Unmanned aerial vehicle auxiliary positioning device and method

Abstract

The invention relates to an unmanned aerial vehicle auxiliary positioning device and method, and belongs to the technical field of unmanned aerial vehicle positioning. The device comprises a signal processing module, a signal receiving module, an antenna, a gyroscope and an antenna attitude control module, the signal receiving module is used for receiving positioning information, broadcast ephemeris, ionosphere model parameters and b2b correction information and screening out messy codes and repeated or incomplete information; the signal processing module is used for processing the signal transmitted by the signal receiving module and carrying out PPP positioning; the antenna is a high-gain antenna and is used for ensuring the integrity of a received signal and enabling positioning to reach the maximum refresh rate; the gyroscope is used for acquiring the antenna direction and transmitting attitude correction information to the antenna attitude control module; and the antenna attitude control module is used for ensuring that the antenna is vertical to the ground and stabilizing the antenna gain. The problem that the unmanned aerial vehicle cannot be positioned when the internet is lost and the base station is connected is solved, the positioning precision of the unmanned aerial vehicle is also improved, and mounting and dismounting are convenient.

Description

Technical Field

[0001] The present invention relates to an auxiliary positioning device and method for an unmanned aerial vehicle (UAV), belonging to the technical field of UAV positioning. Background Art

[0002] Most of the positioning technologies currently used on drones are RTK (real-time kinematic differential technology) or PPK (dynamic post-processing technology). Both technologies can achieve centimeter-level positioning accuracy within a dozen seconds, but positioning requires the support of the Internet and base stations. If the Internet or base station connection is lost, the drone will lose its positioning. Losing positioning during long-distance or field operations is undoubtedly very dangerous. Therefore, an auxiliary positioning method that does not rely on network and base station resources is needed to improve the drone's positioning system and enable drones to perform various tasks in environments without networks or base stations.

[0003] PPP, or Precise Point Positioning, can achieve static centimeter-level positioning after convergence. PPP can replace base stations by receiving satellite broadcasts and can achieve precise positioning solely by relying on the receiver. However, existing PPP solutions have defects such as large device size and long convergence time. A more flexible solution that is more suitable for the miniaturization and lightweight requirements of drones is needed.

[0004] Broadcast ephemeris correction alone can only achieve an accuracy of tens of centimeters, which is obviously insufficient for flexible devices like drones. Compared with RTK or PPK positioning accuracy, the difference is very large. To obtain higher accuracy, it was previously only possible through real-time orbit and real-time clock difference products. These products are all broadcast through the Internet and do not meet the needs of working without a network or base station. But now, by receiving the PPP-B2b correction information broadcast by Beidou-3, a single receiving device can be used to collect all the data required for PPP positioning, which meets the needs of working on drones. However, such devices on the market are either too bulky to be used on drones, or are cumbersome to install, or require specific drone models, and there is a lack of a universal and convenient auxiliary positioning solution.

[0005] Therefore, given the phenomenon that drones cannot be positioned when there is no network or base station, how to use PPP-B2b technology on drones to complete real-time positioning and design sufficiently flexible and lightweight equipment so that the equipment can be used on different drones as much as possible is a problem faced by technical personnel in this field. Summary of the Invention

[0006] In response to the shortcomings of the existing technology, the present invention provides a drone auxiliary positioning device and method, which solves the problem of being unable to locate when the drone loses Internet and base station connection, improves the accuracy of drone positioning, and is easy to install and disassemble.

[0007] The technical solutions of the present invention are as follows: An auxiliary positioning device for unmanned aerial vehicles (UAVs) includes a signal processing module, a signal receiving module, an antenna, a gyroscope, and an antenna attitude control module. The signal processing module is composed of a microprocessor and a baseboard equipped with DDR3L memory, eMMC memory, an external clock, a power management chip, a Wi-Fi chip, and an SD card slot. The device is used to process signals transmitted from the signal receiving module, perform PPP positioning, and send positioning information to a ground user terminal via Wi-Fi. Signal receiving module: Packaged on the same baseboard as the microprocessor, it is used to receive positioning information and broadcast ephemeris, ionospheric model parameters, B2B correction information (message type 1-message type 7) and filter out garbled, repeated or incomplete information (all information that does not conform to the NMEA-0183 protocol and B2B correction information format will not be recorded. If the refresh rate of the same message exceeds the specified refresh rate, the excess will be filtered out); Antenna: Use a high-gain antenna to ensure the integrity of the received signal, and use an independent power supply circuit to prevent the external electromagnetic environment from affecting other modules of the device; Gyroscope: used to obtain antenna direction and transmit antenna attitude information to the antenna attitude control module; Antenna attitude control module: used to ensure that the antenna is perpendicular to the ground, so that the received satellite signal remains stable and prevent the loss of satellite connection due to antenna tilt.

