Satellite positioning method and apparatus for positioning unmanned aerial vehicle, and unmanned-aerial-vehicle terminal and storage medium

Abstract

A satellite positioning method and apparatus for positioning an unmanned aerial vehicle, and an unmanned-aerial-vehicle terminal and a storage medium. The positioning method comprises: (S1) acquiring zone configuration information, and satellite observation data of several satellites; (S2) on the basis of the satellite observation data, calculating terminal location information; (S3) on the basis of the zone configuration information and the terminal location information, determining a zone where a terminal is located; (S4) acquiring zone SSR correction data of the zone where the terminal is located; (S5) on the basis of the terminal location information, the satellite observation data and the zone SSR correction data, calculating a virtual satellite observation value; (S6) on the basis of the zone SSR correction data and the virtual satellite observation value, constructing OSR observation data; and (S7) sending the virtual satellite observation value and the OSR observation data to an unmanned aerial vehicle, such that the unmanned aerial vehicle performs positioning calculation. The conversion of data of an SSR-type into data of an OSR type is realized, thereby solving the problem of it being impossible to apply conventional positioning technology to an unmanned aerial vehicle.

Description

Satellite positioning method and device for positioning unmanned aerial vehicle, unmanned aerial vehicle terminal and storage medium TECHNICAL FIELD

[0001] The present application relates to the technical field of satellite positioning, and particularly relates to a satellite positioning method and device for positioning unmanned aerial vehicle, an unmanned aerial vehicle terminal and a storage medium. BACKGROUND

[0002] At present, unmanned aerial vehicle automatic inspection has become the most important power grid transmission line operation and maintenance technology, and the unmanned aerial vehicle automatic inspection needs a ground-based augmentation system (GBAS) to provide real-time dynamic positioning service (RTK).

[0003] Domestic and foreign experts have proposed a PPP-RTK positioning technology based on a satellite-based augmentation system (SBAS), which combines the advantages of PPP technology and RTK technology, has the characteristics of short convergence time and high positioning accuracy, but the PPP-RTK technology belongs to a state space domain (SSR) augmentation service, and a traditional unmanned aerial vehicle only supports an observation space domain (OSR) augmentation service, and the current PPP-RTK technology cannot be directly applied to the existing unmanned aerial vehicle. How to apply the PPP-RTK technology to the unmanned aerial vehicle is a problem to be solved. SUMMARY

[0004] The present application provides a satellite positioning method and device for positioning unmanned aerial vehicle, an unmanned aerial vehicle terminal and a storage medium, to solve the technical problem that the traditional positioning technology cannot be applied to the unmanned aerial vehicle.

[0005] In order to solve the above technical problems, the present application provides a satellite positioning method for positioning unmanned aerial vehicle, comprising:

[0006] Obtaining partition configuration information and satellite observation data of a plurality of satellites;

[0007] According to all the satellite observation data, the terminal position information is calculated;

[0008] According to the partition configuration information and the terminal position information, the partition in which the terminal is located is determined;

[0009] Obtaining the partition SSR correction data of the partition in which the terminal is located;

[0010] calculating satellite virtual observation values according to the terminal position information, the satellite observation data and the partition SSR correction data;

[0011] constructing OSR observation data according to the partition SSR correction data and the satellite virtual observation values;

[0012] sending the satellite virtual observation values and the OSR observation data to the UAV, so that the UAV performs positioning calculation according to the satellite virtual observation values and the OSR observation data.

[0013] As a preferred solution, the satellite observation data comprises satellite position data and data sending time stamps;

[0014] The calculation of the terminal position information according to the satellite observation data comprises:

[0015] acquiring data receiving time stamps of each satellite observation data;

[0016] calculating distances between each satellite and the terminal according to the satellite position data, the data sending time stamps and the data receiving time stamps corresponding to each satellite;

[0017] determining the terminal position information according to the distances between each satellite and the terminal.

[0018] As a preferred solution, before acquiring the partition SSR correction data of the partition where the terminal is located, the method further comprises:

[0019] performing a mobile network stability test and determining whether the mobile network stability test passes, if yes, setting the communication mode as a network mode, and if no, setting the communication mode as a satellite mode;

[0020] The acquisition of the partition SSR correction data of the partition where the terminal is located comprises:

[0021] if the communication mode is the network mode, logging in a remote server, connecting a partition SSR source node corresponding to the partition where the terminal is located in the server according to the partition where the terminal is located, and acquiring the partition SSR correction data of the corresponding partition;

[0022] if the communication mode is the satellite mode, acquiring wide-area SSR data broadcast by satellites, and acquiring the partition SSR correction data of the corresponding partition from the wide-area SSR data according to the partition where the terminal is located.

