137 results about "Flight velocity" patented technology

The invention relates to the technical field of power equipment inspection, and discloses a transmission, transformation and distribution equipment inspection system and method based on an unmanned aerial vehicle, and the system comprises the following specific components: an unmanned aerial vehicle state monitoring module which is connected with a battery management system, is provided with a pressure sensor, and is connected with a flight control system and various sensors; the unmanned aerial vehicle power, load and flight speed parameters are monitored in real time, tasks are dynamically and intelligently distributed and scheduled through deep fusion of multi-dimensional information such as unmanned aerial vehicle states, task attributes and environmental conditions, it is ensured that each unmanned aerial vehicle can execute the best matching task at the best opportunity and the most appropriate place, resource waste and potential risks are avoided, and the unmanned aerial vehicle task scheduling method and system are suitable for large-scale popularization and application. And meanwhile, task allocation is performed according to the states of the unmanned aerial vehicles and task requirements, the resources of each unmanned aerial vehicle are fully utilized, the service life of each unmanned aerial vehicle is prolonged, the inspection cost is reduced, and the resource utilization efficiency is improved.

The invention provides a bridge and tunnel geological disaster monitoring method and system based on an unmanned aerial vehicle, and relates to the technical field of geological disaster monitoring, and the method comprises the steps: obtaining the data of a sensor carried by the unmanned aerial vehicle; performing space-time alignment and confidence coefficient weighting on the three-dimensional point cloud data, the image data and the flight attitude data through a space-time weighted covariance fusion model to obtain fusion deformation feature data; inputting the data into a wavelet-Volterra series coupling prediction algorithm, performing nonlinear deformation prediction on the key part, and outputting a future displacement prediction value; generating a geological disaster risk probability graph according to the predicted value and a preset risk threshold value; and based on the probability graph, dynamically optimizing the flight speed, height and flight path of the unmanned aerial vehicle through a Bayesian adaptive flight path planning module, and outputting a real-time monitoring path instruction. Through multi-modal fusion and dynamic path planning, the geological disaster monitoring precision and the cruising ability of the unmanned aerial vehicle are improved, and the method is suitable for safety protection of bridges and tunnels in complex terrains.

The invention relates to the technical field of city management, in particular to an unmanned aerial vehicle autonomous inspection and task planning method under a global intelligent platform. Comprising the steps that an inspection task instruction from a global intelligent platform is received, and the inspection task instruction comprises a target inspection area, an inspection precision requirement and inspection time limitation; dividing the target inspection area into a plurality of sub-areas, and calculating the inspection complexity coefficient of each sub-area according to the geographical environment, terrain height and obstacle distribution condition of each sub-area; based on the inspection complexity coefficient, the inspection precision requirement and the inspection time limit, utilizing a preset task allocation algorithm to allocate the inspection task to a plurality of unmanned aerial vehicles; for the sub-region tasks allocated to each unmanned aerial vehicle, generating an optimal flight path by using a path optimization algorithm in combination with the cruising ability, the flight speed and the load weight of the unmanned aerial vehicle; according to the invention, the problems of unreasonable task allocation and low overall efficiency in the existing multi-unmanned aerial vehicle inspection system can be solved.

The invention discloses a tilting quad-rotor unmanned aerial vehicle and an unmanned aerial vehicle countering system, and the system comprises a flight control module which is used for controlling the tilting quad-rotor unmanned aerial vehicle to fly towards a target unmanned aerial vehicle, and adjusting the flight mode and the flight speed of the tilting quad-rotor unmanned aerial vehicle in real time according to the distance and the speed difference in the flight process. The target identification module is used for collecting video stream information of a target airspace and detecting whether a target unmanned aerial vehicle exists in the video stream information frame by frame; the target tracking module is used for determining the distance and the speed difference between the target unmanned aerial vehicle and the tilt quad-rotor unmanned aerial vehicle under the condition that the target unmanned aerial vehicle exists in the video stream information; and the net gun capturing module is used for calculating a launching parameter of a capturing net when the distance between the target unmanned aerial vehicle and the tilt quadrotor unmanned aerial vehicle is smaller than a preset distance, and launching the capturing net to the target unmanned aerial vehicle according to the launching parameter. According to the scheme, the unmanned aerial vehicle can be precisely countered.

