Unmanned aerial vehicle positioning method, system and program product based on wireless positioning beacons

Abstract

The invention provides an unmanned aerial vehicle positioning method and system based on a wireless positioning beacon and a program product, and relates to the technical field of unmanned aerial vehicle positioning, and the unmanned aerial vehicle positioning method comprises the steps: obtaining the first position information of the wireless positioning beacon, the second position information of an unmanned aerial vehicle, and the measurement azimuth angle information of the unmanned aerial vehicle relative to the wireless positioning beacon; based on the first position information and the second position information, calculating azimuth angle information of the unmanned aerial vehicle relative to the wireless positioning beacon is determined; determining corrected azimuth angle information of the unmanned aerial vehicle relative to the wireless positioning beacon based on the measured azimuth angle information and the calculated azimuth angle information; and determining relative position information between the unmanned aerial vehicle and the wireless positioning beacon based on the corrected azimuth angle information.

Description

Technical Field

[0001] This specification relates to the field of drone positioning technology, and in particular to a drone positioning method, system, and program product based on wireless positioning beacons. Background Art

[0002] Drones typically require wireless positioning beacons for positioning in close-range scenarios (such as automatic following and formation flying). Because both drones and wireless positioning beacons typically use satellite positioning systems to obtain their respective positioning information, and satellite positioning systems have inherent positioning errors (typical positioning errors are usually in the range of 2 to 5 meters), close-range scenarios can easily cause relative position offsets and / or relative orientation errors between the drone and the wireless positioning beacon, affecting the drone's precise navigation and flight safety in these scenarios.

[0003] In view of this, some embodiments of this specification provide a drone positioning method, system and program product based on wireless positioning beacons, which can determine the relative position information between the drone and the wireless positioning beacon based on the corrected azimuth information of the drone relative to the wireless positioning beacon, thereby improving the positioning accuracy of the drone in close-range scene applications. Summary of the Invention

[0004] One or more embodiments of the present specification provide a method for positioning a drone based on a wireless positioning beacon, the method comprising: obtaining first position information of the wireless positioning beacon, second position information of the drone, and measured azimuth information of the drone relative to the wireless positioning beacon; determining calculated azimuth information of the drone relative to the wireless positioning beacon based on the first position information and the second position information; determining corrected azimuth information of the drone relative to the wireless positioning beacon based on the measured azimuth information and the calculated azimuth information; and determining the relative position information between the drone and the wireless positioning beacon based on the corrected azimuth information.

[0005] In some embodiments, the wireless positioning beacon periodically sends a beacon signal to the drone; obtaining the measured azimuth information of the drone relative to the wireless positioning beacon includes: based on the array antenna module carried by the drone, obtaining the time difference and / or phase difference of each antenna element in the array antenna module receiving the beacon signal; based on the time difference and / or phase difference, determining the measured azimuth information of the drone relative to the wireless positioning beacon.

[0006] In some embodiments, the array antenna module includes a plurality of antenna elements extending along a first direction and a second direction, and the first direction and the second direction are perpendicular to each other; the spacing between two adjacent antenna elements in the first direction is less than or equal to one-quarter of the signal wavelength corresponding to the beacon signal; the spacing between two adjacent antenna elements in the second direction is less than or equal to one-quarter of the signal wavelength.

[0007] In some embodiments, the number of antenna elements in the first direction is the same as the number of antenna elements in the second direction; and / or the spacing between two adjacent antenna elements in the first direction is the same as the spacing between two adjacent antenna elements in the second direction.

[0008] In some embodiments, the first location information of the wireless positioning beacon is determined based on a satellite positioning system; and / or the second location information of the drone is determined based on a satellite positioning system.

[0009] In some embodiments, obtaining the second position information of the drone includes: determining the initial position information of the drone during operation based on a satellite positioning system; obtaining motion attitude correction information of the drone during operation based on an inertial measurement module carried by the drone; and / or obtaining position drift correction information of the drone during operation based on a magnetometer module carried by the drone; based on the motion attitude correction information and / or position drift correction information, correcting the initial position information to determine the second position information.

[0010] In some embodiments, based on the measured azimuth information and the calculated azimuth information, the corrected azimuth information of the drone relative to the wireless positioning beacon is determined, including: determining the relative distance value of the drone relative to the wireless positioning beacon based on the first position information and the second position information; determining the first fusion weight corresponding to the measured azimuth information and the second fusion weight corresponding to the calculated azimuth information based on the relative distance value; and performing weighted fusion on the measured azimuth information and the calculated azimuth information based on the first fusion weight and the second fusion weight to determine the corrected azimuth information.

[0011] In some embodiments, the weight value of the first fusion weight is negatively correlated with the relative distance value; and / or the weight value of the second fusion weight is positively correlated with the relative distance value.

[0012] In some embodiments, the method further includes: obtaining a measured distance value between the wireless positioning beacon and the drone; determining a relative error vector of the drone relative to the wireless positioning beacon based on the measured distance value, the first position information, and the second position information; and determining the relative position information between the drone and the wireless positioning beacon based on the relative error vector and / or the corrected azimuth information.

[0013] In some embodiments, based on the measured distance value, the first position information and the second position information, the relative error vector of the drone relative to the wireless positioning beacon is determined, including: determining the calculated distance vector of the drone relative to the wireless positioning beacon based on the first position information and the second position information; establishing an objective function associated with the relative error vector; optimizing the objective function using a nonlinear optimization algorithm based on the measured distance value and the calculated distance vector, and determining the relative error vector based on the optimized objective function.

[0014] In some embodiments, the objective function is associated with the difference between the modulus of the calculated distance vector after correction by the relative error vector and the measured distance value; optimizing the objective function using a nonlinear optimization algorithm includes: adjusting the relative error vector so as to minimize the difference between the modulus of the calculated distance vector after correction by the adjusted relative error vector and the measured distance value.

[0015] One or more embodiments of the present specification also provide a UAV positioning system based on a wireless positioning beacon, the system comprising: a position acquisition module for acquiring first position information of the wireless positioning beacon, second position information of the UAV, and measured azimuth information of the UAV relative to the wireless positioning beacon; an azimuth acquisition module for determining calculated azimuth information of the UAV relative to the wireless positioning beacon based on the first position information and the second position information; an azimuth correction module for determining corrected azimuth information of the UAV relative to the wireless positioning beacon based on the measured azimuth information and the calculated azimuth information; and a relative position correction module for determining the relative position information between the UAV and the wireless positioning beacon based on the corrected azimuth information.

[0016] Some embodiments of this specification also provide a computer program product, including computer instructions or a computer program. When at least part of the computer instructions or computer program is executed by a processor, it can implement the drone positioning method based on wireless positioning beacons provided in any embodiment of this specification. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] This specification will be further described in the form of exemplary embodiments, which will be described in detail with reference to the accompanying drawings. The same numbers in the drawings represent the same structures or steps.

[0018] Figure 1 This is a schematic diagram of a drone application scenario based on wireless positioning beacons according to some embodiments of this specification.

[0019] Figure 2 This is an exemplary flow chart of a method for positioning a UAV based on a wireless positioning beacon according to some embodiments of this specification.

[0020] Figure 3This is an exemplary flowchart of determining the second position information of a drone according to some embodiments of this specification.

[0021] Figure 4 This is an exemplary flowchart for obtaining the measured azimuth information of a drone relative to a wireless positioning beacon according to some embodiments of this specification.

[0022] Figure 5 This is a structural diagram of an array antenna module according to some embodiments of this specification.

[0023] Figure 6 This is a structural diagram of another array antenna module according to some embodiments of this specification.