[0023] As a preferred solution, the mobile network stability test comprises:

[0024] repeatedly performing remote server login operations for a preset number of times at a frequency of one login operation per period;

[0025] Judge whether all remote server login operations are successful, if yes, pass the mobile network stability test, if not, fail the mobile network stability test.

[0026] As a preferred solution, the calculating satellite virtual observation value according to the terminal position information, the satellite observation data and the partition SSR correction data comprises:

[0027] According to the partition SSR correction data, the satellite observation data is corrected to obtain corrected satellite observation data;

[0028] According to the corrected satellite observation data and the terminal position information, satellite virtual observation data is calculated.

[0029] As a preferred solution, the constructing OSR observation data according to the partition SSR correction data and the satellite virtual observation value comprises:

[0030] According to the satellite virtual observation value, the geometric distance from the satellite to the virtual reference station is calculated;

[0031] According to the partition SSR correction data and the satellite virtual observation value, the earth rotation correction number, the troposphere zenith delay, the ionosphere slant delay, the antenna phase center deviation, the antenna phase center deviation correction number and the hardware delay correction number are calculated;

[0032] According to the earth rotation correction number, the troposphere zenith delay, the ionosphere slant delay, the antenna phase center deviation, the antenna phase center deviation correction number and the hardware delay correction number, the OSR observation data is constructed.

[0033] As a preferred solution, the sending the satellite virtual observation value and the OSR observation data to the unmanned aerial vehicle comprises:

[0034] The OSR observation data is converted into RTCM 3.x format to obtain converted OSR observation data;

[0035] The satellite virtual observation value and the converted OSR observation data are sent to the unmanned aerial vehicle.

[0036] On the basis of the above embodiment, another embodiment of the application provides a satellite positioning device for positioning unmanned aerial vehicles, comprising a data acquisition module, a data processing module and a data sending module.

[0037] The data acquisition module is configured to acquire partition configuration information and satellite observation data of a plurality of satellites.

[0038] The data processing module is configured to calculate terminal position information according to all the satellite observation data, and determine a partition in which the terminal is located according to the partition configuration information and the terminal position information.

[0039] The data acquisition module is further configured to acquire partition SSR correction data of the partition in which the terminal is located.

[0040] The data processing module is further configured to calculate satellite virtual observation values according to the terminal position information, the satellite observation data and the partition SSR correction data, and construct OSR observation data according to the partition SSR correction data and the satellite virtual observation values.

[0041] The data sending module is further configured to send the satellite virtual observation values and the OSR observation data to the unmanned aerial vehicle, so that the unmanned aerial vehicle performs positioning calculation according to the satellite virtual observation values and the OSR observation data.

[0042] On the basis of the above-mentioned embodiments, a further embodiment of the application provides an unmanned aerial vehicle terminal, which comprises a processor, a memory and a computer program stored in the memory and configured to be executed by the processor, and the processor implements the satellite positioning method of the above-mentioned embodiments of the application when executing the computer program.

[0043] On the basis of the above-mentioned embodiments, a further embodiment of the application provides a storage medium, which comprises a stored computer program, wherein the satellite positioning method of the above-mentioned embodiments of the application is performed by a device in which the storage medium is located when the computer program runs.

[0044] Compared with the prior art, the embodiments of the application have the following beneficial effects:

[0045] This invention acquires partition configuration information and satellite observation data from several satellites; calculates terminal location information based on all the satellite observation data; determines the partition where the terminal is located based on the partition configuration information and the terminal location information; acquires partition SSR correction data for the partition where the terminal is located; calculates virtual satellite observation values ​​based on the terminal location information, the satellite observation data, and the partition SSR correction data; constructs OSR observation data based on the partition SSR correction data and the virtual satellite observation values; and sends the virtual satellite observation values ​​and the OSR observation data to the UAV, enabling the UAV to perform positioning calculations based on the virtual satellite observation values ​​and the OSR observation data. This invention determines the corresponding partition SSR correction data through satellite observation data, then determines the terminal location information and generates virtual satellite observation data, and then constructs OSR observation data based on the virtual satellite observation data and the partition SSR data, realizing the conversion of SSR type data to OSR type data and solving the technical problem that traditional positioning technologies cannot be applied to UAVs. Attached Figure Description

