or full-duplex mode, each target UAV uses photodiode, photoelectric sensor and other photoelectric detectors to receive the state information of other UAVs except the target UAV, so as to judge the potential collision threat according to the received state information of other UAVs. If other UAVs enter a certain detection range, the UAV will execute the following collision prediction and collision strategy.

[0140] Collision prediction: according to the speed and position of other UAVs, the possible collision time and position are predicted.

[0141] Avoidance strategy: once the collision is detected, the UAV adjusts its speed, direction or height according to certain priority rules and avoidance algorithm to avoid collision.

[0142] For the detection range, when the UAV receives the wireless optical signal of other UAVs, it is considered that there is a potential collision threat, and the collision prediction and collision strategy are executed.

[0143] For collision prediction, each UAV judges whether there is a potential collision risk by calculating the Euclidean distance with other UAVs. Assuming that there are two UAVs A and B, the positions are r A =(x A ,y A ,z A ) and rB = (x B , y B , z B ), then the drones will monitor this distance in real time, their distance d AB = |r AB - r s | = sqrt((x AB - x s )2+ (y AB - y s )2+ (z AB - z s )2

[0144]

[0145] If d AB < R s , the drones will further predict the collision time. Assuming the speed of the two drones are v A and v B , the relative speed v rel = v A - v B between them can be calculated; similarly, the relative position r AB = r A - r B , then the relative speed and relative position are used 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 the avoidance strategy, the drones need to change their motion parameters (speed, direction, or height) to avoid collision. The avoidance strategy can be implemented according to the following methods:

[0149] Horizontal avoidance: the drones prefer to avoid in the horizontal plane. In this case, the direction of the velocity vector can be adjusted to avoid. First, calculate the minimum turning angle Δθ that can avoid collision. Assuming drone A needs to avoid drone B, by adjusting the direction of its velocity vector v A , avoid coinciding with the velocity vector v B of B, the minimum turning angle Δθ can be given by the following formula:

[0150]

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

[0152] High Altitude Avoidance: If horizontal avoidance is difficult to achieve (e.g. multiple drones flying in similar directions), drones can also avoid by adjusting altitude. The amount of altitude adjustment Δz can be calculated based on the current altitude layer and the distance to other drones. A minimum altitude difference Δz = ±H min may be set. Drones can prioritize altitude adjustment according to the altitude layer rules. Generally, drones at higher altitude have priority and do not need to adjust altitude, while drones at lower altitude need to avoid ascending.

[0153] Speed Adjustment: If necessary, drones can also avoid by adjusting the magnitude of speed. By slowing down or speeding up, drones can avoid the time of encounter with other drones. If a drone predicts a collision to occur in a close time, it can slow down to delay the time of encounter and avoid collision. The amount of speed adjustment Δv can be calculated based on the time of collision t col :

[0154] Δv = (d AB -R s ) / (t col )

[0155] On the contrary, if a drone predicts that it can pass by within a safe distance, it can also choose to speed up to leave the potential collision area.

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

[0157] In summary, according to the method for avoiding based on automatic broadcasting of unmanned aerial vehicle identification information by optical communication provided in the embodiments of the present application, the unmanned aerial vehicle can determine the current geographic position according to the information of the geographic positioning service, calculate the kinematics information such as the flight speed and direction in combination with the position information at the historical time, calculate the configuration information of the wireless optical light source to realize the preset safety boundary, assemble various state information to be transmitted into a data frame conforming to the preset frame structure, broadcast the data frame in the space by using the wireless optical light, and avoid according to the received state information of other unmanned aerial vehicles. Therefore, the use of the radio frequency spectrum is avoided, the interference on the existing network is reduced, the safety of data transmission is improved, and the risk of information leakage and eavesdropping is reduced. In addition, the target unmanned aerial vehicle will intelligently avoid obstacles after receiving the state information of other unmanned aerial vehicles, thereby improving the cooperative control performance of the unmanned aerial vehicle cluster, enhancing the real-time monitoring and scheduling capability, and having important significance for constructing a safe and efficient unmanned aerial vehicle system.

[0158] Secondly, the device for avoiding based on automatic broadcasting of unmanned aerial vehicle identification information by optical communication provided in the embodiments of the present application is described with reference to the accompanying drawings.

[0159] Figure 4 A block schematic diagram of the device for avoiding based on automatic broadcasting of unmanned aerial vehicle identification information by optical communication provided in the embodiments of the present application is shown.

[0160] As shown in Figure 4 The device for avoiding based on automatic broadcasting of unmanned aerial vehicle identification information by optical communication 40 includes a calculation module 401, a configuration module 402, a framing module 403, a broadcasting module 404, and an avoiding module 405.