[0024] Figure 7 This is an exemplary flow chart of determining the corrected azimuth information of a drone relative to a wireless positioning beacon according to some embodiments of this specification.

[0025] Figure 8 This is an exemplary flowchart of another drone positioning method based on wireless positioning beacons according to some embodiments of this specification.

[0026] Figure 9 This is an exemplary flowchart of determining the relative error vector of a drone relative to a wireless positioning beacon according to some embodiments of this specification.

[0027] Figure 10 This is a functional module diagram of a UAV positioning system based on wireless positioning beacons according to some embodiments of this specification. DETAILED DESCRIPTION

[0028] To more clearly illustrate the technical solutions of the embodiments of this specification, the embodiments will be described in detail below with reference to the accompanying drawings. Obviously, the following descriptions are some examples or embodiments of this specification, and those skilled in the art can apply the technical solutions or methods disclosed in this specification to other scenarios based on these technical contents without inventive effort.

[0029] It should be understood that the terms "system," "device," "unit," and / or "module" used in this specification are a method for distinguishing different components, elements, parts, portions, or assemblies at different levels. However, if other terms can achieve the same purpose, the above terms can be replaced by other expressions.

[0030] Unless otherwise specified, technical terms used in this specification to describe components, elements, and the like do not necessarily refer to the singular but may include the plural. Generally speaking, terms such as "include" and "comprising" only indicate the inclusion of the steps, elements, or components specifically identified, and these steps, elements, and components do not constitute an exclusive list. For example, the method or device being described may also include other steps or components.

[0031] This specification uses flowcharts to illustrate the operational steps performed by the devices or systems of the relevant embodiments. However, unless otherwise specified, the order in which these steps are described should not be construed as limiting the order in which the steps are performed. A person of ordinary skill in the art may adjust the order in which these steps are performed based on the knowledge and information conveyed by the embodiments of this specification. Such adjustments include, but are not limited to, reversing the order of the steps, combining multiple steps, and splitting a step.

[0032] Drones usually need to cooperate with wireless positioning beacons for positioning in close-range scene applications (such as automatic following, formation flying, etc.). Since drones and wireless positioning beacons usually use satellite positioning systems to obtain their respective positioning information, and satellite positioning systems have inherent positioning errors (typical positioning errors are usually in the range of 2 to 5 meters), it is easy to cause relative position offsets and / or relative orientation errors between drones and wireless positioning beacons in close-range scene applications, affecting the precise navigation and flight safety of drones in close-range scene applications. In view of this, this specification provides a drone positioning method, system and program product based on wireless positioning beacons.

[0033] Figure 1 This is a schematic diagram of a drone application scenario based on wireless positioning beacons according to some embodiments of this specification. In some embodiments, Figure 1 As shown, the drone application scenario 100 based on wireless positioning beacons may include a wireless positioning beacon 110, a drone 120, a processing device 130, a network 140 and a terminal device 150, wherein the wireless positioning beacon 110, the drone 120, the processing device 130 and the terminal device 150 can perform data transmission and communication interaction through the network 140.

[0034] In some embodiments, the wireless positioning beacon 110 is a wireless device used to assist in positioning and / or achieve object tracking, and provides its own location information by emitting specific wireless signals (such as specific radio frequency signals, Bluetooth wireless signals, ultra-wideband wireless signals, etc.). In some embodiments, the wireless positioning beacon 110 can be fixed, and a reference positioning system for relative position reference positioning of the drone 120 can be established by setting one or more wireless positioning beacons 110. In some embodiments, the wireless positioning beacon 110 can also be a mobile device that can be handheld and moved by the user, or a wearable mobile device that can be worn by the user (such as a wearable positioning bracelet, etc.), which is used to provide continuously updated location information to the drone 120 for the drone to follow the flight reference, which is not limited here.

[0035] In some embodiments, the drone 120 can cooperate with the wireless positioning beacon 110 for positioning and / or flight trajectory planning in close-range scenarios. For example, in a specific embodiment, in a close-range scenario where the drone 120 automatically follows, the moving wireless positioning beacon 110 can be used as the drone's tracking target. The drone 120 can obtain reference position information provided by the wireless positioning beacon 110 through a communication connection with the wireless positioning beacon 110, and use the drone 120's own positioning information to plan and adjust the drone 120's following path in real time. For another example, in a close-range scenario where drones fly in formation, a reference positioning system can be established based on the locations of one or more wireless positioning beacons 110. The drone 120 can obtain reference position information provided by the wireless positioning beacon 110 through a communication connection with the one or more wireless positioning beacons 110, and use the drone 120's own positioning information to determine whether the drone 120 is in the predetermined position for formation flight. The drone 120 can then be guided to move to the predetermined position for formation flight based on the reference position information provided by the wireless positioning beacon 110.

[0036] In some embodiments, the processing device 130 may be a computer device with high computing performance, configured to determine the relative position information of the drone 120 relative to the wireless positioning beacon 110 based on the positioning information provided by the wireless positioning beacon 110 and the drone 120. In some embodiments, the processing device 130 may be a single computer device or a computing cluster composed of multiple computer devices, thereby providing powerful computing power and efficient response for determining the relative position information of the drone 120 relative to the wireless positioning beacon 110. In some embodiments, the processing device 130 may be a server, which may be an independent physical server, a server cluster or a distributed system composed of multiple physical servers, or a cloud server that provides basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communications, middleware services, domain name services, security services, CDN (Content Distribute Network), and big data and artificial intelligence platforms.

[0037] In some embodiments, network 140 may be any form of wired or wireless network, or any combination thereof. By way of example only, network 140 may be one or more combinations of a wired network, a fiber optic network, a telecommunications network, an intranet, the Internet, a local area network (LAN), a wide area network (WAN), a wireless local area network (WLAN), a metropolitan area network (MAN), a wide area network (WAN), a public switched telephone network (PSTN), a Bluetooth network, and the like. Network 140 may have multiple access points, through which wireless location beacons 110, drones 120, processing devices 130, and terminal devices 150 may access network 130.

[0038] In some embodiments, the terminal device 150 may include, but is not limited to, a desktop computer, a smartphone, a laptop computer, a VR (Virtual Reality) device, and a tablet computer. A user can view the relative position information of the drone 120 relative to the wireless positioning beacon 110 and plan the flight trajectory of the drone 120 on the terminal device 150, without limitation.

[0039] It should be noted that Figure 1The drone positioning application scenario 100 using a wireless positioning beacon is merely an example. The scenario described in the embodiments of this specification is intended to more clearly illustrate the technical solutions of the embodiments of this specification and does not constitute a limitation on the technical solutions provided in the embodiments of this specification. A person skilled in the art will appreciate that the technical solutions provided in the embodiments of this specification are also applicable to similar technical problems. For example, in some application scenarios, the wireless positioning beacon 110 and the processing device 130 can be integrated into one device, and the user can automatically follow and guide the drone by holding the device. In some application scenarios, the wireless positioning beacon 110, the processing device 130, and the terminal device 150 can also be integrated into one device. In some application scenarios, the processing device 130 can be integrated into the drone 120 or the terminal device 150, which is not limited here.

[0040] Figure 2 is an exemplary flow chart of a method for positioning a UAV based on a wireless positioning beacon according to some embodiments of this specification. In some embodiments, Figure 2 The process 200 shown can be executed by the processing device 130. In some embodiments, the process 200 can be implemented by the wireless positioning beacon-based drone positioning system 400 deployed on the processing device 130. In some embodiments, Figure 2 As shown, the process 200 may include the following steps.

[0041] Step 210: Acquire the first location information of the wireless positioning beacon, the second location information of the drone, and the measured azimuth information of the drone relative to the wireless positioning beacon. In some embodiments, step 210 can be implemented by the location acquisition module 1010.