[0046] Figure 1 is a schematic flowchart of a satellite positioning method for locating a drone according to an embodiment of the present invention;

[0047] Figure 2 is a schematic diagram of a satellite positioning device for locating unmanned aerial vehicles provided in an embodiment of the present invention. Detailed Implementation

[0048] To make the objectives, technical solutions, and advantages of this application clearer, the technical solutions of this application will be clearly and completely described below with reference to the accompanying drawings of the embodiments. Obviously, the described embodiments are only some embodiments of this application, not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0049] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application pertains; the terminology used herein is for the purpose of describing particular embodiments only and is not intended to limit the application; the terms “comprising” and “having”, and any variations thereof, in the specification, claims, and foregoing description of the drawings are intended to cover non-exclusive inclusion.

[0050] In this document, the term "embodiment" means that a particular feature, structure, or characteristic described in connection with an embodiment may be included in at least one embodiment of this application. The appearance of this phrase in various places throughout the specification does not necessarily refer to the same embodiment, nor is it a separate or alternative embodiment mutually exclusive with other embodiments. It will be explicitly and implicitly understood by those skilled in the art that the embodiments described herein can be combined with other embodiments.

[0051] In the description of the embodiments in this application, the term "and / or" is merely a description of the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A existing alone, A and B existing simultaneously, or B existing alone. Additionally, the character " / " in this document generally indicates that the preceding and following related objects have an "or" relationship.

[0052] In the description of the embodiments of this application, the term "several" refers to two or more (including two).

[0053] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0054] Example 1

[0055] Please refer to Figure 1, which is a flowchart illustrating a satellite positioning method for locating a drone according to an embodiment of the present invention, including:

[0056] S1. Obtain partition configuration information and satellite observation data for several satellites.

[0057] It should be noted that the partition configuration information specifies how many partitions the SSR data is divided into, as well as the coordinate information of each partition.

[0058] S2. Calculate the terminal location information based on all the satellite observation data.

[0059] In a preferred embodiment, the satellite observation data includes: satellite position data and data transmission timestamps;

[0060] The step of calculating the terminal location information based on the satellite observation data includes:

[0061] Obtain the data reception timestamp for each satellite observation data;

[0062] The distance between each satellite and the terminal is calculated based on the satellite position data, data transmission timestamp, and data reception timestamp corresponding to each satellite.

[0063] The terminal location information is determined based on the distance between each satellite and the terminal.

[0064] In this embodiment, the terminal obtains observation values ​​through a GNSS antenna. The observation values ​​include the satellite's position information (orbit) and signal transmission time information. By calculating the reception time and electromagnetic wave transmission speed, the propagation time of the satellite signal is calculated, and the distance between the terminal and the satellite is obtained. By calculating the distance between the terminal and at least four satellites, the initial coordinate position of the terminal in three-dimensional space is determined.

[0065] S3. Determine the partition where the terminal is located based on the partition configuration information and the terminal location information.

[0066] S4. Obtain the partition SSR correction data of the partition where the terminal is located.

[0067] In a preferred embodiment, before obtaining the partition SSR correction data of the partition where the terminal is located, the method further includes:

[0068] Perform a mobile network stability test and determine whether the mobile network stability test passes. If it does, set the communication mode to network mode; otherwise, set the communication mode to satellite mode.

[0069] The step of obtaining the partition SSR correction data of the partition where the terminal is located includes:

[0070] If the communication mode is network mode, log in to the remote server; according to the partition where the terminal is located, connect to the corresponding partition SSR source node in the server, and obtain the corresponding partition SSR correction data.

[0071] If the communication mode is satellite mode, then the wide-area SSR data broadcast by the satellite is obtained; according to the partition where the terminal is located, the partition SSR correction data of the corresponding partition is obtained from the wide-area SSR data.

[0072] It should be noted that power grid transmission lines need to cross mountainous areas, and the on-site communication environment is relatively complex. When there is no mobile communication network coverage on-site, drones cannot achieve RTK positioning and cannot perform automatic inspections, which greatly reduces the efficiency of power transmission line inspections. Therefore, this invention enables the adoption of appropriate communication methods based on the on-site communication conditions.

[0073] Depending on the on-site communication environment, it operates in two modes and can automatically switch modes by detecting the communication environment in real time. Based on the availability of a 4G mobile communication network, the operating modes can be categorized as network mode and satellite mode.

