CN-121432498-B - Unmanned aerial vehicle track tracking method, server, medium and product

CN121432498BCN 121432498 BCN121432498 BCN 121432498BCN-121432498-B

Abstract

The application provides an unmanned aerial vehicle track tracking method, a server, a medium and a product, and relates to the technical field of unmanned aerial vehicle tracking. The method comprises the steps of receiving GPS positioning signals of all operation unmanned aerial vehicles in real time, determining a reference unmanned aerial vehicle of any target operation unmanned aerial vehicle when the GPS positioning signals of the target operation unmanned aerial vehicle are monitored to be lost, acquiring real-time positioning information of the reference unmanned aerial vehicle, calculating historical relative position relation between the reference unmanned aerial vehicle and the target operation unmanned aerial vehicle, calculating real-time virtual positioning of the target operation unmanned aerial vehicle based on the historical relative position relation and the real-time positioning information of the reference unmanned aerial vehicle, generating a temporary tracking track according to the real-time virtual positioning, and transmitting the temporary tracking track to the target operation unmanned aerial vehicle. The method can ensure the continuity of the unmanned aerial vehicle track and the integrity of the operation, effectively avoid yaw, collision or operation interruption caused by position loss, and remarkably improve the safety and reliability of unmanned aerial vehicle cluster operation in complex scenes.

Inventors

GAO YANG
ZHOU HUA

Assignees

华颐昌能(北京)科技有限公司

Dates

Publication Date: 20260508
Application Date: 20251114

Claims (9)

