An unmanned aerial vehicle navigation verification system based on dead reckoning

Abstract

The application discloses a kind of based on the reckoning of navigation data unmanned plane navigation verification system, belong to unmanned plane navigation verification technical field.The present application solves the problem of positioning error of existing flight calibration, flight route is planned by route planning module, central controller drives unmanned plane to fly according to predetermined route;The coordinates of the current position of unmanned plane, trajectory parameter value and movement direction are determined using the dead reckoning module, and the coordinates of the second calibration point are calculated when the unmanned plane reaches the first calibration point to the second calibration point;Whether the current position parameter value of unmanned plane satisfies the preset calibration condition is calibrated by data calibration module, if not, the current position of unmanned plane is corrected to the coordinates of the second calibration point by issuing instructions to the central controller through the correction instruction module;Thus avoid the disadvantages of GPS failure or positioning error in existing flight calibration work, add dead reckoning technology to ensure the accuracy of navigation system and flight calibration work.

Description

Technical Field

[0001] This invention relates to the field of unmanned aerial vehicle (UAV) flight verification technology, and more specifically to a UAV flight verification system based on dead reckoning data. Background Technology

[0002] In the aviation field, calibration flights are the sole means of verifying the accuracy of ground communication, surveillance, and navigation equipment. A calibration flight refers to the process of using a flight calibration aircraft equipped with specialized calibration equipment to inspect and evaluate the quality and tolerances of spatial signals from various navigation, radar, and communication equipment, as well as airport arrival and departure procedures, in accordance with relevant flight calibration standards, to ensure flight safety. A flight calibration report is then issued based on the inspection and evaluation results. Calibration flights can assess the key technical indicators of the monitored ground equipment under dynamic conditions and are an effective way to confirm that the technical condition of the monitored ground equipment meets standards. Moreover, ground equipment requires flight calibration during commissioning acceptance, maintenance, and overhauls, and even equipment operating well and stably requires periodic flight calibration.

[0003] Most existing flight calibration methods in the aviation field involve manned aircraft carrying various testing terminals for flight calibration or using unmanned aerial vehicles (UAVs) based on GPS technology for flight calibration. While these methods can meet the basic requirements of aviation flight calibration, manned aircraft calibration is often affected by weather or natural disasters, making manned aircraft operation inherently dangerous. When using UAVs for flight calibration, if GPS fails or positioning errors occur, the accuracy and continuity of the navigation system cannot be guaranteed, thus making it impossible to accurately complete the flight calibration work. Summary of the Invention

[0004] The purpose of this invention is to provide a UAV flight calibration system based on dead reckoning data. The system plans a flight path using a route planning module, and a central controller drives the UAV to fly along the predetermined path. The dead reckoning module determines the coordinates, trajectory parameters, and direction of motion of the UAV's current position, and calculates the coordinates of the second calibration point when the UAV reaches the first calibration point. A data calibration module checks whether the UAV's current position parameters meet preset calibration conditions. If not, a correction command module sends a command to the central controller to correct the UAV's current position coordinates to the coordinates of the second calibration point. This avoids the drawbacks of GPS failure or positioning errors in existing flight calibration work, and the addition of dead reckoning technology ensures the accuracy of the navigation system and flight calibration work, solving the problems mentioned in the background art.

[0005] To achieve the above objectives, the present invention employs the following technical solution:

[0006] A UAV flight verification system based on dead reckoning data includes: a route planning unit, a central controller, a dead reckoning unit, a flight verification unit, a cloud platform, and a remote 5G communication module;

[0007] The flight path planning unit is used to plan the optimal flight path for the UAV based on measurement data and predetermined flight path distance.

[0008] The central controller is installed in the drone to receive flight verification commands and control the drone's flight path based on the received commands.

[0009] The dead reckoning unit is used to detect the trajectory parameters and position information of the UAV's current position based on dead reckoning technology, and to estimate the trajectory parameters and position information of the UAV's next position using dead reckoning technology; the flight verification unit is used to obtain the trajectory parameters and position information of the UAV's current position from the dead reckoning unit, and to perform corresponding flight verification analysis based on the obtained trajectory parameters and position information.

[0010] The cloud platform is used to receive flight verification data from drones and store it in real time to the flight verification data evaluation database.

[0011] The remote 5G communication module is used for data transmission between the central controller and the cloud platform via the 5G network.

[0012] Furthermore, the aforementioned remote 5G communication module includes:

[0013] The first communication connection module is used to establish a communication connection between the central controller and the cloud platform via a 5G base station before the drone takes off.