[0008] If the drone antenna can receive PPP-B2B signals, the antenna, gyroscope, and antenna attitude control module in the above-mentioned drone auxiliary positioning device do not need to be installed. Instead, data from the drone antenna is received through the drone interface. If the drone has multiple antennas that can receive satellite signals, the information received by the main antenna is used. Not installing the above-mentioned modules can save fuselage space and improve stability. However, the positioning accuracy, positioning refresh rate, and positioning delay are different from those of products with the above-mentioned modules.

[0009] The positioning method of the above-mentioned UAV auxiliary positioning device has the following steps: (1) Connect the auxiliary positioning device to the UAV. When receiving data, the device receives positioning information and broadcast ephemeris, ionospheric model parameters, and b2b correction information through the antenna. When the UAV has an Internet connection, it can send a download request for broadcast ephemeris, ionospheric model parameters, and b2b correction information, and use the base station service to obtain more accurate positioning information. (2) After receiving the required signal, the signal processing module uses the precise single point positioning algorithm to calculate the position of the UAV; (3) The positioning information is sent to the handheld terminal via the antenna.

[0010] Preferably, according to the present invention, in step (2), when sending precise point positioning data, in addition to real-time broadcasting via WIFI, positioning data or raw data are simultaneously written to an SD card for post-processing and other purposes; when writing raw data, multiple ephemeris data and ionospheric model parameters are saved in the SD card. When the UAV is in a high-speed moving state or other scenarios where positioning consistency and low latency need to be prioritized, it is possible to temporarily not switch to the latest received ephemeris data and ionospheric model parameters, but use the last ephemeris data and ionospheric model parameters in the SD card for processing, and then switch to new ephemeris data and ionospheric model parameters when the UAV is stationary.

[0011] According to the preferred embodiment of the present invention, in step (2), the precise point positioning algorithm includes a Kalman filter algorithm, an error correction algorithm for PPP-B2b service (both of which belong to common precise point positioning technologies) and a fast ambiguity fixation algorithm. The fast ambiguity fixation algorithm includes two processes: decorrelation and search. The purpose of decorrelation is to minimize the correlation in the ambiguity parameters. Specifically: Among them, N is the integer solution of ambiguity, N f is the floating point solution of ambiguity obtained in Kalman filtering, Q N is the residual-covariance matrix of N; The down-correlation operation is completed through integer Gaussian transform. After the down-correlation is completed, the process of searching for the best ambiguity combination is converted into the process of finding the optimal solution in the n-dimensional sphere. Both integer Gaussian transform and n-dimensional sphere optimal solution algorithm are commonly used technologies.

[0012] According to the preferred embodiment of the present invention, in step (2), a multi-system GNSS combined positioning algorithm can be used to optimize the positioning accuracy. According to the preferred embodiment of the present invention, in step (2), when the UAV is in a moving state, the gyroscope data is used to determine the moving direction when calculating the positioning, to eliminate erroneous prediction results, or weights are set according to the speed information obtained by the gyroscope to accelerate the convergence of the algorithm. The algorithm is a PPP-B2B positioning algorithm, specifically: Among them, r0 is the unprocessed prediction space radius, r1 is the processed prediction space radius, w is the weight coefficient obtained according to the speed information, v1 is the moving speed of the drone transmitted by the gyroscope, and v max is the maximum speed of the drone; After processing, a new prediction space with a radius of r1 is generated at the distance r0 from the drone in the direction of the drone (1-w), replacing the original prediction space.