1. An unmanned aerial vehicle track tracking method applied to a server is characterized by comprising the following steps: Receiving GPS positioning signals of all unmanned aerial vehicles in real time; when the GPS positioning signal of any target operation unmanned aerial vehicle is monitored to be lost, determining a reference unmanned aerial vehicle of the target operation unmanned aerial vehicle, and acquiring real-time positioning information of the reference unmanned aerial vehicle; Calculating a historical relative position relation between the reference unmanned aerial vehicle and the target operation unmanned aerial vehicle, wherein the historical relative position relation comprises a horizontal relative distance, a height difference and a relative azimuth angle; Calculating real-time virtual positioning of the target operation unmanned aerial vehicle based on the historical relative position relationship and the real-time positioning information of the reference unmanned aerial vehicle, and generating a temporary tracking track according to the real-time virtual positioning; Issuing the temporary tracking track to the target operation unmanned aerial vehicle; When the GPS positioning signal of any target operation unmanned aerial vehicle is monitored to be lost, determining the reference unmanned aerial vehicle of the target operation unmanned aerial vehicle comprises the following steps: when the GPS positioning signal of any target operation unmanned aerial vehicle is monitored to be lost, acquiring an operation total path, a time stamp of the signal loss and the last effective lost point GPS positioning when the signal is lost; Searching the outer ring layer according to a preset distance gradient based on the lost point GPS positioning to screen out candidate operation unmanned aerial vehicles with effective GPS positioning signals reaching a set candidate number; calculating the space matching degree of each candidate operation unmanned aerial vehicle and the target operation unmanned aerial vehicle based on the operation total path and the time stamp; And screening out the candidate operation unmanned aerial vehicles with the space matching degree larger than the set space proportion, calculating the linear distance between each candidate operation unmanned aerial vehicle and the target operation unmanned aerial vehicle at the moment of GPS signal loss, selecting the operation unmanned aerial vehicle with the shortest linear distance, and determining the operation unmanned aerial vehicle as the reference unmanned aerial vehicle.
2. The method of claim 1, wherein the step of calculating a spatial match of each candidate work drone with the target work drone based on the job total path and the time stamp, comprises: extracting a path position point of the target operation unmanned aerial vehicle at the time stamp from the operation total path; Taking the path position point as a starting point, intercepting an expected path section which is required to be executed by the target operation unmanned aerial vehicle in a set continuing time; based on the time stamp, acquiring a planned path section of each candidate operation unmanned aerial vehicle in the set connection time; Dispersing the expected path section and each planned path section into coordinate points of a plurality of time points according to preset time intervals; Calculating the space distance between the planned path segment and each expected path segment at each corresponding time point, and counting the number of time points, wherein the space distance is smaller than a preset space threshold value; and determining the ratio of the number of the time points to the total number of the time points in the set continuous time as the space matching degree.
3. The method of claim 1, wherein the step of calculating a real-time virtual location of the target work drone based on the historical relative positional relationship and the real-time location information of the reference drone, comprises: Acquiring a continuous operation path of the target operation unmanned aerial vehicle, and extracting preset coordinate positions corresponding to time points of the continuous operation path on a time axis, wherein the preset coordinate positions comprise plane positions and heights, and the continuous operation path refers to a planned residual operation path section which is not executed before a GPS positioning signal of the target operation unmanned aerial vehicle is lost; acquiring the real-time positioning information of the reference unmanned aerial vehicle at each corresponding time point; And calculating the real-time virtual positioning of the target operation unmanned aerial vehicle according to the historical relative position relation, wherein the real-time virtual positioning comprises virtual plane coordinates and virtual heights of the target operation unmanned aerial vehicle at all time points.
4. The method of claim 1, wherein after the step of issuing the temporary tracking trajectory to the target work drone, further comprising: Selecting a nearest and non-shielding operation unmanned aerial vehicle from preset radar calibration unmanned aerial vehicles at intervals of preset calibration time periods so as to perform directional millimeter wave radar scanning on the target operation unmanned aerial vehicle; acquiring scanning data returned by the radar verification unmanned aerial vehicle, and extracting real-time space information of the corresponding target operation unmanned aerial vehicle, wherein the real-time space information comprises azimuth angles, linear distances and height differences of the target operation unmanned aerial vehicle relative to the radar verification unmanned aerial vehicle; The method comprises the steps that preset theoretical space information of the radar verification unmanned aerial vehicle and the target operation unmanned aerial vehicle is called from theoretical data pre-stored before operation at the current verification time; comparing the real-time space information with the preset theoretical space information to determine a verification result; and if the verification result is larger than a set error threshold, updating the temporary tracking track according to the preset theoretical space information.
5. The method of claim 1, wherein after the step of issuing the temporary tracking trajectory to the target work drone, further comprising: When the GPS positioning signal of the target operation unmanned aerial vehicle is recovered, acquiring real-time GPS positioning information and a current time stamp of the target operation unmanned aerial vehicle; Obtaining a corresponding target path node in the total path of the operation according to the current time stamp, and determining a path segment which is not executed after the target path node as a resume-after-resume path; and transmitting the recovered continuing path to the target operation unmanned aerial vehicle.
6. The method as recited in claim 1, further comprising: If the GPS positioning signal of the reference unmanned aerial vehicle is also lost, rescreening the operation unmanned aerial vehicle from candidate operation unmanned aerial vehicles with the space matching degree larger than the set space proportion to form a standby reference candidate pool; calculating the sum of the linear distances of each operation unmanned aerial vehicle, the target operation unmanned aerial vehicle and the reference unmanned aerial vehicle in the standby reference candidate pool at the current moment, and selecting the operation unmanned aerial vehicle with the shortest linear distance sum as a new reference unmanned aerial vehicle; and generating temporary tracking tracks of the target operation unmanned aerial vehicle and the reference unmanned aerial vehicle respectively based on the new reference unmanned aerial vehicle.
7. A server comprising one or more processors and memory coupled to the one or more processors, the memory to store computer program code comprising computer instructions that the one or more processors invoke to cause the server to perform the method of any of claims 1-6.
8. A computer readable storage medium comprising instructions which, when run on a server, cause the server to perform the method of any of claims 1-6.
9. A computer program product, characterized in that the computer program product, when run on a server, causes the server to perform the method according to any of claims 1-6.