[0014] The distribution location extraction module is used to extract the distribution location of the corresponding 5G base stations based on the 5G signal coverage along the flight path;

[0015] The first 5G signal strength threshold acquisition module is used to determine the corresponding flight path marker point based on the shortest straight-line distance between the location of the 5G base station and the flight path; and to set the first 5G signal strength threshold during the flight of the drone based on the theoretical 5G signal strength corresponding to the flight path marker point.

[0016] The target base station acquisition module is used to receive 5G signals around the flight path in real time during the flight of the drone. When there are multiple 5G signals covering the flight path, the strength of each 5G signal is determined, and the 5G base station whose 5G signal strength exceeds the first 5G signal strength threshold is used as the target base station for establishing the communication connection between the central controller installed in the drone and the cloud platform.

[0017] The second 5G signal strength threshold acquisition module is used to set a second 5G signal strength threshold when all 5G signal strengths are lower than the first 5G signal strength threshold, and to filter target base stations based on the second 5G signal strength threshold.

[0018] Furthermore, the first 5G signal strength threshold is obtained using the following formula:

[0019]

[0020] Wherein, B01 represents the first 5G signal strength threshold; n represents the number of all 5G base stations covering the flight route; B0i represents the rated signal strength corresponding to the i-th base station; ΔBi represents the signal strength attenuation caused by each unit distance away from the i-th base station; k represents the number of unit distances contained in the actual distance between the current flight route marker and the 5G base station; Bj represents the theoretical signal strength of the j-th 5G base station corresponding to a flight route marker; m represents the number of 5G base stations corresponding to a flight route marker; ΔBp represents the average attenuation per unit distance for all 5G base stations covering the flight route; kmax represents the maximum distance from all flight route markers to their corresponding 5G base stations; and kp represents the average distance from all flight route markers to their corresponding 5G base stations.

[0021] Furthermore, the second 5G signal strength threshold acquisition module includes...

[0022] The signal strength information acquisition module is used to extract the actual 5G signal strength received at the current flight location and obtain the theoretical 5G signal strength corresponding to the current flight location when all 5G signal strengths are lower than the first 5G signal strength threshold.

[0023] The second 5G signal strength threshold setting module is used to set a second 5G signal strength threshold based on the actual 5G signal strength received at the previous flight position and the theoretical 5G signal strength corresponding to the current flight position.

[0024] The base station connection establishment module is used to select, after obtaining the second 5G signal strength threshold, a 5G base station whose signal strength exceeds the second 5G signal strength threshold from the 5G signals received at the current flight position as the target base station for the communication connection between the central controller and the cloud platform.

[0025] Furthermore, the second 5G signal strength threshold is obtained using the following formula:

[0026]

[0027] Wherein, B02 represents the second 5G signal strength threshold; B01 represents the first 5G signal strength threshold; ΔBj represents the signal strength attenuation caused by each unit distance away from the j-th base station; k represents the number of unit distances contained in the actual distance between the current route marker and the 5G base station; Bj represents the theoretical signal strength of the j-th 5G base station corresponding to a route marker; m represents the number of 5G base stations corresponding to a route marker; and Bsj represents the actual signal strength of the j-th 5G base station corresponding to a route marker.

[0028] Furthermore, the central controller includes:

[0029] The command receiving module is used to receive control commands from the flight verification unit and the cloud platform, and to control the central controller to adjust the flight status of the UAV based on the received control commands.

[0030] Furthermore, the route planning unit includes:

[0031] The flight path planning module is used to obtain the reference coordinates of the land parcel boundary points from the GPS base station, and when the UAV is at the land parcel boundary point, it uses the actual coordinates of the boundary point measured by the UAV's GPS mobile station to calculate the difference between the actual coordinates of the boundary point and the reference coordinates of the boundary point, and plans the optimal flight path based on the calculation results; wherein, the optimal flight path is set with at least two calibration points.

[0032] Furthermore, the dead reckoning unit includes:

[0033] The data acquisition module is used to acquire parameters output by the UAV's onboard navigation equipment; the parameters include: magnetic heading information output by the attitude system, vacuum velocity and barometric altitude information output by the atmospheric data system, and slant range information output by the rangefinder.

[0034] The dead reckoning module is used to determine the coordinates, trajectory parameter values, and direction of motion of the UAV's current position based on dead reckoning technology. The trajectory parameter values ​​include any one or any combination of the following: rate of change of curvature, rate of change of radius of curvature, curvature, and radius of curvature.

[0035] The acquisition module is used to acquire the coordinates of the second calibration point when the UAV flies from the first calibration point to the second calibration point along the preset route.

[0036] The data transmission module is used to send the coordinate values ​​of the second calibration point and the parameters output by the UAV's onboard navigation equipment to the flight verification unit in sequence.