[0042] In some embodiments, a communication connection is established between the drone and the wireless positioning beacon, so that the drone can obtain the reference position information provided by the wireless positioning beacon and plan and / or adjust its own flight trajectory based on the reference position information. In some embodiments, a communication connection is established between the drone and the wireless positioning beacon, and the drone can feed back the reference position information provided by the wireless positioning beacon to the drone's remote control system, and the remote control system plans and / or adjusts the drone's flight trajectory. In some embodiments, the drone's remote control system can directly establish a communication connection with the wireless positioning beacon so that the remote control system can plan and / or adjust the drone's flight trajectory based on the reference position information provided by the wireless positioning beacon. In some embodiments, the wireless positioning beacon may include a Bluetooth positioning beacon, and a Bluetooth communication connection is established between the drone and the Bluetooth positioning beacon. In some embodiments, those skilled in the art can realize the communication connection between the drone and the wireless positioning beacon through WIFI communication connection, UWB (Ultra-Wideband) communication connection, millimeter wave communication connection (for example, using 60GHz millimeter wave, etc.), etc., according to the permission and needs of the actual application scenario. The millimeter wave communication connection is particularly suitable for the deployment scenario of miniaturized drones, which is not limited here.

[0043] In some embodiments, the measured azimuth information of the drone relative to the wireless positioning beacon can be achieved through millimeter wave communication between the drone and the wireless positioning beacon, wherein millimeter waves are electromagnetic waves between microwaves and light waves, propagating in space in the form of direct waves, with a narrow beam and good directionality, less interference sources, and a stable and reliable propagation process. In some embodiments, the frequency band of millimeter wave communication is in the range of 30GHz to 300GHz, and the corresponding millimeter wave wavelength is in the range of 1mm to 10mm. For example, a 60GHz millimeter wave can be used to achieve millimeter wave communication between the drone and the wireless positioning beacon and obtain the measured azimuth information. In some embodiments, a millimeter wave transmitter can be set on the wireless positioning beacon (or drone), and a millimeter wave receiver can be set on the drone (or wireless positioning beacon). The acquisition of the measured azimuth information of the drone relative to the wireless positioning beacon is achieved by receiving the millimeter waves of a preset frequency band emitted by the millimeter wave transmitter. In some embodiments, the sizes of the millimeter wave transmitting end and the millimeter wave receiving end are relatively small. For example, the length and width of a 60GHz rectangular millimeter wave receiving end can be in the range of a dozen millimeters to several millimeters (for example, the length and width can be 18.5 mm * 6.5 mm, etc., which are not limited here), which is particularly suitable for the deployment and application scenarios of miniaturized drones.

[0044] In some embodiments, the first location information of the wireless positioning beacon can be obtained periodically or irregularly when the wireless positioning beacon is in a working state. In some embodiments, the first location information of the wireless positioning beacon can be determined based on a satellite positioning system. For example, the wireless positioning beacon can be equipped with a receiver module that can receive broadcast signals of a satellite positioning system. The receiver module receives broadcast signals with its own location information and broadcast time information broadcast by different satellites in the satellite positioning system, and calculates and determines the first location information of the wireless positioning beacon using the time difference of the broadcast signals received from each satellite. In some embodiments, the first location information of the wireless positioning beacon can be obtained by one or any combination of satellite positioning systems such as the GPS (Global Positioning System) satellite positioning system, the Beidou satellite navigation system, the Galileo satellite positioning system, and the GLONASS (Global Navigation Satellite System) satellite navigation system. Those skilled in the art can also use other available satellite positioning systems to obtain the first location information of the wireless positioning beacon, which is not limited here. In some embodiments, there is a first positioning error between the first location information determined based on the satellite positioning system and the actual location information of the wireless positioning beacon in the real environment. The first positioning error may be caused by interference of the broadcast signal by the atmosphere or other environmental factors during the transmission from the satellite to the wireless positioning beacon; it may also be caused by error factors such as the small number of satellites included in the satellite positioning system, the clock asynchrony between the atomic clocks of different satellites and the internal clock of the wireless positioning beacon, satellite orbit error, etc., which are not limited here. It is understandable that the error factors that cause the first positioning error include environmental error factors, system error factors corresponding to the satellite positioning system, and system error factors corresponding to the wireless positioning beacon. These error factors are often difficult to completely overcome during the actual use of the wireless positioning beacon, resulting in the first positioning error being unable to be completely eliminated in actual application scenarios. In some embodiments, the positioning accuracy of the first location information determined based on the satellite positioning system is generally in the range of meters to ten meters, that is, the deviation between the first location information determined by the satellite positioning system and the actual location information of the wireless positioning beacon in the real environment is generally in the range of one meter to ten meters.

[0045] In some embodiments, the drone's second location information can be determined based on a satellite positioning system. For example, the drone can be equipped with a receiver module capable of receiving broadcast signals from a satellite positioning system. The receiver module receives broadcast signals containing its own location information and broadcast time information from different satellites in the satellite positioning system, and calculates and determines the drone's second location information using the time difference between the received broadcast signals from each satellite. In some embodiments, the drone's second location information can also be obtained using one or any combination of satellite positioning systems such as the GPS satellite positioning system, the Beidou satellite navigation system, the Galileo satellite positioning system, and the GLONASS satellite navigation system. Persons skilled in the art may also use other available satellite positioning systems to obtain the drone's second location information, without limitation. In some embodiments, the second location information determined based on the satellite positioning system may have a second positioning error compared to the drone's actual location information in a real-world environment. This second positioning error may be caused by atmospheric or other environmental factors during the broadcast signal's transmission from the satellite to the wireless positioning beacon; it may also be caused by factors such as the small number of satellites included in the satellite positioning system, clock asynchrony between the atomic clocks of different satellites and the internal clock of the wireless positioning beacon, and satellite orbit errors, without limitation. It is understandable that the error factors that lead to the second positioning error include environmental error factors, system error factors corresponding to the satellite positioning system, and system error factors corresponding to the drone. These error factors are often difficult to completely overcome during the actual use of the drone, resulting in the second positioning error being unable to be completely eliminated in actual application scenarios. In some embodiments, the positioning accuracy of the second position information determined by the satellite positioning system is generally in the range of meters to ten meters, that is, the deviation between the second position information determined by the satellite positioning system and the actual position information of the drone in the real environment is generally in the range of one meter to ten meters.

[0046] In order to further improve the accuracy of obtaining the second position information of the drone, Figure 3 is an exemplary flow chart of determining the second position information of a drone according to some embodiments of this specification. In some embodiments, Figure 3 As shown, the process 300 may include the following steps.

[0047] Step 310: Determine the initial position information of the UAV during operation based on the satellite positioning system.

[0048] In some embodiments, taking into account the positioning error of the satellite positioning system, the positioning position of the drone determined based on the satellite positioning system can be used as the initial position information, and the initial position information can be further corrected through subsequent steps of process 300 to obtain second position information with higher positioning accuracy.

[0049] Step 320: Based on the inertial measurement module carried by the drone, obtain motion attitude correction information of the drone during operation; and / or based on the magnetometer module carried by the drone, obtain position drift correction information of the drone during operation.

[0050] In some embodiments, the inertial measurement unit (IMU) carried by the drone may include multiple sensor components such as accelerometers and gyroscopes, which can obtain the motion state and position changes of the drone during operation. The accelerometer component can be used to measure the linear acceleration of the drone in the three axial directions. By integrating the measured linear acceleration, the speed and position changes of the drone can be calculated. The gyroscope component can be used to measure the angular velocity information of the drone. By integrating the measured angular velocity, the changes in the attitude information of the drone (such as pitch attitude, roll attitude, yaw angle, etc.) can be calculated. In some embodiments, the motion state and position changes of the drone during operation can be used as motion attitude correction information to correct the initial position information obtained based on the satellite positioning system.