[0074] In this embodiment, when the working mode is network mode, the terminal connects to the network through the 4G communication antenna, logs into the remote server, and verifies the username and password; according to the partition where the terminal is located, it finds the corresponding partition SSR source node in the server, connects to the source node of the remote server, and obtains the corresponding partition SSR correction data.

[0075] When the operating mode is satellite mode, it receives wide-area SSR data broadcast by the satellite antenna; and retrieves the corresponding partition SSR correction data from the wide-area SSR data according to the partition where the terminal is located.

[0076] In a preferred embodiment, the mobile network stability test includes:

[0077] The remote server login operation is repeated a preset number of times at a frequency of once per cycle.

[0078] Determine whether all remote server login operations were successful. If so, the mobile network stability test is passed; otherwise, the mobile network stability test is failed.

[0079] In this embodiment, a mobile network stability test is conducted using a 4G communication antenna. The test involves repeatedly logging into the remote server over N consecutive cycles, with each cycle lasting 2 seconds. If the server login success rate is 100% over N cycles, the system enters network mode. If the success rate is less than 100%, the system enters satellite mode. N can be customized based on the on-site communication conditions.

[0080] S5. Calculate the virtual satellite observation value based on the terminal location information, the satellite observation data, and the partition SSR correction data.

[0081] It should be noted that satellite observation data includes: pseudorange observations, carrier phase observations, Doppler observations, signal strength, timestamps, and satellite information.

[0082] Partitioned SSR correction data includes: satellite orbital error, satellite clock error, phase fractional deviation, ionospheric delay error, and tropospheric delay error;

[0083] The process of calculating virtual satellite observations includes: calculating the geometric distance between the station and the satellite, calculating the phase winding correction of the satellite antenna, calculating the phase center deviation correction of the satellite antenna, calculating the phase center change correction of the satellite antenna, calculating the multipath correction between BeiDou satellites, calculating the ionospheric delay correction, calculating the tropospheric delay correction, and calculating the phase decimal deviation correction.

[0084] In a preferred embodiment, calculating the virtual satellite observation value based on the terminal location information, the satellite observation data, and the partitioned SSR correction data includes:

[0085] Based on the partitioned SSR correction data, the satellite observation data is corrected to obtain the corrected satellite observation data.

[0086] Based on the corrected satellite observation data and the terminal location information, calculate the satellite virtual observation data.

[0087] In this embodiment, satellite coordinate errors mainly include satellite performance errors and atmospheric delay errors during signal propagation. The process involves substituting partitioned SSR correction data into the calculation of the satellite's average angular velocity, planning time, mean anomaly angle, off-anomaly angle, true anomaly angle, and perturbation correction terms. The calculated perturbation correction terms are then used to calculate the perturbation-corrected ascending distance angle, satellite radius vector, and orbital inclination. Finally, the satellite observation data is calculated. The specific process for correcting satellite observation data is as follows:

[0088] Substitute the partitioned SSR correction data into the following steps to calculate more accurate coordinates:

[0089] (1) Calculate the average angular velocity n of the satellite:

[0090] According to Kepler's third law, calculate the average angular velocity n0 of the satellite without perturbations. Here, μ is the Earth's gravitational constant in the Earth coordinate system, μ = 3.986005 × 10¹⁴ m³ / s². Considering the perturbation correction Δn given in the satellite message, calculate the actual average angular velocity n = n0 + Δn;

[0091] (2) Calculate the normalization time t k :

[0092] Normalize the observation time t to the GPS time system, t k = t - toe, where toe is the reference time given in the satellite message;

[0093] (3) Calculate the mean perihelion angle M of the satellite at the observation time. k :

[0094] Use formula M k =M0+n tk Calculate the angle M of the mean anterior point k , where M0 is the mean anterior angle of the reference time toe;

[0095] (4) Calculate the near-point angle E k :

[0096] Angle E (nearest point) k The calculation requires iteration. First, let E... k =M k , substitute into formula E k =M k+e*sin(E k The new E is calculated. k The value, e, represents the satellite orbital eccentricity;

[0097] (5) Calculate the true anterior angle V k Other relevant parameters:

[0098] Based on the near point angle E k Calculate the true anterior angle V k The details are as follows:

[0099] Calculate the ascending intersection angle Φ based on parameters such as perigee angular distance ω given in the satellite message. k Specifically, as follows: φ k =V k +ω;

[0100] (6) Consider perturbation corrections:

[0101] Based on the information provided by the satellite message, the perturbation correction term δ for the ascending distance angle u, the satellite radius vector r, and the orbital inclination i is calculated. u δ r δ i ,

[0102] C uc C us C rc C rs C ic C is Obtained from satellite messages.