[0161] The calculation module 401 is configured to obtain the current geographic position information of the target unmanned aerial vehicle, and calculate the kinematics information of the target unmanned aerial vehicle in combination with the historical geographic position information. The configuration module 402 is configured to calculate the configuration information of the wireless optical light source of the target unmanned aerial vehicle according to the kinematics information, so as to set the communication boundary of the wireless optical light source by using the configuration information. The framing module 403 is configured to construct the state information to be transmitted, and assemble the state information to be transmitted into a data frame conforming to the preset frame structure. The broadcasting module 404 is configured to control the wireless optical light source to broadcast the data frame in the space based on the configuration information of the wireless optical light source. The avoiding module 405 is configured to receive the state information of other unmanned aerial vehicles except the target unmanned aerial vehicle, so as to control the target unmanned aerial vehicle to avoid according to the state information.

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

[0163] obtaining the current geographic position information of the target unmanned aerial vehicle by using the geographic positioning service;

[0164] The historical geographical position information and the current geographical position information are processed by using a time domain difference method to obtain a plurality of historical time speed and direction of the target UAV; or

[0165] The plurality of historical time speed is smoothed by using a Kalman filtering method to obtain the current time speed and direction of the target UAV; or

[0166] The plurality of historical time speed is fused by using different weights to obtain the average speed and direction of the target UAV; or

[0167] The acceleration of the target UAV at any time is measured by using an accelerometer, and the current acceleration is numerically integrated by using an 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 position, azimuth angle, half-beam angle, and power allocation.

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

[0170] The acquisition unit is configured to acquire the self-running information of the target UAV.

[0171] The selection unit is configured to select the identification information from the current geographical position information, kinematic information, and self-running information according to the target transmission requirement, and construct the to-be-transmitted state information from the identification information, wherein the to-be-transmitted state information includes at least one of the forward direction, latitude and longitude, height, speed, positioning accuracy, speed accuracy, time stamp, UAV identification code, battery remaining capacity, control mode, and UAV control station latitude and longitude.

[0172] The assembly unit is configured to assemble the to-be-transmitted state information into a data frame conforming to a preset frame structure.

[0173] In some embodiments, the preset frame structure should conform to at least one of the standards for physical layer and MAC requirements including but not limited to IEEE 802.15.7, CCSDS 142.0-B-1, GB / T 36628.1-2018, ITU-T G.709, etc.

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

[0175] Based on the half-duplex or full-duplex mode, the state information of the UAV other than the target UAV is received by using a photodetector.

[0176] It should be noted that the foregoing explanation and description of the embodiment of the avoidance method based on automatic broadcasting of UAV identification information by optical communication also apply to the embodiment of the avoidance device based on automatic broadcasting of UAV identification information by optical communication, which will not be described here again.

[0177] According to the avoidance device based on automatic broadcasting of unmanned aerial vehicle identification information by optical communication provided by the embodiment of the application, the unmanned aerial vehicle can determine the current geographical position according to the information of the geographical positioning service, calculate the kinematic information such as the flight speed and direction in combination with the position information at the historical moment, calculate the configuration information of the wireless light source to realize the preset safety boundary, assemble various state information to be transmitted into a data frame conforming to the preset frame structure, broadcast the above data frame to the space by using the wireless light, and avoid according to the received state information of other unmanned aerial vehicles. Therefore, the use of the radio frequency spectrum is avoided, the interference on the existing network is reduced, the safety of data transmission is improved, and the risk of information leakage and eavesdropping is reduced. In addition, the target unmanned aerial vehicle will intelligently avoid obstacles after receiving the state information of other unmanned aerial vehicles, thereby improving the cooperative control performance of the unmanned aerial vehicle cluster, enhancing the real-time monitoring and scheduling capability, and having important significance for constructing a safe and efficient unmanned aerial vehicle system.

[0178] Figure 5 The electronic device provided by the embodiment of the application is shown in the structural schematic diagram. The electronic device can include:

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

[0180] The processor 502 implements the avoidance method based on automatic broadcasting of unmanned aerial vehicle identification information by optical communication provided by the above embodiment when executing the program.

[0181] Further, the electronic device further includes:

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

[0183] The memory 501 is used for storing the computer program executable on the processor 502.

[0184] The memory 501 can include a high-speed RAM memory, and can also include a 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 with each other through a bus and complete communication between 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, etc. The bus can be divided into an address bus, a data bus, a control bus, etc. For convenience of representation, Figure 5 Only one thick line is used in the figure to represent the bus, but it 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 complete communication between each other through an internal interface.

[0187] The processor 502 can be a Central Processing Unit (CPU), or an Application Specific Integrated Circuit (ASIC), or one or more integrated circuits configured to implement embodiments of the present application.