[0051] In some embodiments, a magnetometer module onboard a drone can be used to measure the strength and direction of the Earth's magnetic field. This provides magnetic field data in three-dimensional space to determine the drone's heading (or heading). This data can then be used to correct the initial position information obtained from a satellite positioning system while the drone is in motion. In some embodiments, the drone can also utilize its own inertial measurement module and magnetometer module to simultaneously obtain motion attitude correction information and position drift correction information during operation, without limitation.

[0052] Step 330: Based on the motion posture correction information and / or the position drift correction information, correct the initial position information to determine the second position information.

[0053] In some embodiments, when the positioning position of the drone obtained based on the satellite positioning system moves from a first position to a second position, the change of the drone from the first position to the second position can be adjusted through motion posture correction information and / or position drift correction information, thereby correcting the positioning error existing in the satellite positioning system, so that the second position information determined after correction can be closer to the actual position of the drone, reducing the positioning error caused by the satellite positioning system.

[0054] In some embodiments, in order to further improve the accuracy of obtaining the second position information of the drone, a Differential Global Positioning System (DGPS) algorithm or a Real-Time Kinematic (RTK) algorithm can be used to obtain the second position information of the drone with higher positioning accuracy based on the satellite positioning system. In some embodiments, the DGPS algorithm can use a fixed base station set up on the ground to receive the broadcast signal sent by the satellite positioning system, compare the known base station position information with the base station positioning position obtained based on the satellite positioning system to determine error correction information, and provide the error correction information to the drone. In the process of obtaining the second position information, the error correction information can be used to correct error factors such as atmospheric delay of the satellite broadcast signal and satellite orbit error to obtain higher-precision second position information. In some embodiments, the RTK algorithm can provide the carrier phase information to the drone based on the carrier phase measurement of the ground base station to achieve error correction of the second position information. In some embodiments, those skilled in the art can also obtain the second position information of the drone based on other feasible drone positioning methods such as visual optical flow positioning, which are not limited here.

[0055] Figure 4 This is an exemplary flow chart of obtaining the measured azimuth information of a drone relative to a wireless positioning beacon according to some embodiments of this specification. In some embodiments, Figure 4 As shown, process 400 may include the following steps.

[0056] Step 410: Based on the array antenna module carried by the UAV, obtain the time difference and / or phase difference of each antenna element in the array antenna module receiving the beacon signal.

[0057] In some embodiments, there is a communication connection between the wireless positioning beacon and the drone, and the communication connection can be a WIFI communication connection, a Bluetooth communication connection, or other achievable wireless communication connection, which is not limited here. In some embodiments, the wireless positioning beacon includes a signal generating module that can periodically send a beacon signal for measuring azimuth to the drone, and the array antenna module carried by the drone is used to receive the beacon signal, wherein the array antenna module includes multiple antenna elements. The antenna element is a basic structural unit for radiating or receiving electromagnetic wave signals, which can be a simple conductor, such as a straight antenna, a loop antenna, etc., or it can have a relative load structure setting, which is not limited here. The specific setting structure of the array antenna module will be described in detail later and will not be repeated here. It is understandable that due to the certain distance between the wireless positioning beacon and the drone, the beacon signal emitted by the wireless positioning beacon has a time difference and / or phase difference when it reaches each antenna element in the array antenna module. The above time difference and / or phase difference can be obtained to provide a data basis for determining the measurement of azimuth information.

[0058] Step 420: Determine the measured azimuth information of the UAV relative to the wireless positioning beacon based on the time difference and / or phase difference.

[0059] In some embodiments, a phase interferometer method can be used to determine the measured azimuth information of the drone relative to the wireless positioning beacon. Specifically, the phase difference between the signals received by multiple antennas can be used to measure the arrival angle of the beacon signal emitted by the wireless positioning beacon to the array antenna module carried by the drone, and the above arrival angle is used as the measured azimuth information of the drone relative to the wireless positioning beacon. In some embodiments, the phase interferometer method can determine the arrival angle of the beacon signal by measuring the phase difference between the beacon signals received by two or more adjacent antenna elements in the array antenna module. In some embodiments, those skilled in the art can also use other suitable algorithms to achieve the determination of the measured azimuth information, which is not limited here.

[0060] Step 220: Based on the first location information and the second location information, determine the calculated azimuth information of the drone relative to the wireless positioning beacon. In some embodiments, step 220 can be implemented by the azimuth acquisition module 1020.

[0061] In some embodiments, based on the wireless positioning beacon location in the first location information and the drone location in the second location information, a mathematical method can be used to directly calculate the calculated azimuth information of the drone relative to the wireless positioning beacon, which will not be described in detail here. In some embodiments, due to positioning errors in the first location information and the second location information obtained by the satellite positioning system, the calculated azimuth information obtained by calculation cannot accurately reflect the true relative position of the drone relative to the wireless positioning beacon, and further azimuth correction needs to be performed in combination with the measured azimuth information obtained in the aforementioned step 210.

[0062] Step 230: Based on the measured azimuth information and the calculated azimuth information, determine the corrected azimuth information of the drone relative to the wireless positioning beacon. In some embodiments, step 230 can be implemented by the azimuth correction module 1030.

[0063] In some embodiments, given that both the measured azimuth information and the calculated azimuth information may contain measurement errors and / or positioning errors, the measured azimuth information and the calculated azimuth information may be combined using a weighted average to determine the corrected azimuth information of the drone relative to the wireless positioning beacon. The specific acquisition of the corrected azimuth information will be described in detail later and will not be repeated here.

[0064] Step 240: Determine the relative position information between the UAV and the wireless positioning beacon based on the corrected azimuth information. In some embodiments, step 240 can be implemented by the relative position correction module 1040.

[0065] In some embodiments, based on determining the corrected azimuth information, the relative positioning information of the drone relative to the wireless positioning beacon can be determined based on the first position information and the second position information, and then the relative positioning information can be corrected by correcting the azimuth information to obtain the relative position information between the drone and the wireless positioning beacon. The above relative position information can reflect the accurate relative position between the drone and the wireless positioning beacon after being corrected by the relative error vector.

[0066] Based on the drone positioning method provided by the aforementioned process 200, the positioning information of the wireless positioning beacon and the drone can be corrected based on the corrected azimuth information between the drone and the wireless positioning beacon, thereby determining high-precision relative position information between the drone and the wireless positioning beacon. This can improve the positioning accuracy of the drone and the accuracy of flight trajectory planning in close-range drone applications. The specific implementation of the aforementioned process 200 will be further explained and illustrated below in conjunction with specific embodiments.

[0067] In some embodiments, the array antenna module carried by the drone may include a plurality of antenna elements extending and arranged along a first direction and a second direction, wherein the first direction and the second direction are perpendicular to each other, that is, the antenna elements are arranged in the form of a matrix, which can effectively receive the beacon signal from the wireless positioning beacon regardless of the orientation of the drone relative to the wireless positioning beacon. In some embodiments, further, the number of antenna elements arranged in the first direction can be the same as the number of antenna elements arranged in the second direction. In some embodiments, further, the spacing between two adjacent antenna elements in the first direction is the same as the distance between two adjacent antenna elements in the second direction, that is, the antenna elements contained in the array antenna module are arranged in a square pattern, so that the array antenna module obtained by the above arrangement has a better reception effect for omnidirectional beacon signals. In some embodiments, the spacing between two adjacent antenna elements in the first direction can be less than or equal to one-quarter of the signal wavelength corresponding to the beacon signal, and the distance between two adjacent antenna elements in the second direction can be less than or equal to one-quarter of the signal wavelength. In some embodiments, the ideal spacing between two adjacent antenna elements is one-quarter of the signal wavelength corresponding to the beacon signal. When the spacing between two adjacent antenna elements is less than one-quarter of the signal wavelength, a certain performance loss will occur. In order to take into account the setting size and antenna performance of the array antenna module at the same time, the spacing between two adjacent antenna elements can be set to be slightly less than one-quarter of the signal wavelength, which is not limited here.