[0013] Preferably, according to the present invention, when the main positioning system of the drone (the present invention is an auxiliary positioning device, and the main positioning system is the positioning system of the drone itself) is working, the ambiguity can be calculated using its positioning results and the original information received by the antenna, skipping the cycle slip detection process. When the drone positioning is working normally, the ambiguity will be updated regularly. When the main positioning method of the drone fails, the most recently fixed ambiguity will be used for positioning, and the cycle slip detection will be restarted to accelerate the convergence speed of subsequent positioning. The calculation process of fuzziness is as follows: Where s represents the satellite number, i represents the signal frequency, and r represents the user receiver. represents the carrier phase, is the value of the carrier phase, Indicates the error of the carrier phase value; ρ represents the geometric distance between the user and the satellite, c represents the speed of light, dt r 、dt s denote the receiver and satellite clock errors respectively, represents the ionospheric delay error, T s represents the tropospheric delay error, B r,i 、 are the phase hardware delays of the receiver and satellite, respectively, i represents the wavelength of frequency i, Represents the integer ambiguity of the phase observation; The calculation process of ρ is: Among them, (X s , Y s , Z s ) represents the satellite coordinates, (X r , Y r , Z r ) represents the receiver coordinates. After substituting the receiver coordinates into the positioning obtained by the main positioning method of the UAV, the ambiguity can be resolved.

[0014] Cycle slip detection is a commonly used technique for detecting carrier phase changes. When the ambiguity is known, it simplifies the process by skipping the cycle slip detection step, saving time and computing resources.

[0015] Preferably, according to the present invention, the UAV is stationary, and after convergence is completed, the positioning accuracy of the UAV's main positioning system is verified, and the positioning structure of the auxiliary positioning device is compared with the positioning result of the UAV's main positioning system. During normal operation, the straight-line distance between the positioning results of the two systems should be less than 10 cm.

[0016] Optionally, the latest broadcast ephemeris and ionospheric model parameters can be downloaded when there is an internet connection, avoiding missing the ephemeris broadcast time and falling into a long time without convergence.

[0017] Optionally, when the ephemeris data and ionospheric model parameters are obtained, the program defaults to select the Beidou satellite navigation system, but can specify a specific satellite system according to the needs of the use area, or use the satellite system with the most visible satellites in the current area, or combine the ephemeris data and ionospheric model parameters of multiple satellite systems to obtain the optimal solution through statistical analysis.

[0018] Optionally, the signal processing module can be in standby state when the unmanned aerial vehicle is powered off or auxiliary positioning is not needed, and the standby state can greatly reduce the convergence time of auxiliary positioning when started.

[0019] The beneficial effects of the present application are: 1. Before the unmanned aerial vehicle takes off or is stationary in the air, the unmanned aerial vehicle auxiliary positioning device provided by the present application can verify the positioning of the main positioning system of the unmanned aerial vehicle, thereby improving the credibility of each other's positioning; the latest broadcast ephemeris can also be downloaded when there is an internet connection.

[0020] 2. When the unmanned aerial vehicle loses positioning after taking off, the present application can be used for emergency positioning of the unmanned aerial vehicle, and the device can provide meter-level positioning when it is just started, and the positioning accuracy increases with time, and the highest can reach centimeter-level positioning when the unmanned aerial vehicle is stationary. BRIEF DESCRIPTION OF DRAWINGS

[0021] Figure 1 It is a schematic diagram of the composition of the unmanned aerial vehicle auxiliary positioning device of the present application; Figure 2 It is a signal receiving schematic diagram of the unmanned aerial vehicle auxiliary positioning device of the present application; Figure 3 It is a schematic diagram of the unmanned aerial vehicle auxiliary positioning device using direction information to assist convergence of the present application; Figure 4 It is a signal receiving schematic diagram of the least composition of the unmanned aerial vehicle auxiliary positioning device of the present application. DETAILED DESCRIPTION

[0022] The present application will be further described below by examples and in conjunction with the drawings, but is not limited thereto.

[0023] Example 1: The embodiment provides an unmanned aerial vehicle assisted positioning device, which comprises a signal processing module, a signal receiving module, an antenna, a gyroscope and an antenna attitude control module, wherein the signal processing module is composed of a microprocessor (for example, STM32MP135DAE7) and a bottom plate which is provided with a DDR3L memory, an eMMC memory, an external clock, a power management chip, a WIFI chip and an SD card slot, and the following signal processing module is also packaged on the bottom plate; the signal processing module is used for processing signals transmitted by the signal receiving module, or when the unmanned aerial vehicle has an internet connection, sending a download request of broadcast ephemeris, ionospheric model parameters and b2b correction information, calculating the position of the unmanned aerial vehicle through a PPP algorithm, and sending the positioning information to a ground user terminal through WIFI.

[0024] The signal receiving module (for example, a UM980 positioning chip) is used for receiving positioning information, broadcast ephemeris, ionospheric model parameters and b2b correction information (information type 1-information type 7) and screening out incorrect, repeated or incomplete information, so as to ensure correct operation of the signal processing; the signal receiving module and the signal processing module are packaged together through the bottom plate to form a PPP positioning module, as shown in Figure 1 .

