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

Abstract

The invention 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 tracking and evaluation unit and a flight management unit, according to the invention, analysis is carried out preliminarily from the angle of fitness of the flight route of the target unmanned aerial vehicle to know whether the flight route of the target unmanned aerial vehicle is yawed, and prediction management is further carried out on mobile obstacle avoidance of the target unmanned aerial vehicle to improve the flight coping ability of the target unmanned aerial vehicle. According to the method, the front-end interference and the rear-end interference of the target unmanned aerial vehicle are analyzed, so that targeted adjustment and management are performed according to information feedback conditions, and based on the rear-end interference, the rear-end interference is further divided, and whether yaw response measures of the target unmanned aerial vehicle need to be taken is judged, so that unnecessary management cost is reduced.

Description

Technical Field

[0001] The present invention relates to the technical field of unmanned aerial vehicle (UAV) flight management, and in particular to an UAV operation tracking and control system applied to regional cruise detection. Background Art

[0002] With the continuous advancement of science and technology, drones are increasingly used in various fields, especially in regional patrol inspections. With their advantages such as flexibility, high efficiency and low cost, drones have gradually become an important detection method. For example, in power inspections, security monitoring, environmental monitoring and other fields, drones can quickly reach designated areas and conduct real-time monitoring and data collection. However, existing drone path planning methods are often based on simple map information or preset routes, which are difficult to adapt to complex and changing regional environments. Consequently, it is difficult to achieve automatic obstacle avoidance during flight. Furthermore, it is difficult to analyze the causes of drone deviations, which increases the risk of regional cruise errors and makes it difficult to ensure stable flight. In view of the above technical defects, a solution is now proposed. Summary of the Invention

[0003] The purpose of the present invention is to provide a UAV operation tracking and control system for regional cruise detection to solve the technical defects mentioned above. The present invention initially analyzes from the perspective of the fit of the target UAV's flight path, so as to intuitively understand whether the target UAV's flight path has yawed, and further predicts and manages the target UAV's mobile obstacle avoidance based on the information feedback to improve the target UAV's flight response capability. Based on the premise of yaw, the target UAV is analyzed from the two points of front-end interference and rear-end interference to determine whether the target UAV's flight yaw is caused by front-end interference or rear-end interference, so as to make targeted adjustments and management based on the information feedback to improve the target UAV's flight stability, and further divide the rear-end interference based on the rear-end interference to determine whether it is necessary to make yaw response measures for the target UAV to reduce unnecessary management costs.

[0004] The object of the present invention can be achieved by the following technical solutions: an unmanned aerial vehicle operation tracking and control system applied to regional cruise detection, comprising an unmanned flight tracking control center, a flight alignment unit, a flight obstacle avoidance unit, a front-end yaw unit, a rear-end yaw unit, a rear-end tracking unit, and a flight management unit; The unmanned flight tracking control center is used to retrieve the flight coordinates of the target UAV and send the flight coordinates to the flight alignment unit for flight route tracking supervision analysis, and to perform discrimination processing on the obtained flight alignment to obtain a normal signal or a yaw signal. When a normal signal is generated, the flight obstacle avoidance unit is used to perform obstacle avoidance risk management analysis on the collected obstacle information to obtain an obstacle avoidance signal or a safety signal; When generating a yaw signal, the front-end yaw unit is used to evaluate and analyze the front-end risk interference of the collected flight interference information of the target UAV, discriminate and process the number of abnormal parameters obtained, and obtain a front-end stable signal or a front-end interference signal. The rear-end yaw unit is used to perform yaw interference rear-end monitoring feedback analysis on the collected rear-end positioning data of the target UAV to obtain a normal signal or a rear-end impact signal. When a back-end impact signal is generated, the back-end evaluation unit is used to perform a back-end interference response evaluation and analysis on the maximum value of the collected flight steering angle of the target UAV to obtain an inertial signal or a non-inertial signal.

[0005] Preferably, the flight route tracking, supervision and analysis process is as follows: the flight period of the target UAV is collected, and the flight period of the target UAV is set as a time threshold, the flight coordinates of the target UAV within the time threshold are obtained, and the flight route characteristic curve of the target UAV 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 fit between the flight route characteristic curve and the preset flight route characteristic curve is obtained, and it is set as the flight fit, and the flight fit is judged and processed to obtain a normal signal or a yaw signal.