[0068] Figure 5 is a schematic diagram of the structure of an array antenna module according to some embodiments of this specification. In some embodiments, Figure 5 As shown, in the array antenna module 500, a 2*2 layout antenna element structure is adopted, a single antenna element 510 is a square, a side length of a single antenna element 510 is 25 mm, and the geometric center distance between two adjacent antenna elements 510 is approximately equal to 30 mm. The length and width of the entire array antenna module 500 are both approximately equal to 60 mm. Figure 6 is a schematic diagram of the structure of another array antenna module according to some embodiments of this specification. In some embodiments, Figure 6 As shown, in the array antenna module 600, a 2*2 layout of antenna elements is also used. A single antenna element 610 is circular, the radius of a single antenna element 610 is 25 mm, the center distance between two adjacent antenna elements 610 is approximately 30 mm, and the length and width of the entire array antenna module 600 are approximately 60 mm. In some embodiments, as Figure 5 The array antenna module 500 shown and Figure 6The received signal frequency corresponding to the array antenna module 600 shown is in the range of 2400 MHz to 2483.5 MHz, and the corresponding signal wavelength is in the range of 12.1 cm to 12.5 cm. The size of the above-mentioned array antenna module is an optimized choice in the actual application scenario. Those skilled in the art can select other suitable antenna element layout structures according to actual application needs, and no limitation is made here.

[0069] Figure 7 is an exemplary flow chart of determining the corrected azimuth information of a drone relative to a wireless positioning beacon according to some embodiments of this specification. In some embodiments, Figure 7 As shown, process 700 may include the following steps.

[0070] Step 710: Based on the first location information and the second location information, determine the relative distance value of the drone relative to the wireless positioning beacon.

[0071] In some embodiments, the calculated distance value of the drone relative to the wireless positioning beacon can be determined based on the positioning information of the wireless positioning beacon and the drone. Specifically, the calculated distance value can be the modulus of the vector pointing from the positioning position coordinates of the wireless positioning beacon to the positioning position coordinates of the drone (or the positioning position coordinates of the drone pointing to the positioning position coordinates of the wireless positioning beacon). The above-mentioned calculated distance value can roughly reflect the relative distance information of the drone relative to the wireless positioning beacon obtained based on the positioning information.

[0072] Step 720: Determine a first fusion weight corresponding to the measured azimuth information based on the relative distance value and calculate a second fusion weight corresponding to the azimuth information.

[0073] In some embodiments, the measured azimuth information has higher measurement accuracy when the drone is close to the wireless positioning beacon. However, when the drone is far away from the wireless positioning beacon, the beacon signal emitted by the wireless positioning beacon may be interfered with by external factors such as the environment, resulting in a decrease in the measurement accuracy of the measured azimuth information. Regarding the calculated azimuth information, when the drone is close to the wireless positioning beacon, there is a large deviation error due to the positioning accuracy of the satellite positioning system. However, when the drone is far away from the wireless positioning beacon, the positioning accuracy impact caused by the satellite positioning system is small or negligible compared to the impact caused by the distance between the drone and the wireless positioning beacon. In this case, the calculated azimuth information can better reflect the relative position between the drone and the wireless positioning beacon. In view of this, in some embodiments, the weight value of the first fusion weight can be negatively correlated with the relative distance value, that is, the closer the relative distance of the drone to the wireless positioning beacon, the higher the first fusion weight corresponding to the measured azimuth information. In some embodiments, the weight value of the second fusion weight can be positively correlated with the relative distance value, that is, the farther the relative distance of the drone from the wireless positioning beacon is, the higher the second fusion weight corresponding to the calculated azimuth information. In some embodiments, when the distance between the drone and the wireless positioning beacon is greater than 500 meters, the weight value of the first fusion weight can be set to 0.2, and the weight value of the second fusion weight can be set to 0.8; when the distance between the drone and the wireless positioning beacon is between 100 meters and 500 meters, the weight value of the first fusion weight can be set to 0.4, and the weight value of the second fusion weight can be set to 0.6; when the distance between the drone and the wireless positioning beacon is between 10 meters and 100 meters, the weight value of the first fusion weight can be set to 0.75, and the weight value of the second fusion weight can be set to 0.25; when the distance between the drone and the wireless positioning beacon is less than 10 meters, the weight value of the first fusion weight can be set to 0.9, and the weight value of the second fusion weight can be set to 0.1, which is not limited here.

[0074] Step 730: Perform weighted fusion on the measured azimuth information and the calculated azimuth information based on the first fusion weight and the second fusion weight to determine the corrected azimuth information.

[0075] In some embodiments, the corrected azimuth information determined by the above process 700 can take into account the azimuth correction of the drone relative to the wireless positioning beacon at close and long distances, and the obtained corrected azimuth information can accurately reflect the actual relative azimuth of the drone relative to the wireless positioning beacon.

[0076] Figure 8 is an exemplary flow chart of another drone positioning method according to some embodiments of this specification. In some embodiments, Figure 8As shown, process 800 may include the following steps.

[0077] Step 810: Obtain the measured distance value between the wireless positioning beacon and the drone.

[0078] In some embodiments, the measured distance value between the wireless positioning beacon and the drone can be obtained by the array antenna module carried by the drone. For example, in a specific example, the drone is equipped with Figure 5 or Figure 6 The array antenna module shown is used to obtain the broadcast signal emitted by the wireless positioning beacon, and obtain the position and relative distance of the drone relative to the wireless positioning beacon based on the time difference and / or phase difference of each antenna element in the array antenna module receiving the broadcast signal. It can be understood that the use of the array antenna module can achieve the acquisition of the measured azimuth information of the drone relative to the wireless positioning beacon while obtaining the measured distance value of the drone relative to the wireless positioning beacon. In some embodiments, the wireless positioning beacon can be a Bluetooth positioning beacon, and the measured distance value between the wireless positioning beacon and the drone can be determined and obtained by Bluetooth channel sounding technology, wherein Bluetooth channel sounding (Channel Sounding) technology is a technology for evaluating wireless channel characteristics. It can optimize the wireless communication performance between various Bluetooth communication devices by measuring and analyzing channel-related parameter information such as frequency response, delay characteristics and multipath effect of different Bluetooth communication channels. In some embodiments, Bluetooth channel detection technology is a technical support included in the Bluetooth 6.0 version released by the Bluetooth Special Interest Group (SIG): When the drone and the wireless positioning beacon are equipped with a Bluetooth signal transceiver module that supports Bluetooth 6.0, a Bluetooth communication connection can be achieved between the drone and the wireless positioning beacon. At this time, the Bluetooth channel detection technology can be used to obtain a high-precision distance between the wireless positioning coordinates and the drone. In some embodiments, the Bluetooth channel detection technology can be used to accurately obtain the measured distance value between the wireless positioning beacon and the drone based on information such as the received Bluetooth signal strength and the time difference from the Bluetooth signal being sent to the Bluetooth signal being received. In some embodiments, the measurement accuracy of the measured distance value determined based on the Bluetooth channel detection technology is generally in the range of centimeters to sub-meters, that is, the deviation between the measured distance value determined by the Bluetooth channel detection technology and the actual distance between the wireless positioning beacon and the drone in a real environment is generally in the range of one centimeter to ten centimeters.

