Unmanned aerial vehicle operation tracking control system applied to regional cruise detection

Abstract

The application relates to the technical field of unmanned aerial vehicle flight management, in particular to an unmanned aerial vehicle operation tracking control system applied to regional cruise detection, which comprises an unmanned flight tracking control center, a flight fitting unit, a flight obstacle avoidance unit, a front end yaw unit, a rear end yaw unit, a rear end evaluation unit and a flight management unit; the application preliminarily analyzes the fitting degree of the flight route of a target unmanned aerial vehicle to understand whether the flight route of the target unmanned aerial vehicle deviates, further predicts and manages the movement obstacle avoidance of the target unmanned aerial vehicle to improve the flight response capability of the target unmanned aerial vehicle, analyzes the front end interference and the rear end interference of the target unmanned aerial vehicle based on the premise of yaw to make targeted adjustment and management according to the information feedback, and further divides the rear end interference based on the rear end interference to judge whether the yaw response measure of the target unmanned aerial vehicle needs to be taken to reduce unnecessary management cost.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of unmanned aerial vehicle flight management, and particularly relates to an unmanned aerial vehicle operation tracking control system applied to regional cruise detection. BACKGROUND

[0002] With the continuous progress of science and technology, unmanned aerial vehicles are increasingly widely used in various fields. In the field of regional cruise detection, unmanned aerial vehicles gradually become an important detection means due to their flexibility, efficiency, and low cost. For example, in the fields of power inspection, security monitoring, and environmental monitoring, unmanned aerial vehicles can quickly reach the designated area for real-time monitoring and data collection.

[0003] However, the existing unmanned aerial vehicle path planning method is often based on simple map information or preset flight routes, which is difficult to adapt to complex and variable regional environments, and thus difficult to achieve automatic obstacle avoidance during flight. Moreover, it is difficult to analyze the reasons for the deviation of the unmanned aerial vehicle flight, which increases the risk of regional cruise error of the unmanned aerial vehicle, and it is difficult to ensure the stable flight of the unmanned aerial vehicle.

[0004] In view of the above technical defects, a solution is proposed. SUMMARY

[0005] The present application aims to provide an unmanned aerial vehicle operation tracking control system applied to regional cruise detection to solve the above technical defects. The present application preliminarily analyzes the flight route fitting degree of the target unmanned aerial vehicle to intuitively understand whether the target unmanned aerial vehicle flight route deviates. Based on the information feedback, the movement obstacle avoidance of the target unmanned aerial vehicle is further predicted and managed to improve the flight response capability of the target unmanned aerial vehicle. Based on the premise of deviation, the front-end interference and rear-end interference of the target unmanned aerial vehicle are analyzed to determine whether the target unmanned aerial vehicle flight deviation is caused by front-end interference or rear-end interference. Based on the information feedback, targeted adjustments and management are made to improve the flight stability of the target unmanned aerial vehicle. Based on the rear-end interference, the rear-end interference is further divided to determine whether the deviation response measures of the target unmanned aerial vehicle need to be taken to reduce unnecessary management costs.

[0006] The purpose of the present application can be achieved by the following technical solution: an unmanned aerial vehicle operation tracking control system applied to regional cruise detection, comprising an unmanned flight tracking control center, a flight fitting unit, a flight obstacle avoidance unit, a front-end deviation unit, a rear-end deviation unit, a rear-end evaluation unit, and a flight management unit.

[0007] The unmanned flight tracking control center is used to call flight coordinates of the target unmanned aerial vehicle, and send the flight coordinates to the flight fitting unit for flight route tracking supervision analysis, and to obtain a flight fitting degree, and to obtain a normal signal or a deviation signal, when the normal signal is generated, the flight obstacle avoidance unit is used for obstacle avoidance risk management analysis on the collected obstacle information, to obtain an obstacle avoidance signal or a safety signal;

[0008] When the deviation signal is generated, the front-end deviation unit is used for front-end risk interference evaluation analysis on the collected flight interference information of the target unmanned aerial vehicle, and the number of abnormal parameters is discriminated to obtain a front-end stable signal or a front-end interference signal, and the rear-end deviation unit is used for deviation interference rear-end monitoring feedback analysis on the collected rear-end positioning data of the target unmanned aerial vehicle, to obtain a normal signal or a rear-end influence signal.