[0025] The PPP positioning module can be connected with the unmanned aerial vehicle through a USB interface, or can be directly connected on a mainboard of the unmanned aerial vehicle through a DIP plug, the module uses a low-power consumption design, can rely on the unmanned aerial vehicle USB or mainboard power supply to operate, does not need an additional power supply, and can also use a battery power supply to realize standby starting.

[0026] The antenna root is connected with the antenna attitude control module, the antenna uses a high-gain antenna, is used for ensuring stable satellite signals, and prevents loss of satellite connection caused by tilting of the antenna; the antenna attitude control module receives attitude information sent by the gyroscope, ensures that the antenna is perpendicular to the ground, and makes the antenna gain stable; The gyroscope is used for acquiring the antenna direction and transmitting attitude correction information to the antenna attitude control module; The antenna attitude control module is used for ensuring that the antenna is perpendicular to the ground, so that the received satellite signals remain stable, and preventing loss of satellite connection caused by tilting of the antenna; The antenna, the antenna attitude control module and the gyroscope are assembled into an integrated whole to form a self-adaptive antenna module, the output signals of the antenna and the gyroscope are output through MMCX interfaces, and the self-adaptive antenna module can be connected with the PPP positioning module.

[0027] If the drone antenna can receive PPP-B2B signals, the antenna, gyroscope, and antenna attitude control module in the above-mentioned drone auxiliary positioning device do not need to be installed. Instead, data from the drone antenna is received through the drone interface. If the drone has multiple antennas that can receive satellite signals, the information received by the main antenna is used. Not installing the above-mentioned modules can reduce the size and weight of the device and improve the stability of the device. However, the positioning accuracy, positioning refresh rate, and positioning delay are different from those of products with the above-mentioned modules.

[0028] The positioning method of the above-mentioned UAV auxiliary positioning device has the following steps: (1) Connect the adaptive antenna module to the PPP positioning module, and then connect the USB interface of the PPP positioning module to the drone. After the device is installed, you can connect the device via WIFI through a mobile phone, computer, tablet or other user terminal. After the connection, it will automatically start to receive antenna data and send the positioning to the terminal. The user terminal can be turned off. After turning it off and back on, you need to disconnect and reconnect the USB interface. When receiving data, the antenna receives positioning information and broadcast ephemeris, ionospheric model parameters, and b2b correction information, such as Figure 2 As shown in the figure, when the drone has an Internet connection, if the broadcast time of satellite hourly broadcast information such as broadcast ephemeris and ionospheric model parameters is missed, the drone can download the latest corresponding information from the Internet instead of waiting for the next satellite broadcast in 1~2 hours.

[0029] (2) After receiving the required signal, the signal processing module uses the precise point positioning algorithm to calculate the position of the UAV (a common precise point positioning technology) and sends the PPP positioning information to the user end; When sending PPP positioning data, in addition to real-time broadcasting via WIFI, positioning data or raw data can be written to the SD card at the same time for post-processing and other purposes; when writing raw data, multiple ephemeris data and ionospheric model parameters can be saved in the SD card. When the drone is in a high-speed moving state and other scenarios where positioning consistency and low latency need to be prioritized, it is possible to temporarily not switch to the latest received ephemeris data and ionospheric model parameters, but use the last ephemeris data and ionospheric model parameters in the SD card for processing, and then switch to the new ephemeris data and ionospheric model parameters when the drone is stationary.

[0030] In addition to the Kalman filter algorithm and the error correction algorithm including the PPP-B2b service, the precise point positioning algorithm also includes a fast ambiguity fixation algorithm. The algorithm consists of two processes: decorrelation and search. The purpose of decorrelation is to minimize the correlation among the ambiguity parameters. Specifically: Wherein, N is the integer ambiguity solution, N f is the ambiguity float solution obtained in Kalman filtering, Q N is the residual-covariance matrix of N; The decorrelation operation is completed by integer Gaussian transformation, and after the decorrelation, the process of searching for the optimal ambiguity combination is converted into the process of finding the optimal solution in an n-dimensional sphere. The integer Gaussian transformation and the n-dimensional sphere optimal solution algorithm both belong to common technologies.

[0031] In the operation of the precise point positioning algorithm, the multi-system GNSS combined positioning can be used to increase the number of observed satellites and optimize the positioning accuracy.

