CN-122024532-A - Unmanned aerial vehicle track compliance monitoring and early warning method

CN122024532ACN 122024532 ACN122024532 ACN 122024532ACN-122024532-A

Abstract

The invention belongs to the technical field of unmanned aerial vehicle airspace safety management, and particularly relates to an unmanned aerial vehicle track compliance monitoring and early warning method, which comprises the steps of respectively constructing three independently operated error models of navigation error, control error and delay error, comprehensively determining three-dimensional envelopes of unmanned aerial vehicle track compliance through the three error models, and timely early warning by comparing required track compliance thresholds, wherein the three-dimensional envelopes of unmanned aerial vehicle track compliance are formed by comprehensively taking predicted nominal positions as centers through the three error models, and defining irregular sphere boundary envelope probability spaces formed by possible position distribution of an unmanned aerial vehicle through front, rear, left, right, upper and lower boundary distances. The invention provides a monitoring means capable of dynamically and accurately reflecting the real flight area of the unmanned aerial vehicle for the airspace safety management of the unmanned aerial vehicle, thereby realizing early identification and early warning of potential yaw risk and finally improving the overall safety and the operation efficiency of a low-altitude airspace.

Inventors

MENG LINGHANG
ZHANG LINHAI
HUANG XIYANG

Assignees

中国民航大学

Dates

Publication Date: 20260512
Application Date: 20260407

Claims (10)