[0009] When the rear-end influence signal is generated, the rear-end evaluation unit is used for rear-end interference coping evaluation analysis on the maximum value of the flight turning angle of the target unmanned aerial vehicle, to obtain an inertial signal or a non-inertial signal.

[0010] Preferably, the flight route tracking supervision analysis process is as follows: the flight period of the target unmanned aerial vehicle is collected, and the flight period of the target unmanned aerial vehicle is set as a time threshold, the flight coordinates of the target unmanned aerial vehicle within the time threshold are obtained, the flight route characteristic curve of the target unmanned aerial vehicle is obtained based on the flight coordinates, the flight route characteristic curve is compared and analyzed with the preset flight route characteristic curve, the fitting degree between the flight route characteristic curve and the preset flight route characteristic curve is obtained, and is set as the flight fitting degree, and the flight fitting degree is discriminated to obtain a normal signal or a deviation signal.

[0011] Preferably, the obstacle avoidance risk management analysis process is as follows: the obstacle information in the set warning range of the target unmanned aerial vehicle within the time threshold is obtained, the obstacle information includes fixed obstacles and mobile obstacles, and the obstacle information is discriminated, if the obstacle information is a fixed obstacle, a planning signal is generated, if the obstacle information is a mobile obstacle, a collision signal is generated, when the collision signal is generated, the basic information of the mobile obstacle is obtained, the basic information includes flight coordinates and flight speed, the predicted movement curve of the mobile obstacle is obtained based on the basic information of the mobile obstacle, and the predicted movement curve is compared and analyzed with the preset flight route characteristic curve, to obtain an obstacle avoidance signal or a safety signal.

[0012] Preferably, the front-end risk interference evaluation analysis process is as follows: the flight interference information of the target unmanned aerial vehicle within the time threshold is obtained, the flight interference information includes environmental information and unmanned aerial vehicle information;

[0013] The evaluation results of the parameters in the flight interference information of the target unmanned aerial vehicle are obtained, the evaluation results include qualified and unqualified, and the evaluation results of the parameters are analyzed, if the evaluation result is qualified, the corresponding parameter is determined as a normal parameter, if the evaluation result is unqualified, the corresponding parameter is determined as an abnormal parameter;

[0014] The number of abnormal parameters is obtained, and the number of abnormal parameters is discriminated to obtain the front-end stable signal or the front-end interference signal.

[0015] Preferably, the yaw interference rear-end monitoring feedback analysis process is as follows:

[0016] The rear-end positioning data of the target unmanned aerial vehicle within the time threshold is obtained, the rear-end positioning data represents the product value obtained by multiplying the data normalized processing values of the rear-end GPS or Beidou positioning signal interruption frequency and interruption time length value of the target unmanned aerial vehicle;

[0017] The waypoint data of the target unmanned aerial vehicle within the time threshold is obtained, the waypoint data represents the number of rear-end waypoint heading angle setting errors of the target unmanned aerial vehicle, and the rear-end waypoint heading angle setting error represents the included angle between the target heading and the actual flight path of the target unmanned aerial vehicle exceeding the preset threshold.

[0018] Preferably, the rear-end positioning data and the waypoint data are discriminated, if the rear-end positioning data is less than the preset rear-end positioning data threshold, and the waypoint data is equal to zero, a normal signal is generated, if the rear-end positioning data is greater than or equal to the preset rear-end positioning data threshold, or the waypoint data is not equal to zero, a rear-end influence signal is generated.

[0019] Preferably, the rear-end interference coping evaluation analysis process is as follows: the time period corresponding to the flight route feature curve deviating from the preset flight route feature curve of the target unmanned aerial vehicle is obtained, and is set as the actual yaw time length, the maximum value of the flight turning angle of the target unmanned aerial vehicle within the actual yaw time length is obtained, the maximum value of the flight turning angle represents the maximum value in the angle value of the flight heading change of the target unmanned aerial vehicle within the actual yaw time length, and the maximum value of the flight turning angle is discriminated, if the maximum value of the flight turning angle is greater than the preset threshold, an inertial signal is generated, if the maximum value of the flight turning angle is less than or equal to the preset threshold, a non-inertial signal is generated.