[0079] Step 820: Determine a relative error vector of the drone relative to the wireless positioning beacon based on the measured distance value, the first position information, and the second position information.

[0080] In some embodiments, since the first position information and the second position information both have corresponding positioning errors during the acquisition process, the relative position information of the drone relative to the wireless positioning beacon is difficult to obtain directly based on the coordinate difference between the first position information and the second position information, affecting the positioning accuracy of the drone in close-range scene applications. In some embodiments, considering that the measurement accuracy of the measured distance value of the drone relative to the wireless positioning beacon is relatively high, the measured distance value can be used to correct the relative position information of the drone relative to the wireless positioning beacon. In some embodiments, taking the wireless positioning beacon as a Bluetooth positioning beacon as an example, the measurement error between the measured distance value and the actual distance value between the drone and the Bluetooth positioning beacon is less than the first positioning error between the first position information and the actual position of the wireless positioning beacon, and less than the second positioning error between the second position information and the actual position of the drone. Therefore, the measured distance value can be used to determine the relative error vector of the drone relative to the wireless positioning beacon. The specific method for determining the relative error vector will be further explained later and will not be repeated here.

[0081] Step 830: Determine the relative position information between the UAV and the wireless positioning beacon based on the relative error vector and / or the corrected azimuth information.

[0082] In some embodiments, based on the determination of the relative error vector, the relative positioning information of the drone relative to the wireless positioning beacon can be first determined based on the first position information and the second position information. The relative positioning information is then corrected using the relative error vector and / or the corrected azimuth information to obtain the relative position information between the drone and the wireless positioning beacon. In some embodiments, the relative position information can be corrected simultaneously using the relative error vector and the corrected azimuth information, further improving the accuracy of the relative position information between the drone and the wireless positioning beacon through multi-dimensional correction. The specific implementation of the above process 800 will be further elaborated and illustrated in conjunction with embodiments below.

[0083] In some embodiments, during the process of acquiring the first location information, the second location information, and the measured distance value, the wireless positioning beacon location coordinates, the drone location coordinates, and the measured distance value between the wireless positioning beacon and the drone corresponding to the multiple collection points contained in each sliding window can be acquired based on a preset sliding window size. In some embodiments, by acquiring the first location information, the second location information, and the measured distance value using a sliding window sampling method, the position changes of the drone and the wireless positioning beacon can be continuously acquired, and the relative position information can be continuously updated based on the position changes. In some embodiments, the first location information can include the location coordinates of multiple wireless positioning beacons corresponding to a single sliding window; the second location information can include the location coordinates of multiple drones corresponding to a single sliding window; and the measured distance value can include multiple measured distance values ​​corresponding to a single sliding window. In some embodiments, taking the sliding window size including three collection points t1, t2, and t3 as an example, for a selected sliding window, the first location information may include the first wireless positioning beacon location coordinates collected by collection point t1, the second wireless positioning beacon location coordinates collected by collection point t2, and the third wireless positioning beacon location coordinates collected by collection point t3; the second location information may include the first drone location coordinates collected by collection point t1, the second drone location coordinates collected by collection point t2, and the third drone location coordinates collected by collection point t3; the measured distance value may include the first measured distance value obtained by collection point t1, the second measured distance value obtained by collection point t2, and the third measured distance value obtained by collection point t3, without limitation. In some embodiments, the acquired data corresponding to each collection point in the sliding window are all clock-calibrated and timestamp information is aligned, which can reflect the position relationship and relative position relationship between the drone and the wireless positioning beacon at the same time.

[0084] Figure 9 is an exemplary flow chart of determining a relative error vector of a drone relative to a wireless positioning beacon according to some embodiments of this specification. In some embodiments, Figure 9 As shown, process 900 may include the following steps.

[0085] Step 910: Based on the first position information and the second position information, determine the calculated distance vector of the drone relative to the wireless positioning beacon.

[0086] In some embodiments, the first location information and the second location information can be acquired using a sliding window sampling method based on a preset sliding window size. In some embodiments, those skilled in the art can set the preset sliding window size based on historical experience. For example, the preset sliding window size can be set to 0.3 seconds, 0.5 seconds, or 1 second, etc., which is not limited here. In some embodiments, the number of collection points included in a single sliding window is related to the positioning frequency of the first location information and the second location information. For example, if the positioning frequency of the first location information and the second location information determined by the satellite positioning system is 10 Hz, then the location information of the wireless positioning beacon and the drone is acquired every 0.1 second. When the single sliding window size is 1 second, the number of collection points included in the single sliding window is 10; when the single sliding window size is 0.3 seconds, the number of collection points included in the single sliding window is 3, which is not limited here. In some embodiments, taking the sliding window size including three collection points t1, t2 and t3 as an example, for a selected first sliding window, the first position information may include the first wireless positioning beacon position coordinates collected by the collection point t1, the second wireless positioning beacon position coordinates collected by the collection point t2, and the third wireless positioning beacon position coordinates collected by the collection point t3. The second position information may include the first drone position coordinates collected by the collection point t1, the second drone position coordinates collected by the collection point t2, and the third drone position coordinates collected by the collection point t3. On this basis, the calculated distance vectors corresponding to the various collection points corresponding to the first sliding window can be determined in sequence, for example, the calculated distance vector corresponding to the collection point t1 The distance vector can be a vector pointing from the first wireless positioning beacon position coordinates to the first drone position coordinates (or the first drone position coordinates to the first wireless positioning beacon position coordinates), the calculated distance vector corresponding to the collection point t2 can be a vector pointing from the second wireless positioning beacon position coordinates to the second drone position coordinates (or the second drone position coordinates to the second wireless positioning beacon position coordinates), and the calculated distance vector corresponding to the collection point t3 can be a vector pointing from the third wireless positioning beacon position coordinates to the third drone position coordinates (or the third drone position coordinates to the third wireless positioning beacon position coordinates). The above-mentioned calculated distance vector can reflect the relative position information of the drone relative to the wireless positioning beacon obtained based on the positioning information.

[0087] Step 920: Establish an objective function associated with the relative error vector.

[0088] In some embodiments, considering that during the process of acquiring the first location information of the wireless positioning beacon based on the satellite positioning system, although there is a positioning error between the first location information and the actual location of the wireless positioning beacon, the positioning error is caused by one or more combinations of environmental error factors, system error factors corresponding to the satellite positioning system, and system error factors corresponding to the wireless positioning beacon. The above error factors are often fixed or slowly drift during the use of the wireless positioning beacon. Therefore, it can be determined that during the continuous acquisition of the first location information of the wireless positioning beacon, the first positioning error corresponding to the first location information can be fixed or slowly drift; similarly, the second positioning error corresponding to the second location information of the drone can also be fixed or slowly drift. In some embodiments, when the first positioning error and the second positioning error generated based on the positioning information can both be considered fixed or slowly drift, the relative error vector of the drone relative to the wireless positioning beacon can be considered fixed or slowly drift, that is, the relative error vector can be a fixed constant vector, or a fixed constant vector in a sliding window.

[0089] In some embodiments, an objective function can be established based on the relative error vector, where the relative error vector can be represented by a fixed constant vector. In some embodiments, the established objective function can be associated with the difference between the modulus of the calculated distance vector corrected by the relative error vector and the measured distance value. In some embodiments, the objective function can be implemented based on the following mathematical expression.