[0037] Furthermore, the flight calibration unit includes:

[0038] The data receiving module is used to receive the parameters output by the UAV's onboard navigation equipment and the coordinate values ​​of the second calibration point;

[0039] The data calibration module is used to use the data received by the data receiving module as a calibration benchmark to determine whether the trajectory parameter values ​​of the current position of the UAV meet the preset calibration conditions. If the preset calibration conditions are not met, no calibration command is issued, and the UAV is driven to continue flying along the predetermined route. If the preset calibration conditions are met, the coordinates of the current position of the UAV are corrected to the coordinate values ​​of the second calibration point.

[0040] The correction command module is used to send the coordinate values ​​of the second calibration point of the UAV to the central controller when the trajectory parameter values ​​of the current position of the UAV do not meet the preset calibration conditions, and then control the adjustment of the next flight path of the UAV through the central controller.

[0041] Furthermore, the cloud platform includes:

[0042] The flight calibration data analysis module is used to read flight calibration data from the flight calibration data evaluation database and analyze the data. The analysis includes: optimization of UAV flight paths, prediction of UAV system failures, and resolution of UAV flight conflicts.

[0043] The remote command module sends adjustment commands to the central controller based on instructions given by ground personnel, and controls the flight status of the UAV through the central controller.

[0044] Compared with existing technologies, the advantages of this invention are as follows: This invention provides a UAV flight calibration system based on dead reckoning data. The system uses a route planning module to calculate the difference between the reference coordinates of the boundary points measured by the GPS base station and the actual coordinates of the boundary points measured by the GPS mobile station, thereby planning the optimal flight route. The central controller drives the UAV into a predetermined orbit and flies along the predetermined flight route. The dead reckoning module determines the coordinates, trajectory parameters, and direction of motion of the UAV's current position. When the UAV reaches the first calibration point to the second calibration point during the flight of the predetermined route, the acquisition module calculates the coordinates of the second calibration point. The data calibration module calibrates whether the trajectory parameters of the UAV's current position meet preset calibration conditions. If not, no calibration command is issued, and the UAV continues to fly along the predetermined route. If the preset calibration conditions are met, a correction command module sends a correction command to the central controller, correcting the coordinates of the UAV's current position to the coordinates of the second calibration point. This avoids the drawbacks of GPS failure or positioning errors in existing flight calibration work, and the addition of dead reckoning technology ensures the accuracy and continuity of the navigation system, thereby optimizing the accuracy of flight calibration work.

[0045] Therefore, it is evident that the present invention has outstanding substantive features and significant progress compared with the prior art, and the beneficial effects of its implementation are also obvious. Attached Figure Description

[0046] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on the provided drawings without creative effort.

[0047] Figure 1 This is a system structure diagram of a specific embodiment of the present invention.

[0048] Figure 2 This is a flowchart illustrating a specific embodiment of the present invention. Detailed Implementation

[0049] 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.

[0050] To address the technical challenges of manned aircraft calibration methods being frequently hampered by weather or natural disasters, and the inability of unmanned aerial vehicles (UAVs) to guarantee navigation system accuracy and continuity due to GPS failure or positioning errors, thus hindering the precise completion of flight calibration tasks, please refer to [link to relevant documentation]. Figures 1-2 This embodiment provides the following technical solution:

[0051] A UAV flight verification system based on dead reckoning data includes: a route planning unit, a central controller, a dead reckoning unit, a flight verification unit, a cloud platform, and a remote 5G communication module.

[0052] The flight path planning unit is used to plan the optimal flight path of the UAV based on measurement data and a predetermined flight path distance. During the planning process, the relevant area needs to be measured. In a preferred embodiment, after the operator arrives at the area to be surveyed, the operation control point is marked first, and then the surveying GPS base station is set up on the operation control point. The relative coordinates of the operation control point are measured using GPS, and the relative coordinates are used as the measurement reference. The boundary coordinates of the plot are measured by the pattern. After the plot measurement is completed, the flight path of the UAV is planned based on the coordinates of the plot.

[0053] The central controller, an airborne control terminal installed in the drone, is used to receive flight verification commands and control the drone's flight path based on the received commands. The central controller is the drone's airborne control terminal and establishes a communication connection with the cloud platform through a remote 5G communication module. The ground operator sends control commands to the central controller through the cloud platform, and then the central controller sends control commands to the various operating devices of the drone, driving the drone to perform corresponding actions according to the control commands, thereby realizing the function of the cloud platform controlling the drone's flight status.

[0054] The central controller includes an instruction receiving module.