[0020] The beneficial effects of the present application are as follows:

[0021] The present application preliminarily analyzes the fitting degree of the flight route of the target unmanned aerial vehicle, so as to intuitively understand whether the flight route of the target unmanned aerial vehicle deviates, so as to timely perform early warning, so as to improve the flight stability and safety of the target unmanned aerial vehicle, and further predict and manage the movement obstacle avoidance of the target unmanned aerial vehicle according to the information feedback, so as to improve the flight response capability of the target unmanned aerial vehicle.

[0022] The present application is based on the premise of yaw, from the front end of the target UAV interference and rear-end interference two points are analyzed to determine whether the target UAV flight yaw is caused by the front end of the interference or the rear-end interference, in order to make targeted adjustment and management according to the information feedback, to improve the flight stability of the target UAV, and further based on the rear-end interference, the rear-end interference is divided to determine whether the yaw response measures of the target UAV need to be taken to reduce unnecessary management cost. BRIEF DESCRIPTION OF DRAWINGS

[0023] The present application will be further described below with reference to the drawings;

[0024] Fig. 1 is a system flowchart of the present application;

[0025] Fig. 2 is an analysis reference diagram of an embodiment of the present application. DETAILED DESCRIPTION

[0026] The technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative labor are within the scope of protection of the present application.

[0027] In this paper, "embodiment" means that the specific features, structures or characteristics described in conjunction with the embodiment can be included in at least one embodiment of the present application. The phrase appears at various places in the specification does not necessarily refer to the same embodiment, nor is it independent or alternative to other embodiments. Those skilled in the art explicitly and implicitly understand that the embodiments described herein can be combined with other embodiments; Embodiment one

[0028] Please refer to Figs. 1-2 The present application is an unmanned aerial vehicle operation tracking control system applied to regional cruise detection, as shown in the figure, which comprises an unmanned flight tracking control center, a flight fitting unit, a flight obstacle avoidance unit, a front-end yaw unit, a rear-end yaw unit, a rear-end evaluation unit and a flight management unit. The unmanned flight tracking control center is in bidirectional communication connection with the flight fitting unit. The flight fitting unit is in unidirectional communication connection with the flight obstacle avoidance unit and the front-end yaw unit. The flight obstacle avoidance unit and the front-end yaw unit are in unidirectional communication connection with the flight management unit. The unmanned flight tracking control center is in unidirectional communication connection with the rear-end yaw unit. The rear-end yaw unit is in bidirectional communication connection with the rear-end evaluation unit. The rear-end yaw unit is in unidirectional communication connection with the flight management unit.

[0029] The unmanned flight tracking control center is used to call the flight coordinates of the target unmanned machine, and send the flight coordinates to the flight fitting unit for flight line tracking supervision analysis, so as to intuitively understand whether the target unmanned machine flight route deviates, so as to timely warning, so as to improve the flight stability and safety of the target unmanned machine, and the specific flight line tracking supervision analysis process is as follows:

[0030] The flight period of the target unmanned machine is collected, and the flight period of the target unmanned machine is set as a time threshold, the flight coordinates of the target unmanned machine within the time threshold are obtained, the flight route characteristic curve of the target unmanned machine is obtained based on the flight coordinates, and the flight route characteristic curve is compared and analyzed with the preset flight route characteristic curve, the fitting degree between the flight route characteristic curve and the preset flight route characteristic curve is obtained, which is set as the flight fitting degree, and the flight fitting degree is discriminated, if the flight fitting degree is greater than or equal to the preset flight fitting degree threshold, a normal signal is generated, if the flight fitting degree is less than the preset flight fitting degree threshold, a deviation signal is generated, and the flight management unit is used to respond to the normal signal or the deviation signal, and immediately make the preset warning operation corresponding to the normal signal or the deviation signal, so as to intuitively understand whether the target unmanned machine flight route deviates, so as to timely warning, so as to improve the flight stability and safety of the target unmanned machine;

[0031] When the normal signal is generated, the flight obstacle avoidance unit is used for obstacle avoidance risk management analysis on the collected obstacle information, so as to make reasonable obstacle avoidance response according to the information feedback, so as to improve the flight safety of the target unmanned machine, and the specific obstacle avoidance risk management analysis process is as follows:

[0032] Obstacle information in the set warning range of the target unmanned machine within the time threshold is obtained, the obstacle information includes fixed obstacles and moving obstacles, and the obstacle information is discriminated, if the obstacle information is a fixed obstacle, a planning signal is generated, if the obstacle information is a moving obstacle, a collision signal is generated, when the collision signal is generated, the basic information of the moving obstacle is obtained, the basic information includes flight coordinates, flight speed, etc., the predicted moving curve of the moving obstacle is obtained based on the basic information of the moving obstacle, and the predicted moving curve is compared and analyzed with the preset flight route characteristic curve, if the predicted moving curve and the preset flight route characteristic curve exist intersection point, the obstacle avoidance signal is generated, if the predicted moving curve and the preset flight route characteristic curve do not exist intersection point, the safety signal is generated, the flight management unit is used to respond to the planning signal or the obstacle avoidance signal or the safety signal, and immediately make the preset warning operation corresponding to the planning signal or the obstacle avoidance signal or the safety signal, the preset warning operation corresponding to the planning signal: planning obstacle avoidance route and warning, the preset warning operation corresponding to the obstacle avoidance signal: warning, re-planning obstacle avoidance route, the preset warning operation corresponding to the safety signal: display safety. Embodiment Two

[0033] When the yaw signal is generated, the front-end yaw unit is used for front-end risk interference evaluation analysis on the collected flight interference information of the target UAV, so as to intuitively understand whether the flight yaw of the target UAV is caused by front-end interference, so as to make targeted adjustment and management according to the information feedback, and improve the flight stability of the target UAV. The specific front-end risk interference evaluation analysis process is as follows:

[0034] The flight interference information of the target UAV within the time threshold is obtained, and the flight interference information includes environmental information, UAV information and other parameters. The environmental information includes environmental wind speed average, environmental temperature, etc. The UAV information includes operating voltage, wing speed, etc.

[0035] The evaluation results of each parameter in the flight interference information of the target UAV are obtained, and the evaluation results include qualified and unqualified. The evaluation results of each parameter are analyzed. If the evaluation result is qualified, the corresponding parameter is determined to be a normal parameter. If the evaluation result is unqualified, the corresponding parameter is determined to be an abnormal parameter.

[0036] The number of abnormal parameters is obtained, and the number of abnormal parameters is discriminated:

[0037] If the number of abnormal parameters is equal to zero, a front-end stable signal is generated;

[0038] If the number of abnormal parameters is not equal to zero, a front-end interference signal is generated. The flight management unit is used to respond to the front-end stable signal or the front-end interference signal, and immediately display the preset warning text corresponding to the front-end stable signal or the front-end interference signal, so as to intuitively understand whether the flight yaw of the target UAV is caused by front-end interference, so as to make targeted adjustment and management according to the information feedback, and improve the flight stability of the target UAV.

[0039] When the yaw signal is generated, the rear-end yaw unit is used for yaw interference rear-end monitoring feedback analysis on the collected rear-end positioning data of the target UAV, so as to intuitively understand whether the flight yaw of the target UAV is caused by rear-end interference. The specific yaw interference rear-end monitoring feedback analysis process is as follows:

[0040] The rear-end positioning data of the target UAV within the time threshold is obtained. The rear-end positioning data represents the product value obtained by multiplying the data normalized value of the rear-end GPS or Beidou positioning signal interruption frequency and the interruption time value of the target UAV. It should be noted that the larger the value of the rear-end positioning data, the greater the influence of the rear-end positioning interference on the yaw.

[0041] The flight point data of the target unmanned aerial vehicle within a time threshold is acquired, the flight point data representing the number of rear-end flight point heading angle setting errors of the target unmanned aerial vehicle, the rear-end flight point heading angle setting error representing that the included angle between the target heading of the target unmanned aerial vehicle and the actual flight route exceeds a preset threshold;

[0042] The rear-end positioning data and the flight point data are discriminated, if the rear-end positioning data is less than a preset rear-end positioning data threshold and the flight point data is equal to zero, a normal signal is generated, if the rear-end positioning data is greater than or equal to the preset rear-end positioning data threshold or the flight point data is not equal to zero, a rear-end influence signal is generated, and the flight management unit is used to respond to the normal signal or the rear-end influence signal and immediately display preset warning words corresponding to the normal signal or the rear-end influence signal, so that it is intuitively understood whether the flight deviation of the target unmanned aerial vehicle is caused by rear-end interference, so that targeted adjustment and management are made according to the information feedback, and the flight stability of the target unmanned aerial vehicle is improved;