[0032] When the unmanned aerial vehicle is in a moving state, the gyro data is used to determine the moving direction when calculating the position, to exclude the wrong prediction results, or to set the weight according to the speed information obtained by the gyroscope to speed up the convergence of the algorithm, specifically: Wherein, r0 is the unprocessed prediction space radius, r1 is the processed prediction space radius, w is the weight coefficient obtained according to the speed information, v1 is the moving speed of the unmanned aerial vehicle transmitted by the gyroscope, v max is the maximum moving speed of the unmanned aerial vehicle; After processing, a new prediction space with a radius of r1 is generated at a distance of (1-w) r0 from the unmanned aerial vehicle in the direction of the unmanned aerial vehicle, replacing the original prediction space, as shown in Figure 3 .

[0033] (3) The positioning information is sent to the handheld terminal through the antenna.

[0034] Embodiment 2: A positioning method of an unmanned aerial vehicle assisted positioning device, the steps are as described in Embodiment 1, the difference is that: In step (2), when receiving data, because the tilt of the antenna will cause the visible satellites to change, the unmanned aerial vehicle is required to send the tilt information of the gyroscope, as shown in Figure 4 , which is used to adjust the satellite weight information to obtain the maximum geometric accuracy. Adding the satellite weight information can make the positioning provided by the device more stable.

[0035] When the main positioning system of the unmanned aerial vehicle is working, the positioning result thereof and the original information received by the antenna can be used to calculate the ambiguity, and the cycle slip detection process is skipped. When the main positioning mode of the unmanned aerial vehicle is working normally, the ambiguity is updated regularly. When the main positioning mode of the unmanned aerial vehicle fails, the last fixed ambiguity is used for positioning, and the cycle slip detection is restarted to speed up the convergence speed of the subsequent positioning. The calculation process of the ambiguity is as follows: Wherein, s represents satellite number, i represents signal frequency, r represents user receiver, Indicates the carrier phase, Is the value of the carrier phase, Indicates the error of the carrier phase value; ρ represents the geometric distance between the user and the satellite, c represents the speed of light, dt r , dt s Respectively represent the receiver and satellite clock error, Indicates the ionospheric delay error, T s Indicates the tropospheric delay error, B r,i , Respectively represent the receiver and satellite phase hardware delay, λ i Indicates the wavelength of i frequency point, Indicates the integer ambiguity of the phase observation; Wherein, the calculation process of ρ is: Wherein, (X s , Y s , Z s ) represents satellite coordinates, (X r , Y r , Z r ) represents receiver coordinates, and the receiver coordinates are substituted into the positioning of the main positioning mode of the unmanned aerial vehicle to solve the ambiguity.

[0036] Embodiment 3: A positioning method of an unmanned aerial vehicle auxiliary positioning device, the steps are as described in embodiment 1, and the difference is that: The unmanned aerial vehicle is stationary, and after convergence is completed, the positioning accuracy of the main positioning system of the unmanned aerial vehicle is verified, the positioning structure of the auxiliary positioning device is compared with the positioning result of the main positioning system of the unmanned aerial vehicle, and when normally operating, the straight line distance of the positioning results of the two systems should be less than 10cm.

[0037] The application realizes the positioning of the unmanned aerial vehicle without internet and base station by using the PPP-b2b signal provided by Beidou-3 and the positioning information provided by each satellite system, ionospheric model parameters and ephemeris data, solves the related problems that the unmanned aerial vehicle cannot be positioned to obtain whole process information without internet and base station, the working state of the matched adaptive antenna is automatically maintained in the vertical state with the ground, the positioning accuracy of the unmanned aerial vehicle is improved, and in addition, the device is convenient to move and disassemble.

[0038] The various embodiments in this specification are described in a progressive manner, with each embodiment focusing on the differences from other embodiments. Reference can be made to the common and similar parts between the various embodiments. For the devices disclosed in the embodiments, since they correspond to the methods disclosed in the embodiments, the description is relatively simple, and the relevant parts can be referred to the method description.

[0039] The above description of the disclosed embodiments enables those skilled in the art to implement or use the present invention.

[0040] Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the invention. Therefore, the present invention is not limited to the embodiments shown herein, but is to be construed in the widest manner consistent with the principles and novel features disclosed herein.