[0103] (7) Calculate the coordinates after perturbation correction:

[0104] Using perturbation correction term δ u δ r δ i Calculate the perturbation-corrected ascending intersection distance angle u. k Satellite radius r k and orbital inclination i k The details are as follows:

[0105] (8) Calculate the satellite's coordinates in the orbital plane coordinate system:

[0106] Based on the perturbation-corrected ascending intersection angle u k Satellite radius r k and orbital inclination i k The coordinates of the satellite in the orbital plane coordinate system are calculated as follows:

[0107] (9) Transform to the geocentric coordinate system:

[0108] If necessary, the satellite's coordinates in the orbital plane coordinate system can be transformed to the geocentric coordinate system.

[0109] The process of calculating satellite virtual observation data includes:

[0110] (1) Based on the terminal location information, find the nearest reference station and use it as the main reference reference station;

[0111] (2) Based on the baseline between the main reference station and other reference stations, calculate the bifurcated atmospheric parameters, including ionospheric delay and tropospheric delay, etc.

[0112] (3) Using interpolation, estimate the virtual limit double-difference atmospheric parameters from the known double-difference atmospheric parameters;

[0113] (4) Convert the double-difference atmospheric parameters into single-difference atmospheric parameters;

[0114] (5) Generate satellite virtual observation data based on single-difference atmospheric parameters.

[0115] S6. Construct OSR observation data based on the partitioned SSR correction data and the satellite virtual observation values.

[0116] In a preferred embodiment, constructing OSR observation data based on the partitioned SSR correction data and the satellite virtual observations includes:

[0117] Calculate the geometric distance from the satellite to the virtual reference station based on the virtual satellite observations.

[0118] Based on the partitioned SSR correction data and the satellite virtual observations, calculate the Earth rotation correction, tropospheric zenith delay, ionospheric slant delay, antenna phase center deviation, antenna phase center deviation correction, and hardware delay correction;

[0119] OSR observation data are constructed based on the Earth rotation correction, the tropospheric zenith delay, the ionospheric slant delay, the antenna phase center deviation, the antenna phase center deviation correction, and the hardware delay correction.

[0120] In this embodiment, the process of constructing OSR observation data includes:

[0121] (1) Analyze SSR correction data. Obtain precise orbital corrections, precise clock error corrections, uncalibrated phase delay corrections (UPD), and regional atmospheric corrections;

[0122] (2) Calculate the initial pseudorange. The initial pseudorange needs to be calculated iteratively based on the broadcast ephemeris, virtual reference station coordinates, and epoch time. The calculation process is as follows:

[0123] 1) The initial signal propagation time dt0 is set to an empirical value of 0.08s;

[0124] 2) Calculate the signal transmission time based on the epoch time and signal propagation time;

[0125] 3) Calculate satellite positions and clock biases based on broadcast ephemeris;

[0126] 4) Calculate the geometric distance based on the satellite position and the coordinates of the virtual reference station;

[0127] 5) Calculate the signal propagation time dt based on the geometric distance;

[0128] 6) Calculate the difference between the signal propagation time and the initial signal propagation time, Δdt = |dt - dt0|, and determine whether the difference is less than the threshold. If it is less than the threshold, the iteration terminates, and the initial pseudorange value is calculated according to formula (1); otherwise, the initial signal transmission time is updated, and the calculation is restarted from step 2) until the condition is met.

[0129] 7) Formula for calculating the initial value of pseudorange: P0=ρ-cdts (1)

[0130] In the formula, P0 is the initial value of pseudorange, ρ is the geometric distance from the satellite to the virtual reference station, c is the speed of light, and dts is the satellite clock error;

[0131] (3) Calculate the precise satellite position and satellite clock bias based on the broadcast ephemeris and orbit and clock bias corrections: X orbit =X broadcast -δX (2)

[0132] In the formula, X broadcast X is the satellite position calculated from the broadcast ephemeris. orbit δX represents the satellite position correction obtained after orbital corrections. broadcast The satellite clock bias (dts) is calculated from the broadcast ephemeris. satellite The satellite clock error is obtained after correction by the clock error correction factor, where C0 is the clock error correction factor;

[0133] (4) Calculate the solid tide correction and correct the virtual reference station coordinates: X' vrs =X vrs +δX tide Y' vrs =Y vrs +δY tide Z' vrs =Z vrs+δZ tide (4)

[0134] In the formula, (δX tide ,δY tide ,δZ tide ) represents the fixed tide correction;

[0135] (5) Calculate the geometric distance ρ between satellite S and the virtual reference station. s :

[0136] (6) Calculate the Earth's rotation correction.