[0090]

[0091] in, is the objective function, N is the number of acquisition points corresponding to the selected first sliding window, P rc,i is the wireless positioning beacon location information corresponding to the i-th collection point in the first sliding window, P robot,i is the UAV location information corresponding to the i-th collection point in the first sliding window, p rc,i -P robot,i is the calculated distance vector corresponding to the i-th acquisition point in the first sliding window, p e is the relative error vector, ||P rc,i -P robot,i -p e || is the modulus of the calculated distance vector corresponding to the i-th acquisition point in the first sliding window corrected by the relative error vector, d i is the measured distance value corresponding to the i-th acquisition point in the first sliding window.

[0092] Step 930: Optimize the objective function using a nonlinear optimization algorithm based on the measured distance value and the calculated distance vector, and determine the relative error vector based on the optimized objective function.

[0093] In some embodiments, when the objective function is associated with the difference between the modulus of the calculated distance vector after correction by the relative error vector and the measured distance value, the nonlinear optimization of the objective function can be performed by adjusting the relative error vector so as to minimize the difference between the modulus of the calculated distance vector after correction by the adjusted relative error vector and the measured distance value, i.e., minimizing the value of the objective function. It will be understood that the smaller the difference between the modulus of the calculated distance vector after correction by the relative error vector and the measured distance value, the closer the calculated distance vector after correction by the relative error vector is to the actual relative position between the drone and the wireless positioning beacon. The relative error vector determined by the above optimization method can be used to accurately correct the positioning errors of the drone and the wireless positioning beacon.

[0094] In some embodiments, the nonlinear optimization algorithm for the objective function may include a sequential quadratic programming algorithm and a quasi-Newton algorithm, wherein the sequential quadratic programming algorithm (SQP) is an effective algorithm for solving nonlinear optimization problems, particularly suitable for optimization problems with constraints, by solving a quadratic programming (QP) subproblem in each iteration to gradually approach the optimal solution; the quasi-Newton algorithm (Quasi-Newton Method) is a type of iterative algorithm for solving unconstrained optimization problems, particularly suitable for finding the local minimum of the objective function, which does not require calculating the Hessian matrix of the objective function, but improves the calculation and optimization efficiency by gradually updating an approximate Hessian matrix. In some embodiments, those skilled in the art may also adopt other suitable algorithms to achieve nonlinear optimization of the objective function, which is not limited here.

[0095] In some embodiments, when optimizing the objective function using a nonlinear optimization algorithm, the objective function can be optimized using the nonlinear optimization algorithm based on the measured distance value, the calculated distance vector, and the preset error vector. The preset error vector can be set based on historical positioning experience between the drone and the wireless positioning beacon to accelerate the optimization calculation process of the objective function. In some embodiments, considering that the relative error vector of the drone relative to the wireless positioning beacon can be considered to drift slowly, the historical relative error vector corresponding to the previous sliding window can be used as the initial value of the relative error vector of the current sliding window, replacing the preset error vector when optimizing the objective function using the nonlinear optimization algorithm. This can accelerate the optimization calculation process of the objective function while ensuring smooth changes in the determined relative error vector.

[0096] Some embodiments of this specification also provide a drone positioning system based on wireless positioning beacons. Figure 10 Schematic diagram of the functional modules of a UAV positioning system based on wireless positioning beacons according to some embodiments of this specification. Figure 10 As shown, the drone positioning system 1000 may include a position acquisition module 1010, an azimuth acquisition module 1020, an azimuth correction module 1030, and a relative position correction module 1040. In some embodiments, the various modules of the drone positioning system 1000 may be configured in the processing device 130.

[0097] In some embodiments, the location acquisition module 1010 is used to acquire the location information of the wireless positioning beacon and the drone. In some embodiments, the location acquisition module 1010 can be used to respectively acquire the first location information of the wireless positioning beacon, the second location information of the drone, and the measured azimuth information of the drone relative to the wireless positioning beacon. In some embodiments, the location acquisition module 1010 can also be used to acquire the measured distance value of the drone relative to the wireless positioning beacon. In some embodiments, the location acquisition module 1010 can adopt a sliding window sampling acquisition method, based on a preset sliding window size, to acquire the wireless positioning beacon location coordinates, drone location coordinates, the measured azimuth of the drone relative to the wireless positioning beacon, and the measured distance value between the wireless positioning beacon and the drone corresponding to the multiple collection points contained in each sliding window.

[0098] In some embodiments, the azimuth acquisition module 1020 is configured to determine the calculated azimuth information of the drone relative to the wireless positioning beacon based on the respective positioning information of the drone and the wireless positioning beacon. In some embodiments, the azimuth acquisition module 1020 can be used to determine the calculated azimuth information of the drone relative to the wireless positioning beacon based on the first position information and the second position information.

[0099] In some embodiments, the azimuth correction module 1030 is used to determine the corrected azimuth information of the drone relative to the wireless positioning beacon, and the corrected azimuth information can reflect the accurate relative direction of the drone relative to the wireless positioning beacon. In some embodiments, the azimuth correction module 1030 can be used to determine the corrected azimuth information of the drone relative to the wireless positioning beacon based on the measured azimuth information and the calculated azimuth information. In some embodiments, the azimuth correction module 1030 can first determine the relative distance value of the drone relative to the wireless positioning beacon based on the first position information and the second position information, and then determine the first fusion weight corresponding to the measured azimuth information and the second fusion weight corresponding to the calculated azimuth information based on the relative distance value, and determine the corrected azimuth information by weighted fusion of the measured azimuth information and the calculated azimuth information. In some embodiments, the weight value of the first fusion weight can be negatively correlated with the relative distance value. In some embodiments, the weight value of the second fusion weight can be positively correlated with the relative distance value.

[0100] In some embodiments, the relative position correction module 1040 can be used to determine the relative position information between the drone and the wireless positioning beacon based on the corrected azimuth information. The above relative position information can reflect the accurate relative position between the drone and the wireless positioning beacon after being corrected by the corrected azimuth information.

[0101] In some embodiments, the relative position correction module 1040 can also use the measured distance value between the wireless positioning beacon and the drone obtained by the position acquisition module 1010 to first determine the relative error vector of the drone relative to the wireless positioning beacon based on the measured distance value, the first position information and the second position information, and then determine the relative position information between the drone and the wireless positioning beacon based on the relative error vector and / or the corrected azimuth information. By fusing and correcting multi-dimensional information such as relative distance, relative position error vector, and corrected azimuth, the accurate relative position between the drone and the wireless positioning beacon can be more accurately reflected. In some embodiments, the relative position correction module 1040 can first establish an objective function associated with the relative error vector in the process of determining the relative error vector, and use a nonlinear optimization algorithm to optimize the objective function to determine the relative error vector, which is not limited here.

[0102] For more information about each module, see Figures 2 to 9 The relevant description of , will not be repeated here. It should be understood that, Figure 10The system and its modules shown can be implemented in various ways. For example, in some embodiments, the system and its modules can be implemented by hardware, software, or a combination of software and hardware. Among them, the hardware part can be implemented using dedicated logic; the software part can be stored in a memory and executed by an appropriate instruction execution system, such as a microprocessor or dedicated hardware. Those skilled in the art will understand that the above-mentioned methods and systems can be implemented using computer-executable instructions and / or control codes contained in a processor, such as a carrier medium such as a disk, CD or DVD-ROM, or a memory of a programmable device. The system and its modules of this specification can not only be implemented by hardware circuits such as very large-scale integrated circuits or gate arrays, semiconductors such as logic chips, transistors, or programmable hardware devices such as field programmable gate arrays, programmable logic devices, etc., but can also be implemented by software executed by various types of processors, or by a combination of the above-mentioned hardware circuits and software (for example, firmware).