1. The unmanned aerial vehicle track compliance monitoring and early warning method is characterized by comprising the following steps of: receiving original data from an unmanned aerial vehicle navigation system through a navigation data interface unit, wherein the original data comprises GPS/GNSS global positioning signals, triaxial acceleration and angular velocity output by an inertial measurement unit and barometer height data; respectively constructing three independently operated error models of a navigation error, a control error and a delay error according to the original data; comprehensively determining the three-dimensional envelope of the unmanned aerial vehicle track compliance through the three error models, and comparing the required track compliance thresholds for early warning in time; the three-dimensional envelope of the unmanned aerial vehicle track compliance takes a predicted nominal position as a center, is formed by integrating three error models, and defines an irregular sphere boundary envelope probability space formed by possible position distribution of the unmanned aerial vehicle by six boundary distances of front, back, left, right, upper and lower.
2. The unmanned aerial vehicle track compliance monitoring and early warning method according to claim 1, wherein the navigation error model consists of a three-dimensional Gaussian sphere with 95% confidence level, and three-dimensional directions respectively accord with 0 as a mean value and 0 as a standard deviation 、 Is a gaussian distribution of (c).
3. The unmanned aerial vehicle track compliance monitoring and early warning method according to claim 1, wherein the control error model consists of a steady-state control error and a dynamic control error; The steady-state control error consists of a three-dimensional Gaussian sphere, wherein the three-dimensional directions respectively accord with the average value of 0 and the standard deviation of 0 、 The dynamic control error is the process of converging to a steady-state control error ellipsoid in the adjusting time after the steady-state unmanned aerial vehicle deviates to the maximum overshoot position under the influence of wind.
4. The unmanned aerial vehicle track compliance monitoring and early warning method according to claim 1, wherein the unmanned aerial vehicle track compliance three-dimensional envelope is divided into an overall error envelope of 8 typical states of uniform linear flat flight, accelerated linear flat flight, decelerated linear flat flight, linear climbing, linear descent, flat flight turning, turning climbing and turning descent according to the state of the unmanned aerial vehicle.
5. The unmanned aerial vehicle track compliance monitoring and early warning method according to claim 4, wherein when the uniform straight line flies horizontally, the total error envelope has six boundary distances of front, back, left, right, upper and lower respectively: Forward distance: ; Rear distance: ; Left distance: ; Right distance: ; Upper distance: ; The following distance is as follows: ; In the formula, 、 Respectively represents the standard deviation of the navigation error and the annotation difference of the control error in the horizontal direction, 、 The standard deviation of the navigation error and the standard deviation of the control error in the vertical direction are shown, respectively.
6. The unmanned aerial vehicle track compliance monitoring and early warning method according to claim 4, wherein when the acceleration straight line flies flat, the front, rear, left, right, upper and lower boundary distances of the total error envelope are respectively: Forward distance: ; Rear distance: ; In the formula, 、 Respectively represents the standard deviation of the navigation error and the annotation difference of the control error in the horizontal direction, 、 The navigation error standard deviation and the control error standard deviation in the vertical direction are respectively indicated, The standard deviation of the system delay is indicated, The standard deviation of the acceleration of the unmanned aerial vehicle is represented, Representing the bisecting speed of the unmanned plane; when the acceleration straight line flies flatly and the deceleration straight line flies flatly, the left distance, the right distance, the upper distance and the lower distance are the same as those of the uniform speed flatly flying.
7. The unmanned aerial vehicle track compliance monitoring and early warning method according to claim 4, wherein when the deceleration straight line flies flat, the front, rear, left, right, upper and lower boundary distances of the total error envelope are respectively: Forward distance: ; Rear distance: ; In the formula, 、 Respectively represents the standard deviation of the navigation error and the annotation difference of the control error in the horizontal direction, The standard deviation of the system delay is indicated, The standard deviation of the acceleration of the unmanned aerial vehicle is represented, Representing the bisecting speed of the unmanned plane; when the acceleration straight line flies flatly and the deceleration straight line flies flatly, the left distance, the right distance, the upper distance and the lower distance are the same as those of the uniform speed flatly flying.
8. The unmanned aerial vehicle track compliance monitoring and early warning method according to claim 4, wherein when the straight line climbs, the front distance, the rear distance, the left distance and the right distance are the same as those of the uniform straight line flat flight; According to the command issuing time t0, the earliest climbing time t1, the expected climbing time t2, the latest climbing time t3, the earliest leveling time t4, the expected leveling time t5 and the latest leveling time t6, the method is divided into 5 stages: when t0 is less than or equal to t < t1 and t > t6, the unmanned aerial vehicle is in a plane flight stage and is a three-dimensional ellipsoid; when 1<t is less than or equal to t3, Upper distance: ; The following distance is as follows: ;; When 3<t is less than or equal to t4, Upper distance: ; The following distance is as follows: ; when t4 is less than or equal to t6, Upper distance: ; The following distance is as follows: ; In the formula, 、 The navigation error standard deviation and the control error standard deviation in the vertical direction are respectively represented, and RC represents the climbing rate.
9. The unmanned aerial vehicle track compliance monitoring and early warning method according to claim 4, wherein when the unmanned aerial vehicle is in straight line descending, a front distance, a rear distance, a left distance and a right distance are the same as those of uniform straight line flat flight; according to the command issuing time t0, the earliest descending time t1, the expected descending time t2, the latest descending time t3, the earliest leveling time t4, the expected leveling time t5 and the latest leveling time t6, the method is divided into 5 stages: when t0 is less than or equal to t < t1 and t > t6, the unmanned aerial vehicle is in a plane flight stage and is a three-dimensional ellipsoid; when t1 is less than or equal to t3, Upper distance: ; The following distance is as follows: ; When t3 is less than or equal to t4, Upper distance: ; The following distance is as follows: ; when t4 is less than or equal to t6, Upper distance: ; The following distance is as follows: ; In the formula, 、 The navigation error standard deviation and the control error standard deviation in the vertical direction are shown, respectively, and RD represents the rate of decrease.
10. The unmanned aerial vehicle track compliance monitoring and early warning method according to claim 4, wherein the horizontal track compliance envelope of the flat flight turns is composed of the largest outer envelope of the constant-speed flat flight three-dimensional track compliance envelopes corresponding to the earliest turning track, the expected turning track and the latest turning track; The horizontal track coincidence envelope of the turning climbing and the turning descending is the same as that of the flat fly turning, and the vertical track coincidence envelope of the turning climbing and the turning descending is the same as that of the turning climbing and the turning descending respectively.