[0137] (7) Calculate the tropospheric oblique delay of the virtual reference station location based on the virtual reference station location and the regional atmospheric correction:

[0138] 1) Calculate the Zenith tropospheric dry delay (ZHD) using the Sasstamoinen model.

[0139] 2) Construct an error model and calculate the tropospheric wet delay ZWD

[0140] 3) Calculate the tropospheric mapping function mf

[0141] 4) The tropospheric zenith delay is:

[0142] (8) Calculate the ionospheric slack delay of the virtual reference station location based on the virtual reference station location and regional atmospheric corrections:

[0143] An error model was constructed to calculate the ionospheric slant delay. The ionospheric model combines a polynomial model with gridded ionospheric residuals, and the model formula is as follows: stec s =C 00 +C 01 *(φ r -φ0)+C 10 *(λ r -λ0)+C 11 *(φ r -φ0)* (λ r -λ0)+Δstec s (6)

[0144] In the formula, stec s For the ionospheric delay of satellite S; C 00 C 01 C 10 C 11 The coefficients are polynomial coefficients; (λ) r ,φ r(λ0, φ0) represents the user's location coordinates (latitude and longitude in radians); (λ0, φ0) represents the latitude and longitude (radians) of the center point of the modeling area, which can be calculated from the area's coordinates; Δstec s The interpolated value of the grid ionospheric residual can be obtained by interpolation through four grid points around the user or grid points within a certain range around the user;

[0145] Interpolation can be performed directly using the inverse distance interpolation method. The grid point coordinates can be calculated based on the coordinates of the lower left corner of the region and the latitude and longitude step size. The formula is as follows:

[0146] In the formula, W i The weights calculated based on the distance from the user to the surrounding grid points.

[0147] The ionospheric value calculated by formula (6) is in TECU and needs to be converted to meters using the following formula (8). Where f1 is the frequency value of the first frequency of the satellite.

[0148] (9) Calculate the phase winding correction d of the satellite antenna. windup

[0149] (10) Calculate the phase center deviation of the satellite antenna Antenna phase center deviation correction

[0150] (11) Calculate the hardware delay correction for raw observation data based on the uncalibrated phase hardware delay correction.

[0151] In the formula, For satellite S narrow lane UPD, Satellite S-width UPD, f is the frequency

[0152] (12) Based on the error corrections calculated in steps (1) to (11), construct the OSR observation data.

[0153] In the formula, These are pseudorange observations at the first frequency; These are pseudorange observations at the second frequency; These are carrier observations at the first frequency; These are carrier observations at the second frequency.

[0154] S7. The satellite virtual observation values ​​and the OSR observation data are sent to the UAV so that the UAV can perform positioning calculations based on the satellite virtual observation values ​​and the OSR observation data.

[0155] In a preferred embodiment, sending the satellite virtual observations and the OSR observation data to the UAV includes:

[0156] The OSR observation data is converted into RTCM 3.x format to obtain the converted OSR observation data;

[0157] The satellite virtual observations and the converted OSR observation data are sent to the UAV.

[0158] In this embodiment, the terminal forwards OSR data to the drone via Wi-Fi or a data cable. Specifically, parameter management is initialized, and the validity of usernames, passwords, and source nodes is restricted. OSR-encoded RTCM 3.x format differential data serves as the data source, and an NtripServer is automatically created and partitioned internally. A TCPServer is created based on a fixed IP address and port, and the presence of TCPClient connections is monitored in real time. Ntrip login information from the TCPClient is received and authenticated. If authentication is successful, partitioning and caching are performed based on the initial location information in the login information. Data forwarding is performed between NtripServers and NtripClients mounted to the same source node, and matching NtripServer data is transparently transmitted to all matching NtripClients. The drone logs into the NtripCaster as an NtripClient and receives differential data. After receiving the differential data, the drone performs RTK positioning and initiates automatic inspection.