[0188] The embodiment of the present application further provides a computer program product, and the computer program / instruction is executed by the processor to realize the above-mentioned unmanned aerial vehicle avoidance method based on automatic broadcasting of identification information through optical communication.

[0189] The embodiment of the present application further provides a computer readable storage medium, and the computer readable storage medium stores a computer program, and the program is executed by the processor to realize the above-mentioned unmanned aerial vehicle avoidance method based on automatic broadcasting of identification information through optical communication.

[0190] In the description of the application, reference to "one embodiment", "some embodiments", "an example", "a specific example", or "some examples" means that a particular feature, structure, material, or characteristic being described is included in at least one embodiment or example of the application. The appearances of the phrase in various places in the specification are not necessarily all referring to the same embodiment or example. Furthermore, the described specific features, structures, materials, or characteristics can be combined in any suitable manner in one or more embodiments or examples. In addition, the usage of "first", "second" and the like does not indicate any order but rather serves merely to name various components. Moreover, the usage of "top", "bottom", and the like is made for the purpose of illustration only and does not indicate any orientation. The terms "coupled" and "connected", along with their derivatives, can be used. It should be understood that these terms are not intended as synonyms for each other. Rather, particular features are described as being coupled or connected where the feature is in some way present, for example through shared use of one or more components, and can be communicatively, electrically, structurally, and / or mechanically connected, for example. Similarly, "coupled" or "connected" can be used to indicate that two or more members are either directly in contact or indirectly in contact through one or more intermediate members.

[0191] Furthermore, the terms "first", "second", and the like, merely denote different categories, and do not imply a relative importance or a specific order. Thus, features defined with "first", "second" and the like can include at least one of the features, either explicitly or implicitly. In the description of the application, the term "N" means at least two, for example two, three, etc., unless explicitly specified otherwise.

[0192] Any process or method descriptions or blocks in flow charts or otherwise described herein represent embodiments of modules, segments, or portions of code which include one or more executable instructions for implementing specific logical functions or steps, and alternate implementations are possible. In some embodiments, the processes or methods described can be accomplished with one or more hardware items, for example, hardwired circuits, memory, logic circuits, look-up tables, microcode or the like, software programs, firmware programs, microcode routines, embedded logic, embedded software, or any combination thereof, which work together to cause a general purpose computer, a special purpose computer, or both, to perform the processes or methods described. The various embodiments further can interact with a user through one or more computer programs, software applications, firmware applications, operating systems, or the like, which interact with a user. Such software can be written in any of a variety of suitable programming languages and can be executed using a variety of suitable hardware and software configurations. It will be appreciated that computer programs, software applications, firmware applications, operating systems, or the like, can be written in any combination of one or more suitable programming languages, and that such software can be executed using one or more computing devices capable of netlist generation as described herein.

[0193] The logic and / or steps represented in flow diagrams or otherwise described herein, for example, can be considered as a sequence of instructions to implement logic functions, and can be embodied in any computer-readable medium for use by an instruction execution system, apparatus, or device, such as a computer-based system, processor- containing system, or other system that can fetch the instructions from the instruction execution system, apparatus, or device and execute the instructions. In the context of this specification, a "computer-readable medium" can be any means that can contain, store, communicate, propagate or transport the program for use by or in connection with the instruction execution system, apparatus, or device. The computer-readable medium can be a machine-readable storage device (e.g., magnetic, optical or other) a machine-readable storage diskette (e.g., floppy, flexible or other), a machine-readable storage card (e.g., ROM, EEPROM, flash memory or other), a machine- readable storage tape (e.g., magnetic, optical or other), a machine-readable storage medium (e.g., a portable electronic device, a computer diskette, a computer memory, a programmable logic device, an application-specific integrated circuit, a programmable logic controller, a digital signal processor, a microprocessor, a microprocessor array or other), or a machine- readable interface device (e.g., a wired or wireless interface device). The computer-readable medium can also be paper or other suitable material upon which the program is printed, as the program can be electronically captured, via optical scanning of the paper or other suitable medium, then compiled, interpreted or otherwise processed in a suitable manner into a useable format for use in the computer memory.

[0194] It should be understood that aspects of the application can be implemented in hardware, software, firmware or combinations thereof. In the above embodiments, the N steps or methods can be implemented in software or firmware stored in a memory and executed by a suitable instruction execution system. If implemented in hardware and in another embodiment, any of the following technologies, known in the art, or combinations thereof, can be used: discrete logic circuitry having logic gates for implementing logic functions on data signals, application specific integrated circuits having appropriate combinational logic gates, programmable gate arrays (PGA), field programmable gate arrays (FPGA), and the like.