[0055] The command receiving module is used to receive control commands issued by the flight calibration unit and the cloud platform, and control the central controller to adjust the flight status of the UAV based on the received commands. The central controller can also be used to receive control commands transmitted by the flight calibration unit, and based on the various parameters collected by the flight calibration unit and the calibration results, control the UAV to adjust its flight status according to the commands given by the flight calibration unit, thereby realizing the flight calibration of the UAV.

[0056] The dead reckoning unit detects the trajectory parameters and position information of the UAV's current position based on dead reckoning technology, and estimates the trajectory parameters and position information of the UAV's next position using dead reckoning technology.

[0057] The flight verification unit is used to obtain the trajectory parameters and position information of the UAV's current position from the dead reckoning unit, and to perform corresponding flight verification analysis based on the obtained trajectory parameters and position information.

[0058] The cloud platform is used to receive flight calibration data from UAVs and store it in real time to the flight calibration data evaluation database. This enables a remote control platform for comprehensive flight data management, which can store, process, and visualize large-scale data. It solves the problems of low data processing efficiency and low utilization of effective information caused by the different sources and complex types of data in existing flight calibration platforms.

[0059] The remote 5G communication module is used to establish a communication connection between the central controller installed in the drone and the cloud platform.

[0060] Specifically, the remote 5G communication module includes: a first communication connection module, a distributed location extraction module, a first 5G signal strength threshold acquisition module, a target base station acquisition module, and a second 5G signal strength threshold acquisition module.

[0061] The first communication connection module is used to establish a communication connection between the central controller installed in the drone and the cloud platform through the nearest 5G base station before the drone takes off.

[0062] The distribution location extraction module is used to extract the distribution locations of all 5G base stations that provide signal coverage along the flight path.

[0063] The first 5G signal strength threshold acquisition module is used to set a first 5G signal strength threshold during the drone's flight based on the shortest straight-line distance between the location of the 5G base station and the flight path, and the theoretical signal strength of the flight path marker corresponding to the shortest straight-line distance between the location of the 5G base station and the flight path within the signal coverage area of ​​the 5G base station; wherein, the first 5G signal strength threshold is obtained by the following formula:

[0064]

[0065] Wherein, B01 represents the first 5G signal strength threshold; n represents the number of all 5G base stations covering the flight route; B0i represents the rated signal strength corresponding to the i-th base station; ΔBi represents the signal strength attenuation caused by each unit distance away from the i-th base station; k represents the number of unit distances contained in the actual distance between the current flight route marker and the 5G base station; Bj represents the theoretical signal strength of the j-th 5G base station corresponding to a flight route marker; m represents the number of 5G base stations corresponding to a flight route marker; ΔBp represents the average attenuation per unit distance for all 5G base stations covering the flight route; kmax represents the maximum distance from all flight route markers to their corresponding 5G base stations; and kp represents the average distance from all flight route markers to their corresponding 5G base stations.

[0066] The target base station acquisition module is used to receive 5G signals around the flight path in real time during the flight of the UAV. When there are multiple 5G signals covering the flight path, the module determines the strength of the multiple 5G signals and uses the 5G base station whose 5G signal strength exceeds the first 5G signal strength threshold as the target base station for establishing the communication connection between the central controller installed in the UAV and the cloud platform.

[0067] The second 5G signal strength threshold acquisition module is used to filter target base stations by acquiring the second 5G signal strength threshold when all 5G signal strengths are at the first 5G signal strength threshold.

[0068] The technical effects of the above solution are as follows: the first communication connection module can quickly establish a communication connection between the central controller and the cloud platform before the drone takes off, so as to achieve efficient data transmission and communication; ensure the stability and reliability of the communication connection to ensure real-time communication between the drone and the cloud platform and avoid communication interruption or data loss. At the same time, the nearest 5G base station to the drone is selected to ensure that the coverage of the communication connection is optimal and to reduce the possibility of signal delay and communication failure.

[0069] The distribution location extraction module can accurately extract the distribution location information of all 5G base stations that provide signal coverage along the flight path, ensuring the accuracy of subsequent analysis and calculation. Furthermore, it extracts the distribution location of base stations in real time to ensure real-time analysis and decision-making regarding signal coverage during flight path planning and drone flight.

[0070] The first 5G signal strength threshold acquisition module can accurately calculate the first 5G signal strength threshold based on the shortest straight-line distance between the 5G base station location and the flight path, as well as the theoretical signal strength corresponding to the marker point within the base station's signal coverage area, ensuring the accuracy of signal strength judgment. Simultaneously, it can flexibly set the first 5G signal strength threshold according to different flight paths and base station configurations to adapt to different environments and needs.