Description

Unmanned aerial vehicle track compliance monitoring and early warning method Technical Field The invention belongs to the technical field of unmanned aerial vehicle airspace safety management, and particularly relates to an unmanned aerial vehicle track compliance monitoring and early warning method. Background With the vigorous development of low-altitude economy, unmanned aerial vehicles are increasingly widely applied to scenes such as logistics distribution, agricultural plant protection, electric power inspection, urban air traffic and the like. Meanwhile, the proliferation of the number of unmanned aerial vehicles in the airspace also brings unprecedented challenges to low-altitude safety management and control, and particularly, the method effectively monitors and prevents the unauthorized unmanned aerial vehicles from invading sensitive areas (such as airport clearance areas, military management areas and the like). Under the background, the prediction and the monitoring of the accurate flight path of the unmanned aerial vehicle, particularly when the unmanned aerial vehicle performs the maneuvering action, become the key for improving the perception and the operation efficiency of the airspace security situation. However, the real track of the unmanned aerial vehicle is affected by coupling of various complex factors, so that deviation exists between the real track and a preset ideal track. The track compliance is the degree of deviation of the actual track of the unmanned aerial vehicle from the target track. The target track is the nominal position that the unmanned aerial vehicle is expected to reach as predicted by flight plan, current position, dynamics. The flight path compliance reflects the ability of the unmanned aerial vehicle to maintain a flight plan and is a key index for unmanned aerial vehicle flight path monitoring. The existing track monitoring method still has obvious limitations in terms of accuracy and reliability, and is mainly characterized in the following aspects: The actual flight position of the unmanned aerial vehicle is not only dependent on a navigation system (such as GPS) of the unmanned aerial vehicle, but also is comprehensively influenced by dynamic response errors of the flight control system, noise of an airborne sensor, random delay of data link communication and complex environments (such as urban wind fields). In particular, when the unmanned aerial vehicle performs motor actions such as acceleration and steering, the coupling effect of the factors is more remarkable. Most current track monitoring models fail to sufficiently fuse the heterogeneous error sources, so that the prediction range of the possible positions of the unmanned aerial vehicle is too optimistic, and the accuracy is insufficient. Model misalignment under maneuver the prior art lacks fine modeling of the dynamics of the unmanned aerial vehicle during transient maneuvers such as climb/descent, acceleration/deceleration, cornering, etc. The traditional motion model is often based on ideal assumptions such as uniform speed or uniform acceleration, and complex stress changes in maneuvering flight cannot be accurately described, so that larger deviation occurs in track prediction at key time. The environment perception and the adaptability are insufficient, and the influence of the external environment, especially the complex wind field, on the unmanned aerial vehicle track is of great importance. Research shows that wind field simulation and intelligent path planning in urban environments are current research fronts. However, most existing monitoring models cannot effectively integrate real-time or predicted wind field data, and also do not fully consider the changes of aerodynamic characteristics of an aircraft along with wind directions and wind speeds, so that the robustness of the model under complex meteorological conditions is poor. And (3) the model is disjointed from the practical application, namely, part of research begins to try to carry out integrated design of track planning and control through methods such as deep reinforcement learning, or train a lightweight and efficient navigation strategy by utilizing a differentiable physical engine. Although the method has potential, the core of the method focuses on the control and obstacle avoidance of the unmanned aerial vehicle, and the method is not specially used for an application scene of monitoring and early warning the high-precision track compliance of the unmanned aerial vehicle by a third party (such as an air management system). Furthermore, these advanced algorithms typically rely on high performance computing platforms and are difficult to deploy at low cost at monitoring terminals that require fast response. Disclosure of Invention The invention aims to provide the unmanned aerial vehicle track compliance monitoring and early warning method, solve the technical problems in the prior art, provide a monitoring means capable of