[0159] Example 2

[0160] Please refer to Figure 2, which is a structural schematic diagram of a satellite positioning device for locating a drone according to an embodiment of the present invention, including: a data acquisition module, a data processing module, and a data transmission module;

[0161] The data acquisition module is used to acquire partition configuration information and satellite observation data of several satellites;

[0162] The data processing module is used to calculate the terminal location information based on all the satellite observation data; and to determine the partition where the terminal is located based on the partition configuration information and the terminal location information.

[0163] The data acquisition module is also used to acquire the partition SSR correction data of the partition where the terminal is located;

[0164] The data processing module is further configured to calculate virtual satellite observation values ​​based on the terminal location information, the satellite observation data, and the partitioned SSR correction data; and to construct OSR observation data based on the partitioned SSR correction data and the virtual satellite observation values.

[0165] The data transmission module is further configured to transmit the satellite virtual observation values ​​and the OSR observation data to the UAV, so that the UAV can perform positioning calculations based on the satellite virtual observation values ​​and the OSR observation data.

[0166] Example 3

[0167] Accordingly, this invention provides a drone terminal, which includes a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor. When the processor executes the computer program, it implements the satellite positioning method described in the above-described embodiments of the invention.

[0168] Example 4

[0169] Accordingly, embodiments of the present invention provide a storage medium, the storage medium including a stored computer program, wherein, when the computer program is running, it controls the device where the storage medium is located to execute the satellite positioning method described in the above embodiments of the invention.

[0170] It should be noted that the device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate, and the components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs. Furthermore, in the accompanying drawings of the device embodiments provided by this invention, the connection relationships between modules indicate that they have communication connections, which can be specifically implemented as one or more communication buses or signal lines. Those skilled in the art can understand and implement this without any creative effort.

[0171] Those skilled in the art will clearly understand that, for convenience and brevity, the specific working process of the device described above can be referred to the corresponding process in the foregoing method embodiments, and will not be repeated here.

[0172] The drone terminal can be a computing device such as a desktop computer, laptop, handheld computer, or cloud server. The drone terminal may include, but is not limited to, a processor and memory.

[0173] The processor can be a Central Processing Unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor can be a microprocessor or any conventional processor. The processor is the control center of the device, connecting various parts of the device via various interfaces and lines.

[0174] The memory can be used to store the computer program. The processor implements various functions of the device by running or executing the computer program stored in the memory and calling data stored in the memory. The memory may mainly include a program storage area and a data storage area. The program storage area may store the operating system, applications required for at least one function, etc.; the data storage area may store data created based on the use of the mobile phone, etc. In addition, the memory may include high-speed random access memory, and may also include non-volatile memory, such as hard disk, RAM, plug-in hard disk, smart media card (SMC), secure digital (SD) card, flash card, at least one disk storage device, flash memory device, or other volatile solid-state storage device.

[0175] The storage medium is a storage medium in which the computer program is stored. When executed by a processor, the computer program can implement the steps of the various method embodiments described above. The computer program includes computer program code, which can be in the form of source code, object code, executable file, or some intermediate form. The computer-readable medium can include any entity or device capable of carrying the computer program code, recording media, USB flash drive, portable hard drive, magnetic disk, optical disk, computer memory, read-only memory (ROM), random access memory (RAM), electrical carrier signals, telecommunication signals, and software distribution media, etc. It should be noted that the content included in the computer-readable medium can be appropriately added or removed according to the requirements of legislation and patent practice in the jurisdiction. For example, in some jurisdictions, according to legislation and patent practice, computer-readable media do not include electrical carrier signals and telecommunication signals.

[0176] The above description represents the preferred embodiments of the present invention. It should be noted that those skilled in the art can make various improvements and modifications without departing from the principles of the present invention, and these improvements and modifications are also considered to be within the scope of protection of the present invention.

Claims

1. A satellite positioning method for locating unmanned aerial vehicles (UAVs), characterized in that, A terminal suitable for use with drones, wherein the terminal is located in the same partition as the drone and is communicatively connected; The satellite positioning method includes: Obtain partition configuration information and satellite observation data from several satellites; Calculate the terminal location information based on all the aforementioned satellite observation data; The partition where the terminal is located is determined based on the partition configuration information and the terminal location information; Obtain the partition SSR correction data of the partition where the terminal is located; Based on the terminal location information, the satellite observation data, and the partitioned SSR correction data, calculate the virtual satellite observation value; Based on the partitioned SSR correction data and the satellite virtual observations, OSR observation data is constructed; The satellite virtual observation values ​​and the OSR observation data are sent to the UAV so that the UAV can perform positioning calculations based on the satellite virtual observation values ​​and the OSR observation data.