[0071] The target base station acquisition module can receive 5G signals around the flight path in real time and determine their strength to quickly identify the target base station, ensuring the real-time performance and stability of the communication connection. Simultaneously, it can accurately identify base stations among multiple 5G signals covering the flight path whose strength exceeds a first 5G signal strength threshold and select them as target base stations to ensure the quality and efficiency of the communication connection.

[0072] The second 5G signal strength threshold acquisition module filters target base stations by acquiring a second 5G signal strength threshold when all 5G signal strengths are below the first 5G signal strength threshold. The accuracy of the second threshold calculation, its adaptability to signal strength distribution, and the efficiency of the filtering process are all considered.

[0073] Simultaneously, by using the above factors for calculation, a first 5G signal strength threshold B01 applicable to the drone's flight process can be obtained. This threshold can be used to determine whether the signal strength meets the requirements, thereby filtering out suitable target base stations for establishing communication connections.

[0074] As an example, the second 5G signal strength threshold acquisition module includes a signal strength information acquisition module, a second 5G signal strength threshold setting module, and a base station connection establishment module.

[0075] The signal strength information acquisition module is used to extract the actual 5G signal strength received at the current flight location and obtain the theoretical 5G signal strength corresponding to the current flight location when all 5G signal strengths are lower than the first 5G signal strength threshold.

[0076] The second 5G signal strength threshold setting module is used to set a second 5G signal strength threshold based on the actual 5G signal strength received at the previous flight position and the theoretical 5G signal strength corresponding to the current flight position. The second 5G signal strength threshold is obtained using the following formula:

[0077]

[0078] Wherein, B02 represents the second 5G signal strength threshold; B01 represents the first 5G signal strength threshold; ΔBj represents the signal strength attenuation caused by each unit distance away from the j-th base station; k represents the number of unit distances contained in the actual distance between the current route marker and the 5G base station; Bj represents the theoretical signal strength of the j-th 5G base station corresponding to a route marker; m represents the number of 5G base stations corresponding to a route marker; and Bsj represents the actual signal strength of the j-th 5G base station corresponding to a route marker.

[0079] The base station connection establishment module is used to, after obtaining the second 5G signal strength threshold, use 5G base stations whose 5G signal strength received at the current flight position exceeds the second 5G signal strength threshold as target base stations for establishing a communication connection between the central controller installed in the UAV and the cloud platform.

[0080] The technical effects of the above solution include: the signal strength information acquisition module extracts the actual 5G signal strength received at the current flight location and obtains the theoretical 5G signal strength corresponding to the current flight location. This improves the accuracy and real-time performance of signal strength extraction, as well as the breadth and precision of signal acquisition at the current location.

[0081] The second 5G signal strength threshold setting module sets a second 5G signal strength threshold based on the actual 5G signal strength received at the current flight location and the corresponding theoretical 5G signal strength. This effectively improves the accuracy of the threshold setting, the adaptability of the threshold to the actual signal strength, and the ability to dynamically adjust to different locations.

[0082] The target base station acquisition module, based on the obtained second 5G signal strength threshold, identifies base stations whose 5G signal strength at the current flight location exceeds the threshold as target base stations. These base stations are used to establish a communication connection between the central controller mounted on the UAV and the cloud platform. This effectively improves the accuracy of base station identification, the real-time performance of target base station selection, and the accuracy of the selection logic for multiple base stations.

[0083] On the other hand, by calculating the actual distance, theoretical signal strength, and signal attenuation between the current flight path marker and each 5G base station using the above method, a second 5G signal strength threshold is determined. This improves the accuracy of the second 5G signal strength threshold calculation and provides an adaptive adjustment mechanism to accommodate changes between different flight path markers and base stations, thereby enhancing the stability and reliability of the communication connection.

[0084] As an example, the route planning unit includes:

[0085] The flight path planning module uses the reference coordinates of the land parcel boundary points measured by the GPS base station and the actual coordinates of the boundary points measured by the UAV's GPS rover when the UAV is at the land parcel boundary point. It calculates the difference between the actual coordinates and the reference coordinates of the boundary points to plan the optimal flight path. The UAV has at least two calibration points set during its flight along the preset path. Specifically, the UAV is positioned directly above the boundary point of the land parcel to be measured. After measuring the coordinates of the operation control point using GPS, the UAV is positioned based on these coordinates to obtain the actual coordinates of the boundary point. The reference coordinates and the actual coordinates of the boundary point are then differentially calculated; the difference result represents the GPS positioning error of the UAV. Finally, the coordinates used in the flight path planning are differentially analyzed with the above difference result to regenerate the flight path data, thus achieving the replanning of the flight path. It should be noted that since the latitude and longitude of the actual geographical locations represented by the two coordinates are the same when measuring the reference coordinates and the actual coordinates of the boundary point, this difference result, used as the calibration value for the flight path coordinate data, is accurate and objective, thus providing the optimal flight path for the UAV.