[0195] Those of ordinary skill in the art can understand that all or part of the steps carried out by the above-mentioned embodiment methods can be completed by programs instructing relevant hardware, and the programs can be stored in a computer-readable storage medium. When the programs are executed, they include one of the steps of the method embodiments or a combination thereof.

[0196] In addition, each function unit in each embodiment of the present application can be integrated in one processing module, or each unit can be physically present separately, or two or more units can be integrated in one module. The integrated module can be realized in the form of hardware or in the form of a software function module. When the integrated module is realized in the form of a software function module and sold or used as an independent product, it can also be stored in a computer readable storage medium.

[0197] The storage medium mentioned above can be a read-only memory, a magnetic disk or an optical disk, etc. Although the embodiments of the present application have been shown and described above, it should be understood that the above embodiments are exemplary and should not be construed as limiting the present application, and those skilled in the art can make changes, modifications, replacements and variations to the above embodiments within the scope of the present application.

Claims

1. A method for automatic broadcasting of information for avoiding unmanned aerial vehicles based on optical communication, characterized in that, The method comprises the following steps: acquiring current geographic position information of a target UAV and calculating kinematic information of the target UAV in combination with historical geographic position information; calculating configuration information of a wireless light source of the target UAV according to the kinematic information, so as to set a communication boundary of the wireless light source through the configuration information; constructing to-be-transmitted state information and assembling the to-be-transmitted state information into a data frame conforming to a preset frame structure; controlling the wireless light source to broadcast the data frame into space based on the configuration information of the wireless light source; receiving state information of other UAVs except the target UAV, so as to control the target UAV to avoid according to the state information.

2. The method according to claim 1, wherein The acquiring current geographic position information of a target UAV and calculating kinematic information of the target UAV in combination with historical geographic position information comprises: acquiring current geographic position information of a target UAV by using a geographic positioning service; processing the historical geographic position information and the current geographic position information by using a time domain difference method to obtain a plurality of historical time speed and direction of the target UAV; or smoothing the plurality of historical time speed by using a Kalman filtering method to obtain a current time speed and direction of the target UAV; or fusing the plurality of historical time speed by using different weights to obtain an average speed and direction of the target UAV; or measuring acceleration of the target UAV at any time by using an accelerometer, and performing numerical integration on the current acceleration by using an acceleration integration method to obtain instantaneous speed and direction of the target UAV. 3.The method of claim 1, wherein, The configuration information comprises at least one of position, azimuth angle, half-beam angle, and power distribution. 4.The method of claim 1, wherein, The constructing to-be-transmitted state information and assembling the to-be-transmitted state information into a data frame conforming to a preset frame structure comprises: collecting self-running information of the target UAV; selecting identification information from the current geographic position information, the kinematic information and the self-running information according to target transmission requirements, and constructing the identification information to to-be-transmitted state information, wherein the to-be-transmitted state information comprises at least one of forward direction, latitude and longitude, height, speed, positioning accuracy, speed accuracy, time stamp, UAV identification code, battery remaining capacity, control mode, and UAV control station latitude and longitude; assembling the to-be-transmitted state information into a data frame conforming to the preset frame structure. 5.The method of claim 4, wherein, The preset frame structure should conform to at least one of standards for physical layer and MAC requirements including but not limited to IEEE 802.15.7, CCSDS 142.0-B-1, GB / T 36628.1-2018, and ITU-T G.

709. 6.The method of claim 1, wherein, The receiving state information of other UAVs except the target UAV comprises: receiving state information of other UAVs except the target UAV by using a photoelectric detector in a half-duplex or full-duplex manner.

7. An automatic avoidance device based on optical communication unmanned aerial vehicle identification information automatic broadcast, characterized in that, The method comprises: a calculation module for acquiring current geographic position information of a target UAV and calculating kinematic information of the target UAV in combination with historical geographic position information; The configuration module is configured to calculate configuration information of a 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. The framing module is configured to construct to-be-transmitted state information, and frame the to-be-transmitted state information into a data frame conforming to a preset frame structure. The broadcasting module is configured to control the wireless optical light source to broadcast the data frame in space based on the configuration information of the wireless optical light source. The avoidance module is configured to receive state information of other UAVs except the target UAV, and control the target UAV to avoid according to the state information.

8. An electronic device, comprising: The computer program / instructions are executed by the processor to implement the avoidance method based on automatic broadcasting of identification information of the UAV based on optical communication according to any one of claims 1-6. The computer program / instructions are executed by the processor to implement the avoidance method based on automatic broadcasting of identification information of the UAV based on optical communication according to any one of claims 1-6.

9. A computer program product, characterised in that, The program is executed by the processor to implement the avoidance method based on automatic broadcasting of identification information of the UAV based on optical communication according to any one of claims 1-6.

10. A computer-readable storage medium having stored thereon a computer program, characterized in that, ​

Images