[0043] When the rear-end influence signal is generated, the rear-end evaluation unit is used to perform rear-end interference response evaluation analysis on the maximum value of the flight turning angle of the target unmanned aerial vehicle collected, so as to further divide the rear-end interference and determine whether the flight deviation response measure of the target unmanned aerial vehicle needs to be taken, and the specific rear-end interference response evaluation analysis process is as follows:

[0044] The time period corresponding to the deviation of the flight route feature curve of the target unmanned aerial vehicle from the preset flight route feature curve is acquired and is set as the actual deviation time length, the maximum value of the flight turning angle of the target unmanned aerial vehicle within the actual deviation time length is acquired, the maximum value of the flight turning angle representing the maximum value of the angle value of the change of the flight heading of the target unmanned aerial vehicle within the actual deviation time length, and the maximum value of the flight turning angle is discriminated, if the maximum value of the flight turning angle is greater than a preset threshold, an inertia signal is generated, if the maximum value of the flight turning angle is less than or equal to the preset threshold, a non-inertia signal is generated, and the flight management unit is used to respond to the inertia signal or the non-inertia signal and immediately display preset warning words corresponding to the inertia signal or the non-inertia signal, so as to further divide the rear-end interference and determine whether the flight deviation response measure of the target unmanned aerial vehicle needs to be taken, so as to reduce unnecessary management cost;

[0045] To sum up, the application preliminarily analyzes the flight route of the target unmanned aerial vehicle from the fitting degree angle, so as to intuitively understand whether the target unmanned aerial vehicle flight route deviates, so as to timely give early warning, so as to improve the flight stability and safety of the target unmanned aerial vehicle, and further predict and manage the movement obstacle avoidance of the target unmanned aerial vehicle according to the information feedback, so as to improve the flight response capability of the target unmanned aerial vehicle, and based on the premise of deviation, the front-end interference and rear-end interference of the target unmanned aerial vehicle are analyzed, so as to judge whether the flight deviation of the target unmanned aerial vehicle is caused by the front-end interference or the rear-end interference, so as to make targeted adjustment and management according to the information feedback, so as to improve the flight stability of the target unmanned aerial vehicle, and based on the rear-end interference, the rear-end interference is further divided, whether the deviation response measures of the target unmanned aerial vehicle need to be made is judged, so as to reduce unnecessary management cost.

[0046] The threshold is set for result comparison and analysis, so as to determine whether it is good or bad, and the size of the threshold is determined according to the large model analysis of sample data and artificial experience, and the threshold is set for storage, and the threshold can also be adjusted according to the seasonal or reasonable influence condition;

[0047] The size of the coefficient is a specific value obtained by quantifying each parameter, so as to facilitate subsequent comparison, and the size of the coefficient depends on the amount of sample data and the corresponding running coefficient preliminarily set by the person skilled in the art for each group of sample data; as long as the proportional relationship between the parameter and the quantized value is not affected.

[0048] The above is only a preferred specific embodiment of the application, but the protection scope of the application is not limited to this, any person skilled in the art in the technical range disclosed by the application can make equivalent replacement or change according to the technical scheme and the inventive concept of the application, which should be covered in the protection scope of the application.