[0006] Preferably, the obstacle avoidance risk management analysis process is as follows: obtaining obstacle information within the set warning range of the target UAV within the time threshold, the obstacle information includes fixed obstacles and mobile obstacles, and performing discrimination processing on the obstacle information. 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 includes flight coordinates and flight speed. Based on the basic information of the mobile obstacle, a predicted movement curve of the mobile obstacle is obtained, 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.

[0007] Preferably, the front-end risk interference assessment and analysis process is as follows: obtaining flight interference information of the target UAV within a time threshold, the flight interference information including environmental information and UAV information; Obtain the evaluation results of various parameters in the flight interference information of the target UAV, including qualified and unqualified results, and analyze the evaluation results of various parameters. 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; The number of abnormal parameters is obtained, and the number of abnormal parameters is discriminated and processed: a front-end stable signal or a front-end interference signal is obtained.

[0008] Preferably, the yaw disturbance back-end monitoring feedback analysis process is as follows: Obtain the back-end positioning data of the target drone within the time threshold. The back-end positioning data represents the product of the interruption frequency and interruption duration of the back-end GPS or Beidou positioning signal of the target drone after data normalization. The waypoint data of the target UAV within the time threshold is obtained. The waypoint data indicates the number of back-end waypoint heading angle settings errors of the target UAV. The back-end waypoint heading angle setting error indicates that the angle between the target heading of the target UAV and the actual route exceeds the preset threshold.

[0009] Preferably, the back-end positioning data and waypoint data are discriminated and processed. If the back-end positioning data is less than a preset back-end positioning data threshold and the waypoint data is equal to zero, a normal signal is generated. If the back-end positioning data is greater than or equal to the preset back-end positioning data threshold, or the waypoint data is not equal to zero, a back-end impact signal is generated.

[0010] Preferably, the back-end interference response evaluation and analysis process is as follows: the time period corresponding to the deviation of the flight path characteristic curve of the target UAV from the preset flight path characteristic curve is obtained, and it is set as the actual yaw duration, and the maximum value of the flight steering angle of the target UAV within the actual yaw duration is obtained. The maximum value of the flight steering angle represents the maximum value of the angle value of the target UAV's flight heading change within the actual yaw duration, and the maximum value of the flight steering angle is judged and processed. If the maximum value of the flight steering angle is greater than the preset threshold, an inertial signal is generated. If the maximum value of the flight steering angle is less than or equal to the preset threshold, a non-inertial signal is generated.

[0011] The beneficial effects of the present invention are as follows: The present invention initially analyzes the target UAV's flight path from the perspective of fit, so as to intuitively understand whether the target UAV's flight path has deviated, so as to provide timely warnings to improve the target UAV's flight stability and safety. Based on the information feedback, the target UAV's mobile obstacle avoidance is further predicted and managed to improve the target UAV's flight response capability. Based on the premise of yaw, the present invention analyzes the front-end interference and rear-end interference of the target UAV to determine whether the flight yaw of the target UAV is caused by the front-end interference or the rear-end interference, so as to make targeted adjustments and management according to the information feedback to improve the flight stability of the target UAV. Based on the rear-end interference, the rear-end interference is further divided to determine whether it is necessary to take countermeasures to the yaw of the target UAV to reduce unnecessary management costs. BRIEF DESCRIPTION OF THE DRAWINGS

[0012] The present invention will be further described below with reference to the accompanying drawings; Figure 1 It is a flow chart of the system of the present invention; Figure 2 It is a reference diagram for analyzing an embodiment of the present invention. DETAILED DESCRIPTION

[0013] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0014] References to "embodiments" herein mean that a particular feature, structure, or characteristic described in connection with the embodiment may be included in at least one embodiment of the present invention. The appearance of the phrase in various places in the specification does not necessarily refer to the same embodiment, nor does it constitute a separate or alternative embodiment that is mutually exclusive of other embodiments. It is understood, both explicitly and implicitly, by those skilled in the art that the embodiments described herein may be combined with other embodiments; Example 1