[0103] It should be noted that the above description of the system and its modules is for convenience only and does not limit this specification to the scope of the illustrated embodiments. It is understood that those skilled in the art, after understanding the principles of the system, may, without departing from these principles, arbitrarily combine the modules to form subsystems connected to other modules. Alternatively, they may split certain modules to obtain more modules or multiple units within a module. Such variations are within the scope of this specification.

[0104] Some embodiments of this specification also provide a drone positioning device based on a wireless positioning beacon, which includes a processor and a storage medium, wherein the storage medium stores computer program instructions, and the processor is used to execute at least part of the computer program instructions to implement the drone positioning method based on a wireless positioning beacon provided in the aforementioned embodiments of this specification.

[0105] Some embodiments of this specification also provide a computer program product, including computer instructions or a computer program. When at least part of the computer instructions or computer program is executed by a processor, it can implement the drone positioning method based on wireless positioning beacons provided in the aforementioned embodiments of this specification.

[0106] In some embodiments, the processor may be a combination of one or more of the following processors: a central processing unit (CPU), an application-specific integrated circuit (ASIC), an application-specific instruction set processor (ASIP), a graphics processing unit (GPU), a physical processing unit (PPU), a digital signal processor (DSP), a field-programmable gate array (FPGA), a programmable logic device (PLD), a programmable logic controller (PLC), a reduced instruction set computer (RISC), a microprocessor, etc. In some embodiments, the processor may be the processing device 130.

[0107] The beneficial effects that may be brought about by the embodiments of this specification include but are not limited to: (1) the positioning information of the wireless positioning beacon and the drone can be corrected based on the corrected azimuth information between the drone and the wireless positioning beacon to determine the high-precision relative position information between the drone and the wireless positioning beacon, which can improve the positioning accuracy of the drone and the accuracy of flight trajectory planning in the close-range scene application of the drone. (2) The relative position information can also be corrected simultaneously through the relative error vector and the corrected azimuth information, and the accuracy of obtaining the relative position information between the drone and the wireless positioning beacon can be further improved through multi-dimensional correction. (3) In the process of obtaining the high-precision relative position information between the drone and the wireless positioning beacon, Bluetooth channel detection technology is used for determination, which is more suitable for small drones. It should be noted that different embodiments may produce different beneficial effects. In different embodiments, the beneficial effects that may be produced may be any one or a combination of the above, or any other possible beneficial effects.

[0108] While the basic concepts have been described above, it will be apparent to those skilled in the art that the detailed disclosure is merely illustrative and does not limit this specification. Although not explicitly stated herein, various modifications, improvements, and revisions to this specification may be made by those skilled in the art. Such modifications, improvements, and revisions are taught in this specification and remain within the spirit and scope of the exemplary embodiments of this specification.

Claims

1. A method for positioning a UAV based on a wireless positioning beacon, characterized in that: The method comprises: Obtaining first position information of a wireless positioning beacon, second position information of a drone, and measured azimuth information of the drone relative to the wireless positioning beacon; Determining calculated azimuth information of the drone relative to the wireless positioning beacon based on the first location information and the second location information; Determining corrected azimuth information of the UAV relative to the wireless positioning beacon based on the measured azimuth information and the calculated azimuth information; Based on the corrected azimuth information, the relative position information between the UAV and the wireless positioning beacon is determined.

2. The method according to claim 1, characterized in that The wireless positioning beacon periodically sends a beacon signal to the drone; The obtaining of the measured azimuth information of the UAV relative to the wireless positioning beacon includes: Based on the array antenna module carried by the UAV, obtaining the time difference and / or phase difference between each antenna element in the array antenna module receiving the beacon signal; Based on the time difference and / or the phase difference, the measurement azimuth information of the UAV relative to the wireless positioning beacon is determined.

3. The method according to claim 2, characterized in that The array antenna module includes a plurality of antenna elements arranged and extending along a first direction and a second direction, wherein the first direction and the second direction are perpendicular to each other; The distance between two adjacent antenna elements in the first direction is less than or equal to one quarter of the signal wavelength corresponding to the beacon signal; The distance between two adjacent antenna elements in the second direction is less than or equal to one quarter of the signal wavelength.

4. The method according to claim 3, characterized in that The number of the antenna elements in the first direction is the same as the number of the antenna elements in the second direction; and / or The distance between two adjacent antenna elements in the first direction is the same as the distance between two adjacent antenna elements in the second direction.

5. The method according to claim 1, wherein The first location information of the wireless positioning beacon is determined based on a satellite positioning system; and / or The second position information of the drone is determined based on the satellite positioning system.

6. The method according to claim 1, characterized in that Acquiring the second position information of the drone includes: Determining the initial position information of the UAV during operation based on the satellite positioning system; Obtaining motion attitude correction information of the drone during operation based on an inertial measurement module carried by the drone; and / or obtaining position drift correction information of the drone during operation based on a magnetometer module carried by the drone; Based on the motion posture correction information and / or the position drift correction information, the initial position information is corrected to determine the second position information.

7. The method according to claim 1, characterized in that The determining, based on the measured azimuth information and the calculated azimuth information, the corrected azimuth information of the UAV relative to the wireless positioning beacon includes: Determine a relative distance value of the drone relative to the wireless positioning beacon based on the first location information and the second location information; Determine, based on the relative distance value, a first fusion weight corresponding to the measured azimuth information and a second fusion weight corresponding to the calculated azimuth information; The measured azimuth information and the calculated azimuth information are weightedly fused based on the first fusion weight and the second fusion weight to determine the corrected azimuth information.

8. The method according to claim 7, characterized in that The weight value of the first fusion weight is negatively correlated with the relative distance value; and / or The weight value of the second fusion weight is positively correlated with the relative distance value.

9. The method according to claim 1, characterized in that The method further comprises: Obtaining a measured distance value between the wireless positioning beacon and the drone; Determining a relative error vector of the UAV relative to the wireless positioning beacon based on the measured distance value, the first position information, and the second position information; Based on the relative error vector and / or the corrected azimuth information, the relative position information between the UAV and the wireless positioning beacon is determined.

10. The method according to claim 9, characterized in that The determining, based on the measured distance value, the first position information, and the second position information, a relative error vector of the UAV relative to the wireless positioning beacon includes: Determining a calculated distance vector of the drone relative to the wireless positioning beacon based on the first location information and the second location information; establishing an objective function associated with the relative error vector; The objective function is optimized using a nonlinear optimization algorithm according to the measured distance value and the calculated distance vector, and the relative error vector is determined according to the optimized objective function.

11. The method according to claim 10, characterized in that The objective function is associated with the difference between the modulus of the calculated distance vector corrected by the relative error vector and the measured distance value; The optimizing the objective function by using a nonlinear optimization algorithm includes: adjusting the relative error vector so as to minimize the difference between the modulus of the calculated distance vector corrected by the adjusted relative error vector and the measured distance value.

12. A UAV positioning system based on wireless positioning beacons, characterized in that: The system comprises: A position acquisition module is used to obtain first position information of a wireless positioning beacon, second position information of a UAV, and measured azimuth information of the UAV relative to the wireless positioning beacon; an azimuth acquisition module, configured to determine calculated azimuth information of the UAV relative to the wireless positioning beacon based on the first position information and the second position information; an azimuth correction module, configured to determine, based on the measured azimuth information and the calculated azimuth information, the corrected azimuth information of the UAV relative to the wireless positioning beacon; The relative position correction module is used to determine the relative position information between the UAV and the wireless positioning beacon based on the corrected azimuth information.

13. A computer program product, comprising computer instructions or a computer program, wherein when at least part of the computer instructions or the computer program is executed by a processor, it can implement the drone positioning method based on wireless positioning beacons as described in any one of claims 1 to 11.

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