2. The satellite positioning method as described in claim 1, characterized in that, The satellite observation data includes: satellite position data and data transmission timestamps; The step of calculating the terminal location information based on the satellite observation data includes: Obtain the data reception timestamp for each satellite observation data; The distance between each satellite and the terminal is calculated based on the satellite position data, data transmission timestamp, and data reception timestamp corresponding to each satellite. The terminal location information is determined based on the distance between each satellite and the terminal.

3. The satellite positioning method as described in claim 1, characterized in that, Before obtaining the partition SSR correction data of the partition where the terminal is located, the process also includes: Perform a mobile network stability test and determine whether the mobile network stability test passes. If it does, set the communication mode to network mode; otherwise, set the communication mode to satellite mode. The step of obtaining the partition SSR correction data of the partition where the terminal is located includes: If the communication mode is network mode, log in to the remote server; according to the partition where the terminal is located, connect to the corresponding partition SSR source node in the server, and obtain the corresponding partition SSR correction data. If the communication mode is satellite mode, then the wide-area SSR data broadcast by the satellite is obtained; according to the partition where the terminal is located, the partition SSR correction data of the corresponding partition is obtained from the wide-area SSR data.

4. The satellite positioning method as described in claim 3, characterized in that, The mobile network stability test includes: The remote server login operation is repeated a preset number of times at a frequency of once per cycle. Determine whether all remote server login operations were successful. If so, the mobile network stability test is passed; otherwise, the mobile network stability test is failed.

5. The satellite positioning method as described in claim 1, characterized in that, The step of calculating virtual satellite observation values ​​based on the terminal location information, the satellite observation data, and the partitioned SSR correction data includes: Based on the partitioned SSR correction data, the satellite observation data is corrected to obtain the corrected satellite observation data. Based on the corrected satellite observation data and the terminal location information, calculate the satellite virtual observation data.

6. The satellite positioning method as described in claim 1, characterized in that, The step of constructing OSR observation data based on the partitioned SSR correction data and the satellite virtual observations includes: Calculate the geometric distance from the satellite to the virtual reference station based on the virtual satellite observations. Based on the partitioned SSR correction data and the satellite virtual observations, calculate the Earth rotation correction, tropospheric zenith delay, ionospheric slant delay, antenna phase center deviation, antenna phase center deviation correction, and hardware delay correction; OSR observation data are constructed based on the Earth rotation correction, the tropospheric zenith delay, the ionospheric slant delay, the antenna phase center deviation, the antenna phase center deviation correction, and the hardware delay correction.

7. The satellite positioning method as described in claim 1, characterized in that, The step of sending the satellite virtual observation values ​​and the OSR observation data to the UAV includes: The OSR observation data is converted into RTCM 3.x format to obtain the converted OSR observation data; The virtual satellite observations and the converted OSR observation data are sent to the UAV.

8. A satellite positioning device for locating unmanned aerial vehicles (UAVs), characterized in that, include: Data acquisition module, data processing module, and data sending module; The data acquisition module is used to acquire partition configuration information and satellite observation data of several satellites; The data processing module is used to calculate the terminal location information based on all the satellite observation data; and to determine the partition where the terminal is located based on the partition configuration information and the terminal location information. The data acquisition module is also used to acquire the partition SSR correction data of the partition where the terminal is located; The data processing module is further configured to calculate virtual satellite observation values ​​based on the terminal location information, the satellite observation data, and the partitioned SSR correction data; and to construct OSR observation data based on the partitioned SSR correction data and the virtual satellite observation values. The data transmission module is further configured to transmit the satellite virtual observation values ​​and the OSR observation data to the UAV, so that the UAV can perform positioning calculations based on the satellite virtual observation values ​​and the OSR observation data.

9. A drone terminal, characterized in that, It includes a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor, wherein the processor, when executing the computer program, implements the satellite positioning method as described in any one of claims 1 to 7.

10. A storage medium, characterized in that, The storage medium includes a stored computer program, wherein, when the computer program is executed, it controls the device containing the storage medium to perform the satellite positioning method as described in any one of claims 1 to 7.

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