[0086] As an example, the dead reckoning unit includes: a data acquisition module, a dead reckoning module, an acquisition module, and a data transmission module.

[0087] The data acquisition module is used to collect parameters output by various navigation devices on the UAV; these parameters include: magnetic heading information output by the attitude and bearing system, vacuum speed and barometric altitude information output by the atmospheric data system, and slant range information output by the rangefinder.

[0088] The dead reckoning module is used to determine the coordinates, trajectory parameters, and direction of motion of the UAV's current position using dead reckoning technology. The trajectory parameters include any one of the following: rate of change of curvature, rate of change of radius of curvature, curvature, and radius of curvature. The module acquires the UAV's magnetic heading information through a data acquisition module. Based on the coordinates, trajectory parameters, and direction of motion calculated by the dead reckoning module, the magnetic deviation is obtained by querying a database. The magnetic heading information and the magnetic deviation information are added together to obtain the true heading. Then, based on the UAV's position and wind speed at the previous moment, the true heading at the current moment, vacuum velocity, and barometric altitude, the dead reckoning method is used to obtain the estimated position information for the current moment.

[0089] The acquisition module is used to acquire the coordinates of the second calibration point when the UAV is flying from the first calibration point to the second calibration point along a preset flight path. The flight path represents the direction and trajectory of the UAV's movement. Following the above embodiment, for example, when the UAV moves between the first and second calibration points, if the UAV's direction of movement is from the first calibration point to the second calibration point, then the first calibration point is the previous calibration point and the second calibration point is the next calibration point; if the UAV's direction of movement is from the second calibration point to the first calibration point, then the second calibration point is the previous calibration point and the first calibration point is the next calibration point. The UAV can measure its own direction of movement using its onboard gyroscope sensor. The coordinates of the first calibration point, the coordinates of the current position, and the coordinates of the second calibration point can be based on latitude and longitude coordinates, two-dimensional coordinates, or coordinates set in an electronic map; this invention does not impose any limitations.

[0090] The data transmission module is used to sequentially send the coordinate values ​​of the second calibration point predicted by the acquisition module and the parameters output by the various navigation devices on the UAV to the flight verification unit. The data transmission module uses a remote 5G communication module as the transmission carrier, thereby establishing a communication connection with the flight verification unit. Following the above embodiment, for example, the data acquisition module acquires the magnetic heading information output by the UAV's onboard attitude system, the vacuum velocity and barometric altitude information output by the atmospheric data system, and the slant range information output by the rangefinder. The acquisition module predicts the value of the second calibration point based on the first calibration point, and then sends the acquired data and the value of the second calibration point to the flight verification unit for verification via the remote 5G communication module.

[0091] As an example, the flight verification unit includes: a data receiving module, a data calibration module, and a correction instruction module.

[0092] The data receiving module is used to receive parameters output by various navigation devices on the UAV and the coordinate values ​​of the predicted second calibration point.

[0093] The data calibration module uses the parameters currently collected by the UAV and the coordinates of the second calibration point as calibration benchmarks to calibrate whether the trajectory parameters of the UAV's current position meet preset calibration conditions. If the preset calibration conditions are not met, no calibration command is issued, and the UAV continues to fly along the predetermined route. If the preset calibration conditions are met, the coordinates of the UAV's current position are corrected to the coordinates of the second calibration point. The coordinates of the current position obtained through dead reckoning technology increase over time. When the trajectory parameters of the UAV's current position meet the preset calibration conditions, the calibration conditions are used to determine whether the UAV has reached the second calibration point. If the calibration conditions are met, the coordinates of the UAV's current position are corrected to the coordinates of the second calibration point. Therefore, when the UAV flies on the predetermined route, at least two calibration points are set on the predetermined route. The UAV can perform calibration once every time it passes through a sub-path according to the above calibration method, which can effectively reduce the positioning deviation of the UAV and thus improve the accuracy of the UAV navigation system and the accuracy of the flight verification results.

[0094] The correction command module, based on the calibration results obtained by the data calibration module, if the trajectory parameter values ​​of the current position of the UAV do not meet the preset calibration conditions, sends the coordinate values ​​of the second calibration point of the UAV to the central controller through the correction command module, and controls the adjustment of the next flight path of the UAV through the central controller.