[0015] See also Figures 1 to 2 As shown, the present invention is a UAV operation tracking and 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 yaw unit, a rear-end yaw unit, a rear-end tracking unit and a flight management unit. The unmanned flight tracking control center is connected to the flight fitting unit in a two-way communication manner, the flight fitting unit is connected to the flight obstacle avoidance unit and the front-end yaw unit in a one-way communication manner, the flight obstacle avoidance unit and the front-end yaw unit are connected to the flight management unit in a one-way communication manner, the unmanned flight tracking control center is connected to the rear-end yaw unit in a one-way communication manner, the rear-end yaw unit is connected to the rear-end tracking unit in a two-way communication manner, and the rear-end yaw unit is connected to the flight management unit in a one-way communication manner. The unmanned flight tracking control center is used to retrieve the flight coordinates of the target drone and send the flight coordinates to the flight alignment unit for flight path tracking supervision and analysis, so as to intuitively understand whether the flight path of the target drone has deviated, so as to provide timely warnings to improve the flight stability and safety of the target drone. The specific flight path tracking supervision and analysis process is as follows: The flight period of the target UAV is collected, and the flight period of the target UAV is set as a time threshold, the flight coordinates of the target UAV within the time threshold are obtained, and the flight path characteristic curve of the target UAV is obtained based on the flight coordinates, and the flight path characteristic curve is compared and analyzed with a preset flight path characteristic curve, and the fit between the flight path characteristic curve and the preset flight path characteristic curve is obtained and set as the flight fit, and the flight fit is judged and processed. If the flight fit is greater than or equal to the preset flight fit threshold, a normal signal is generated; if the flight fit is less than the preset flight fit threshold, a yaw signal is generated, and the flight management unit is used to respond to the normal signal or the yaw signal and immediately perform a preset warning operation corresponding to the normal signal or the yaw signal, so as to intuitively understand whether the flight path of the target UAV has deviated, so as to make a warning in time, thereby improving the flight stability and safety of the target UAV; When a normal signal is generated, the flight obstacle avoidance unit is used to perform obstacle avoidance risk management analysis on the collected obstacle information, so as to make reasonable obstacle avoidance responses based on the information feedback to improve the flight safety of the target UAV. The specific obstacle avoidance risk management analysis process is as follows: Obstacle information within a set warning range of the target UAV within a time threshold is obtained. The obstacle information includes fixed obstacles and mobile obstacles. The obstacle information is then identified and processed. 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, including flight coordinates, flight speed, etc. Based on the basic information of the mobile obstacle, a predicted movement curve of the mobile obstacle is obtained. The predicted movement curve is compared and analyzed with a preset flight path characteristic curve. If the predicted movement curve and the preset flight path characteristic curve intersect, an obstacle avoidance signal is generated. If the predicted movement curve and the preset flight path characteristic curve do not intersect, a safety signal is generated. The flight management unit is configured to respond to the planning signal, obstacle avoidance signal, or safety signal and immediately perform a preset warning operation corresponding to the planning signal, obstacle avoidance signal, or safety signal. The preset warning operation corresponding to the planning signal is to plan an obstacle avoidance route and issue a warning. The preset warning operation corresponding to the obstacle avoidance signal is to issue a warning and replan the obstacle avoidance route. The preset warning operation corresponding to the safety signal is to display a safety status. Example 2