Description

Unmanned aerial vehicle track tracking method, server, medium and product Technical Field The application relates to the technical field of unmanned aerial vehicle tracking, in particular to an unmanned aerial vehicle track tracking method, a server, a medium and a product. Background Along with the rapid development of unmanned aerial vehicle technology, the application scene of the unmanned aerial vehicle is expanded from single aerial photography operation to complex scenes such as high-density cluster operation (such as unmanned aerial vehicle firework show and formation performance), agricultural large-scale plant protection, power line inspection and the like. In these scenes, precise trajectory control of the unmanned aerial vehicle is a core for guaranteeing operation safety, efficiency and effect, and the basis of trajectory control depends on stable and high-precision positioning information. At present, the main stream positioning mode of the unmanned aerial vehicle is mainly GPS positioning, the flight control system of the unmanned aerial vehicle can receive GPS positioning data in real time, compares the GPS positioning data with a preset operation total path (such as a route of agricultural plant protection and time sequence coordinates of formation performance), calculates the deviation between the current position and a target path, and corrects the flight attitude by adjusting the motor rotation speed, the steering engine angle and the like to ensure the flight along a preset track. However, in a practical complex operating scenario, GPS positioning signals are susceptible to loss or drift due to interference from a variety of factors, such as signal shielding in densely populated areas of cities, electromagnetic interference around high-voltage lines, interaction of multiple signals in clustered operation, attenuation of satellite signals by smoke in firework shows, and the like. When GPS positioning signals of the target operation unmanned aerial vehicle are lost, if accurate positions of the target operation unmanned aerial vehicle cannot be obtained in time, the unmanned aerial vehicle is extremely easy to deviate from a preset track, and serious problems such as cluster collision, omission of an operation area, even crash of equipment and the like are caused. Disclosure of Invention The application provides an unmanned aerial vehicle track tracking method, a server, a medium and a product, which are used for supplementing flight track data of an unmanned aerial vehicle during the loss of a positioning signal so as to ensure the continuity of tasks and the flight safety of the unmanned aerial vehicle. The application provides an unmanned aerial vehicle track tracking method, which is applied to a server and comprises the steps of receiving GPS positioning signals of all unmanned aerial vehicles in real time, determining a reference unmanned aerial vehicle of any target unmanned aerial vehicle when the GPS positioning signals of the target unmanned aerial vehicle are monitored to be lost, acquiring real-time positioning information of the reference unmanned aerial vehicle, calculating historical relative position relations between the reference unmanned aerial vehicle and the target unmanned aerial vehicle, wherein the historical relative position relations comprise horizontal relative distances, height differences and relative azimuth angles, calculating real-time virtual positioning of the target unmanned aerial vehicle based on the historical relative position relations and the real-time positioning information of the reference unmanned aerial vehicle, generating a temporary tracking track according to the real-time virtual positioning, and transmitting the temporary tracking track to the target unmanned aerial vehicle. By adopting the technical scheme, a movable and reliable reference coordinate system is established for the target unmanned aerial vehicle losing the signal by determining a 'reference unmanned aerial vehicle' with a normal GPS signal. Secondly, the core is to calculate and utilize a "historical relative positional relationship" which relationship (including horizontal distance, altitude difference and azimuth angle) is essentially a digitized representation of the unmanned aerial vehicle formation. The relatively stable formation morphological relationship is superimposed on the real-time accurate position of the reference unmanned aerial vehicle, so that the current virtual position of the target unmanned aerial vehicle can be inverted with high fidelity. Based on the temporary track generated by the virtual positioning, the target unmanned aerial vehicle can continue to follow formation and maintain formation even under the condition of no self GPS, so that the continuity of the track and the integrity of operation are greatly ensured, yaw, collision or operation interruption caused by position loss is effectively avoided, and the safety and reliability of unmanned