Claims

1. A UAV operation tracking control system applied to regional cruise detection, characterized in that, The unmanned flight tracking control center, the flight fitting unit, the flight obstacle avoidance unit, the front end yaw unit, the rear end yaw unit, the rear end evaluation unit and the flight management unit are included. The unmanned flight tracking control center is used to call flight coordinates of a target unmanned aerial vehicle and send the flight coordinates to the flight fitting unit for flight route tracking supervision analysis, and to obtain normal signals or yaw signals by discriminating the obtained flight fitting degree; when the normal signals are generated, the flight obstacle avoidance unit is used to analyze the collected obstacle information for obstacle avoidance risk management, and to obtain obstacle avoidance signals or safety signals; When the yaw signals are generated, the front end yaw unit is used to analyze the collected flight interference information of the target unmanned aerial vehicle for front end risk interference evaluation analysis, to obtain front end stable signals or front end interference signals by discriminating the number of obtained abnormal parameters, and the rear end yaw unit is used to analyze the collected rear end positioning data of the target unmanned aerial vehicle for yaw interference rear end monitoring feedback analysis, to obtain normal signals or rear end influence signals; When the rear end influence signals are generated, the rear end evaluation unit is used to analyze the maximum value of the flight turning angle of the target unmanned aerial vehicle for rear end interference coping evaluation analysis, to obtain inertial signals or non-inertial signals; The front end risk interference evaluation analysis process is as follows: the flight interference information of the target unmanned aerial vehicle within a time threshold is obtained, and the flight interference information includes environmental information and unmanned aerial vehicle information; The evaluation results of each parameter in the flight interference information of the target unmanned aerial vehicle are obtained, the evaluation results include qualified and unqualified, and the evaluation results of each parameter are analyzed; if the evaluation result is qualified, the corresponding parameter is determined to be a normal parameter, and if the evaluation result is unqualified, the corresponding parameter is determined to be an abnormal parameter; The number of abnormal parameters is obtained, and the number of abnormal parameters is discriminated; if the number of abnormal parameters is equal to zero, the front end stable signal is generated, and if the number of abnormal parameters is not equal to zero, the front end interference signal is generated; The rear end monitoring feedback analysis process of the yaw interference is as follows: The rear end positioning data of the target unmanned aerial vehicle within a time threshold is obtained, and the rear end positioning data represents the product value obtained by multiplying the data normalized values of the rear end GPS or Beidou positioning signal interruption frequency and interruption time length value of the target unmanned aerial vehicle; The waypoint data of the target unmanned aerial vehicle within a time threshold is obtained, and the waypoint data represents the number of rear end waypoint heading angle setting errors of the target unmanned aerial vehicle, and the rear end waypoint heading angle setting error represents the included angle between the target heading of the target unmanned aerial vehicle and the actual flight route that exceeds the preset threshold; The rear end positioning data and the waypoint data are discriminated; if the rear end positioning data is less than a preset rear end positioning data threshold and the waypoint data is equal to zero, the normal signal is generated, and if the rear end positioning data is greater than or equal to the preset rear end positioning data threshold or the waypoint data is not equal to zero, the rear end influence signal is generated; The rear-end interference coping evaluation analysis process is as follows: a time period corresponding to deviation of a flight route characteristic curve of the target unmanned aerial vehicle from a preset flight route characteristic curve is obtained, and the time period is set as an actual deviation time length; a maximum value of a flight turning angle of the target unmanned aerial vehicle in the actual deviation time length is obtained, the maximum value of the flight turning angle representing a maximum value in angle values of change in flight direction of the target unmanned aerial vehicle in the actual deviation time length; and the maximum value of the flight turning angle is subjected to discrimination processing. If the maximum value of the flight turning angle is greater than a preset threshold value, an inertial signal is generated; and if the maximum value of the flight turning angle is less than or equal to the preset threshold value, a non-inertial signal is generated.

2. The UAV flight tracking control system for zone cruise detection of claim 1, wherein, The flight route tracking supervision analysis process is as follows: a flight time period of the target unmanned aerial vehicle is collected, and the flight time period of the target unmanned aerial vehicle is set as a time threshold value; flight coordinates of the target unmanned aerial vehicle in the time threshold value are obtained; a flight route characteristic curve of the target unmanned aerial vehicle is obtained based on the flight coordinates; the flight route characteristic curve is compared and analyzed with a preset flight route characteristic curve; a fitting degree between the flight route characteristic curve and the preset flight route characteristic curve is obtained and set as a flight fitting degree; and the flight fitting degree is subjected to discrimination processing to obtain a normal signal or a deviation signal.

3. The UAV flight tracking control system for zone cruise detection of claim 1, wherein, The obstacle avoidance risk management analysis process is as follows: obstacle information in a set warning range of the target unmanned aerial vehicle in the time threshold value is obtained, the obstacle information including fixed obstacles and mobile obstacles; the obstacle information is subjected to discrimination processing; if the obstacle information is a fixed obstacle, a planning signal is generated; if the obstacle information is a mobile obstacle, a collision signal is generated; when the collision signal is generated, basic information of the mobile obstacle is obtained, the basic information including flight coordinates and flight speed; a predicted movement curve of the mobile obstacle is obtained based on the basic information of the mobile obstacle; the predicted movement curve is compared and analyzed with a preset flight route characteristic curve to obtain an obstacle avoidance signal or a safety signal.

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