[0016] When generating a yaw signal, the front-end yaw unit is used to evaluate and analyze the front-end risk interference of 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 the front-end interference, so as to make targeted adjustments and management based on the information feedback to improve the flight stability of the target UAV. The specific front-end risk interference evaluation and analysis process is as follows: Obtain flight interference information of the target drone within the time threshold. The flight interference information includes parameters such as environmental information and drone information. Environmental information includes average wind speed and ambient temperature, while drone information includes operating voltage and wing speed. Obtain the evaluation results of various parameters in the flight interference information of the target UAV, including qualified and unqualified results, and analyze the evaluation results of various parameters. 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; Get the number of abnormal parameters and perform judgment on the number of abnormal parameters: If the number of abnormal parameters is equal to zero, a front-end stability signal is generated; 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 stability signal or the front-end interference signal and immediately display the preset warning text corresponding to the front-end stability signal or the front-end interference signal, so as to intuitively understand whether the flight deviation of the target UAV is caused by the front-end interference, so as to make targeted adjustments and management based on the information feedback to improve the flight stability of the target UAV; When a yaw signal is generated, the back-end yaw unit is used to perform yaw interference back-end monitoring feedback analysis on the collected back-end positioning data of the target UAV, so as to intuitively understand whether the flight yaw of the target UAV is caused by back-end interference. The specific yaw interference back-end monitoring feedback analysis process is as follows: The backend positioning data of the target UAV is obtained within the time threshold. The backend positioning data represents the product of the interruption frequency and interruption duration of the backend GPS or Beidou positioning signal of the target UAV after data normalization. It should be noted that the larger the value of the backend positioning data, the greater the impact of the backend positioning interference on the yaw; Obtain the waypoint data of the target drone within the time threshold. The waypoint data indicates the number of backend waypoint heading angle settings errors of the target drone. Backend waypoint heading angle setting errors indicate that the angle between the target heading of the target drone and the actual route exceeds the preset threshold. The back-end positioning data and waypoint data are discriminated and processed. If the back-end positioning data is less than the preset back-end positioning data threshold and the waypoint data is equal to zero, a normal signal is generated. If the back-end positioning data is greater than or equal to the preset back-end positioning data threshold, or the waypoint data is not equal to zero, a back-end impact signal is generated. The flight management unit is used to respond to the normal signal or the back-end impact signal and immediately display the preset warning text corresponding to the normal signal or the back-end impact signal, so as to intuitively understand whether the target UAV's flight deviation is caused by back-end interference, so as to make targeted adjustments and management based on the information feedback to improve the flight stability of the target UAV; When the back-end impact signal is generated, the back-end tracking unit is used to perform back-end interference response evaluation and analysis on the maximum value of the collected flight steering angle of the target UAV, so as to further classify the back-end interference and determine whether it is necessary to take yaw response measures for the target UAV. The specific back-end interference response evaluation and analysis process is as follows: The time period corresponding to the deviation of the target UAV's flight path characteristic curve from the preset flight path characteristic curve is obtained, and the time period is set as the actual yaw duration. The maximum value of the target UAV's flight steering angle within the actual yaw duration is obtained. The maximum value of the flight steering angle represents the maximum value of the angle value of the target UAV's flight heading change within the actual yaw duration. The maximum value of the flight steering angle is judged and processed. If the maximum value of the flight steering angle is greater than a preset threshold, an inertial signal is generated. If the maximum value of the flight steering angle is less than or equal to the preset threshold, a non-inertial signal is generated. The flight management unit is used to respond to the inertial signal or the non-inertial signal and immediately display the preset warning text corresponding to the response inertial signal or the non-inertial signal, so as to further classify the back-end interference and judge whether it is necessary to take countermeasures for the yaw of the target UAV, so as to reduce unnecessary management costs. To sum up, the present invention preliminarily analyzes from the perspective of the fit of the flight path of the target UAV, so as to intuitively understand whether the flight path of the target UAV has deviated, so as to make timely early warning to improve the flight stability and safety of the target UAV, and further predicts and manages the mobile obstacle avoidance of the target UAV based on the information feedback to improve the flight response capability of the target UAV. Based on the premise of yaw, the front-end interference and rear-end interference of the target UAV are analyzed to determine whether the flight yaw of the target UAV is caused by front-end interference or rear-end interference, so as to make targeted adjustments and management based on the information feedback to improve the flight stability of the target UAV, and further divide the rear-end interference based on the rear-end interference to determine whether it is necessary to take measures to deal with the yaw of the target UAV to reduce unnecessary management costs.

[0017] The threshold is set for result comparison and analysis to determine whether it is good or bad. The value of the threshold is set based on a combination of large-scale model analysis of sample data and manual experience to enter and store data. It can also be appropriately adjusted based on seasonal or common sense influencing conditions. The size of the coefficient is to quantify each parameter to obtain a specific numerical value, which is convenient for subsequent comparison. The size of the coefficient depends on the amount of sample data and the preliminary setting of the corresponding operating coefficient for each set of sample data by technical personnel in this field; as long as it does not affect the proportional relationship between the parameter and the quantized value.

[0018] The above description is only a preferred specific embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any technician familiar with the technical field, within the technical scope disclosed by the present invention, who makes equivalent replacements or changes based on the technical solution and inventive concept of the present invention, should be covered by the scope of protection of the present invention.