[0095] As an example, the cloud platform includes: a flight calibration data analysis module and a remote command module.

[0096] The flight calibration data analysis module is used to read and analyze flight calibration data from the flight calibration data evaluation database. The analysis includes optimizing UAV flight paths, predicting UAV system malfunctions, and resolving UAV flight conflicts. By analyzing flight calibration data through this module, functions such as UAV trajectory optimization, UAV system malfunction prediction, and UAV flight conflict resolution can be achieved. UAV trajectory optimization aims to enable the calibration UAV to complete as many calibration tasks as possible, reduce safety exposure time, and improve the efficiency of UAV flight calibration.

[0097] The remote command module sends adjustment commands to the central controller based on instructions given by ground personnel, and controls the flight status of the UAV through the central controller.

[0098] In addition, this invention also discloses an implementation method for an unmanned aerial vehicle (UAV) navigation verification system based on dead reckoning data, which specifically includes the following steps:

[0099] S1: The route planning module uses the reference coordinates of the land boundary points measured by the GPS base station and the actual coordinates of the boundary points measured by the GPS mobile station, and calculates the difference between the two coordinates to plan the optimal flight route.

[0100] S2: The central controller drives the drone into a predetermined orbit and flies along a predetermined flight path.

[0101] S3: Use the dead reckoning module to determine the coordinates, trajectory parameter values ​​and direction of motion of the UAV at its current position, and when the UAV reaches the first calibration point to the second calibration point in the preset flight path, use the acquisition module to calculate the coordinates of the second calibration point.

[0102] S4: The data calibration module calibrates whether the trajectory parameter values ​​of the current position of the UAV meet the preset calibration conditions; if the preset calibration conditions are met, no calibration command is issued, and the UAV continues to fly along the predetermined route; if not, the correction command module sends a correction command to the central controller to correct the coordinates of the current position of the UAV to the coordinate values ​​of the second calibration point.

[0103] This avoids the drawbacks of GPS failure or positioning errors in existing flight calibration work, and adds dead reckoning technology to ensure the accuracy and continuity of the navigation system, thereby optimizing the precision of flight calibration work.

[0104] It should be noted that, in this document, relational terms such as "first" and "second" are used only to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such process, method, article, or apparatus.

[0105] Although embodiments of the invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the appended claims and their equivalents.