Claims

1. A drone auxiliary positioning device, characterized in that: It includes a signal processing module, a signal receiving module, an antenna, a gyroscope and an antenna attitude control module. The signal processing module is used to process the signal transmitted by the signal receiving module, perform PPP positioning, and send the positioning information to the ground user terminal; Signal receiving module: used to receive positioning information and broadcast ephemeris, ionospheric model parameters, b2b correction information and filter out garbled, repeated or incomplete information; Antenna: Use a high-gain antenna to ensure the integrity of the received signal, and use an independent power supply circuit to prevent the external electromagnetic environment from affecting other modules of the device; Gyroscope: used to obtain antenna direction and transmit antenna attitude information to the antenna attitude control module; Antenna attitude control module: used to ensure that the antenna is perpendicular to the ground so that the received satellite signal remains stable.

2. The positioning method of the UAV-assisted positioning device according to claim 1, characterized in that: Here are the steps: (1) Connect the auxiliary positioning device to the UAV and, when receiving data, receive positioning information and broadcast ephemeris, ionospheric model parameters, and b2b correction information through the antenna or send a download request for broadcast ephemeris, ionospheric model parameters, and b2b correction information when the UAV has an Internet connection; (2) After receiving the required signal, the signal processing module calculates the position of the drone through the precise single point positioning algorithm (3) The positioning information is sent to the handheld terminal via the antenna.

3. The positioning method of the UAV-assisted positioning device according to claim 2, characterized in that: In step (2), when sending PPP positioning data, in addition to real-time broadcasting, the positioning data or original data is also written to the SD card; The SD card stores multiple ephemeris data and ionospheric model parameters. The device uses the most recent ephemeris data and ionospheric model parameters by default. When the drone is moving and needs to prioritize positioning consistency and low latency, it does not switch to the latest received ephemeris data and ionospheric model parameters. Instead, it uses the last ephemeris data and ionospheric model parameters in the SD card for processing. The new ephemeris data and ionospheric model parameters are saved in the SD card and then switched when the drone is stationary.

4. The positioning method of the UAV-assisted positioning device according to claim 2, wherein: The precise point positioning algorithm includes the Kalman filter algorithm, the error correction algorithm of the PPP-B2b service, the fast ambiguity fixation algorithm and the multi-system GNSS combined positioning algorithm.

5. The positioning method of the UAV-assisted positioning device according to claim 2, characterized in that: In step (2), when the drone is in a moving state, the gyroscope data is used to determine the moving direction when calculating the positioning, eliminating incorrect prediction results, or setting weights based on the speed information obtained by the gyroscope to accelerate the convergence of the algorithm. The algorithm is the PPP-B2B positioning algorithm, specifically: Among them, r0 is the unprocessed prediction space radius, r1 is the processed prediction space radius, w is the weight coefficient obtained according to the speed information, v1 is the moving speed of the drone transmitted by the gyroscope, and v max is the maximum speed of the drone; After processing, a new prediction space with a radius of r1 is generated at the distance r0 from the drone in the direction of the drone (1-w), replacing the original prediction space.

6. The positioning method of the UAV-assisted positioning device according to claim 2, characterized in that: When the main positioning system of the drone is working, the ambiguity is calculated using its positioning results and the original information received by the antenna, skipping the cycle slip detection process. When the drone positioning is working normally, the ambiguity will be updated regularly. When the main positioning method of the drone fails, the most recent ambiguity will be used for positioning, and the cycle slip detection will be restarted to accelerate the convergence speed of subsequent positioning. The calculation process of fuzziness is as follows: Where s represents the satellite number, i represents the signal frequency, and r represents the user receiver. represents the carrier phase, is the value of the carrier phase, Indicates the error of the carrier phase value; ρ represents the geometric distance between the user and the satellite, c represents the speed of light, dt r 、dt s denote the receiver and satellite clock errors respectively, represents the ionospheric delay error, T s represents the tropospheric delay error, B r,i 、 are the phase hardware delays of the receiver and satellite, respectively, i represents the wavelength of frequency i, Represents the integer ambiguity of the phase observation; The calculation process of ρ is: Among them, (X s , Y s , Z s ) represents the satellite coordinates, (X r , Y r , Z r ) represents the receiver coordinates. After substituting the receiver coordinates into the positioning obtained by the main positioning method of the UAV, the ambiguity can be resolved.

7. The positioning method of the UAV-assisted positioning device according to claim 2, characterized in that: When the drone is stationary and convergence is complete, verify the positioning accuracy of the drone's main positioning system and compare the positioning structure of the auxiliary positioning device with the positioning results of the drone's main positioning system. During normal operation, the straight-line distance between the positioning results of the two systems should be less than 10 cm.

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