Claims

1. The UAV tracking control system used for regional patrol detection is characterized by: It includes unmanned flight tracking control center, flight alignment unit, flight obstacle avoidance unit, front-end yaw unit, rear-end yaw unit, rear-end tracking unit and flight management unit; The unmanned flight tracking control center is used to retrieve the flight coordinates of the target UAV and send the flight coordinates to the flight alignment unit for flight route tracking supervision analysis, and to perform discrimination processing on the obtained flight alignment to obtain a normal signal or a yaw signal. When a normal signal is generated, the flight obstacle avoidance unit is used to perform obstacle avoidance risk management analysis on the collected obstacle information to obtain an obstacle avoidance signal or a safety signal; When generating a yaw signal, the front-end yaw unit is used to evaluate and analyze the front-end risk interference of the collected flight interference information of the target UAV, discriminate and process the number of abnormal parameters obtained, and obtain a front-end stable signal or a front-end interference signal. The rear-end yaw unit is used to perform yaw interference rear-end monitoring feedback analysis on the collected rear-end positioning data of the target UAV to obtain a normal signal or a rear-end impact signal. When a back-end impact signal is generated, the back-end evaluation unit is used to perform a back-end interference response evaluation and analysis on the maximum value of the collected flight steering angle of the target UAV to obtain an inertial signal or a non-inertial signal.

2. The UAV operation tracking and control system for regional cruise detection according to claim 1 is characterized in that: The flight route tracking, supervision and analysis process is as follows: the flight period of the target UAV is collected, and the flight period of the target UAV is set as a time threshold, the flight coordinates of the target UAV within the time threshold are obtained, and the flight route characteristic curve of the target UAV is obtained based on the flight coordinates, and the flight route characteristic curve is compared and analyzed with the preset flight route characteristic curve, and the fit between the flight route characteristic curve and the preset flight route characteristic curve is obtained and set as the flight fit, and the flight fit is judged and processed to obtain a normal signal or a yaw signal.

3. The UAV operation tracking and control system for regional cruise detection according to claim 1 is characterized in that: The obstacle avoidance risk management analysis process is as follows: obstacle information within a set warning range of the target UAV within a time threshold is obtained, the obstacle information includes fixed obstacles and mobile obstacles, and the obstacle information is discriminated and processed. 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 includes flight coordinates and flight speed. Based on the basic information of the mobile obstacle, a predicted movement curve of the mobile obstacle is obtained, and 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.

4. The UAV operation tracking and control system for regional cruise detection according to claim 1 is characterized in that: The front-end risk interference assessment and analysis process is as follows: obtaining flight interference information of the target UAV within a time threshold, the flight interference information including environmental information and UAV information; Obtain the evaluation results of various parameters in the flight interference information of the target UAV, including qualified and unqualified results, and analyze the evaluation results of various parameters. 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; The number of abnormal parameters is obtained, and the number of abnormal parameters is discriminated and processed: a front-end stable signal or a front-end interference signal is obtained.

5. The UAV operation tracking and control system for regional cruise detection according to claim 1 is characterized in that: The yaw disturbance back-end monitoring feedback analysis process is as follows: Obtain the back-end positioning data of the target drone within the time threshold. The back-end positioning data represents the product of the interruption frequency and interruption duration of the back-end GPS or Beidou positioning signal of the target drone after data normalization. The waypoint data of the target UAV within the time threshold is obtained. The waypoint data indicates the number of back-end waypoint heading angle settings errors of the target UAV. The back-end waypoint heading angle setting error indicates that the angle between the target heading of the target UAV and the actual route exceeds the preset threshold.

6. The UAV operation tracking and control system for regional cruise detection according to claim 5 is characterized in that: The backend positioning data and waypoint data are discriminated and processed. If the backend positioning data is less than the preset backend positioning data threshold and the waypoint data is equal to zero, a normal signal is generated. If the backend positioning data is greater than or equal to the preset backend positioning data threshold, or the waypoint data is not equal to zero, a backend impact signal is generated.

7. The UAV operation tracking and control system for regional cruise detection according to claim 1 is characterized in that: The back-end interference response evaluation and analysis process is as follows: the time period corresponding to the deviation of the target UAV's flight path characteristic curve from the preset flight path characteristic curve is obtained, and the time period is set as the actual yaw duration, and the maximum value of the target UAV's flight steering angle within the actual yaw duration is obtained. The maximum value of the flight steering angle represents the maximum value of the angle value of the target UAV's flight heading change within the actual yaw duration, and the maximum value of the flight steering angle is judged and processed. If the maximum value of the flight steering angle is greater than the preset threshold, an inertial signal is generated. If the maximum value of the flight steering angle is less than or equal to the preset threshold, a non-inertial signal is generated.

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