Claims

1. A UAV flight verification system based on dead reckoning data, characterized in that, include: The system includes a route planning unit, a central controller, a dead reckoning unit, a flight verification unit, a cloud platform, and a remote 5G communication module. The flight path planning unit is used to plan the optimal flight path for the UAV based on measurement data and predetermined flight path distance. The central controller is installed in the drone to receive flight verification commands and control the drone's flight path based on the received commands. The dead reckoning unit is used to detect the trajectory parameters and position information of the UAV's current position based on dead reckoning technology, and to estimate the trajectory parameters and position information of the UAV's next position using dead reckoning technology. The flight verification unit is used to obtain the trajectory parameters and position information of the UAV's current position from the dead reckoning unit, and to perform corresponding flight verification analysis based on the obtained trajectory parameters and position information. The cloud platform is used to receive flight verification data from drones and store it in real time to the flight verification data evaluation database. The remote 5G communication module is used for data transmission between the central controller and the cloud platform via the 5G network. The remote 5G communication module includes: The first communication connection module is used to establish a communication connection between the central controller and the cloud platform via a 5G base station before the drone takes off. The distribution location extraction module is used to extract the distribution location of the corresponding 5G base stations based on the 5G signal coverage along the flight path; The first 5G signal strength threshold acquisition module is used to determine the corresponding flight path marker point based on the shortest straight-line distance between the location of the 5G base station and the flight path; and to set the first 5G signal strength threshold during the flight of the drone based on the theoretical 5G signal strength corresponding to the flight path marker point. The target base station acquisition module is used to receive 5G signals around the flight path in real time during the flight of the drone. When there are multiple 5G signals covering the flight path, the strength of each 5G signal is determined, and the 5G base station whose 5G signal strength exceeds the first 5G signal strength threshold is used as the target base station for establishing the communication connection between the central controller installed in the drone and the cloud platform. The second 5G signal strength threshold acquisition module is used to set a second 5G signal strength threshold when all 5G signal strengths are lower than the first 5G signal strength threshold, and to filter target base stations based on the second 5G signal strength threshold. The first 5G signal strength threshold is obtained by the following formula: Wherein, B01 represents the first 5G signal strength threshold; n represents the number of all 5G base stations covering the flight path; B0i represents the rated signal strength corresponding to the i-th base station; ΔBi represents the signal strength attenuation caused by each unit distance away from the i-th base station; k represents the number of unit distances contained in the actual distance between the current flight path marker and the 5G base station; Bj represents the theoretical signal strength of the j-th 5G base station corresponding to a flight path marker; m represents the number of 5G base stations corresponding to a flight path marker; ΔBp represents the average attenuation per unit distance for all 5G base stations covering the flight path; kmax represents the maximum distance from all flight path markers to their corresponding 5G base stations; and kp represents the average distance from all flight path markers to their corresponding 5G base stations. The second 5G signal strength threshold acquisition module includes The signal strength information acquisition module is used to extract the actual 5G signal strength received at the current flight location and obtain the theoretical 5G signal strength corresponding to the current flight location when all 5G signal strengths are lower than the first 5G signal strength threshold. The second 5G signal strength threshold setting module is used to set a second 5G signal strength threshold based on the actual 5G signal strength received at the previous flight position and the theoretical 5G signal strength corresponding to the current flight position. The base station connection establishment module is used to select, after obtaining the second 5G signal strength threshold, a 5G base station whose signal strength exceeds the second 5G signal strength threshold from the 5G signals received at the current flight position as the target base station for the communication connection between the central controller and the cloud platform. The second 5G signal strength threshold is obtained using the following formula: Wherein, B02 represents the second 5G signal strength threshold; B01 represents the first 5G signal strength threshold; ΔBj represents the signal strength attenuation caused by each unit distance away from the j-th base station; k represents the number of unit distances contained in the actual distance between the current flight path marker and the 5G base station; Bj represents the theoretical signal strength of the j-th 5G base station corresponding to a flight path marker; m represents the number of 5G base stations corresponding to a flight path marker; and Bsj represents the actual signal strength of the j-th 5G base station corresponding to a flight path marker. The dead reckoning unit includes: The data acquisition module is used to acquire parameters output by the UAV's onboard navigation equipment; the parameters include: magnetic heading information output by the attitude system, vacuum velocity and barometric altitude information output by the atmospheric data system, and slant range information output by the rangefinder. The dead reckoning module is used to determine the coordinates, trajectory parameter values, and direction of motion of the UAV's current position based on dead reckoning technology. The trajectory parameter values ​​include any one or any combination of the following: rate of change of curvature, rate of change of radius of curvature, curvature, and radius of curvature. The acquisition module is used to acquire the coordinates of the second calibration point when the UAV flies from the first calibration point to the second calibration point along the preset route. The data transmission module is used to send the coordinate values ​​of the second calibration point and the parameters output by the UAV's onboard navigation equipment to the flight verification unit in sequence. The flight verification unit includes: The data receiving module is used to receive the parameters output by the UAV's onboard navigation equipment and the coordinate values ​​of the second calibration point; The data calibration module is used to use the data received by the data receiving module as a calibration benchmark to determine whether the trajectory parameter values ​​of the current position of the UAV meet the preset calibration conditions. If the preset calibration conditions are not met, no calibration command is issued, and the UAV is driven to continue flying along the predetermined route. If the preset calibration conditions are met, the coordinates of the current position of the UAV are corrected to the coordinate values ​​of the second calibration point. The correction command module is used to send the coordinate values ​​of the second calibration point of the UAV to the central controller when the trajectory parameter values ​​of the current position of the UAV do not meet the preset calibration conditions, and then control the adjustment of the next flight path of the UAV through the central controller.

2. The UAV flight verification system based on dead reckoning data as described in claim 1, characterized in that: The central controller includes: The command receiving module is used to receive control commands from the flight verification unit and the cloud platform, and to control the central controller to adjust the flight status of the UAV based on the received control commands.

3. The UAV flight verification system based on dead reckoning data as described in claim 1, characterized in that: The route planning unit includes: The flight path planning module is used to obtain the reference coordinates of the land parcel boundary points from the GPS base station, and when the UAV is at the land parcel boundary point, it uses the actual coordinates of the boundary point measured by the UAV's GPS mobile station to calculate the difference between the actual coordinates of the boundary point and the reference coordinates of the boundary point, and plans the optimal flight path based on the calculation results; wherein, the optimal flight path is set with at least two calibration points.

4. The UAV flight verification system based on dead reckoning data as described in claim 1, characterized in that: The cloud platform includes: The flight calibration data analysis module is used to read flight calibration data from the flight calibration data evaluation database and analyze the data. The analysis includes: optimization of UAV flight paths, prediction of UAV system failures, and resolution of UAV flight conflicts. The remote command module sends adjustment commands to the central controller based on instructions given by ground personnel, and controls the flight status of the UAV through the central controller.

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