The invention relates to a multi-mode interactive indoor unmanned aerial vehicle target detection and tracking method and system. The system comprises a target detection and tracking module, a laser radar inertial odometer module, a video display and interaction module and a flight control module. The method comprises the steps that an unmanned aerial vehicle end receives and processes RGB images, laser radar point cloud and IMU data; and optimizing a YOLOv8 target detection model and an OSTrack target tracking model through a TensorRT inference engine. By fusing LiDAR and IMU data, accurate state estimation and map construction are provided. And the ground station end displays a video stream and generates a control command through the video display and interaction module. And calculating a flight speed and a yaw angle rate by estimating an error between the target image position and the current position of the unmanned aerial vehicle, and generating a flight control instruction. The problems that an indoor unmanned aerial vehicle system often faces low target detection precision, poor tracking stability and difficult user interaction experience are solved, and the method and the system are more efficient, more accurate and higher in interactivity.

The invention relates to the technical field of fan blades, in particular to an automatic fan blade coating spraying method and system based on an unmanned aerial vehicle. Comprising the steps that a plurality of blade subareas are set according to the surface structure of the fan blade; according to a preset wear simulation model, an expected wear value of each blade sub-region is generated, and whether a primary spraying strategy is generated or not is judged according to the expected wear values; acquiring a spraying monitoring packet according to a preset feedback time node, and judging whether to correct the primary spraying strategy according to the spraying monitoring packet; the wear degree of each area of the fan blade is remotely predicted according to the wear simulation model in combination with environmental monitoring parameters, each wear point of the protective coating is accurately positioned in combination with image data acquired by the unmanned aerial vehicle, and accurate control of the flight position of the unmanned aerial vehicle is realized by acquiring feature points of each blade sub-area. And meanwhile, the flight speed and the coating flow of the unmanned aerial vehicle are dynamically corrected in time by periodically collecting the thickness of a spraying layer in the spraying process, and the spraying execution efficiency is improved.

The invention relates to an unmanned aerial vehicle detection and control method and system for regional defense, and the method comprises the steps: dividing a to-be-defended region, and setting a differentiated flight forbidding threshold and a detection response priority; secondly, constructing a multi-dimensional cooperative detection network of radio spectrum monitoring, millimeter wave radar, photoelectric tracking and an acoustic sensor based on sub-region division, and collecting multi-source data of the unmanned aerial vehicle in real time; judging a sub-region to which the unmanned aerial vehicle belongs through coordinate matching, screening out over-limit target data, and extracting a target feature set of flight speed, height, communication protocol type, radar reflection cross section and voiceprint information; and inputting a target dynamic classification model, and dynamically outputting three threat levels of a harmless civil type threat level, a suspicious reconnaissance type threat level and a high-risk aggressive type threat level. The hierarchical management and control are executed in combination with the sub-region priority and the threat level, the management and control effect is dynamically evaluated based on the preset evaluation index, and the detection parameter and the management and control strategy are adaptively adjusted, so that the intrusion risk of the core region is effectively reduced, and the intellectualization and adaptive ability of regional defense are improved.

The invention relates to the technical field of geological disaster prevention and treatment, and discloses a geological disaster prevention and treatment method, device and equipment and a storage medium, and the method comprises the steps: generating a scheduling reference information set of each candidate unmanned aerial vehicle through determining the monitoring demands of each geological disaster monitoring sub-region in a target time period; by taking the monitoring frequency, the maximum flight speed and the state information as constraint conditions and taking the minimum number of the selected aerial photography monitoring unmanned aerial vehicles as an optimization target, optimizing and solving a selection strategy of the target aerial photography unmanned aerial vehicles and an execution strategy of the aerial photography monitoring action of each target aerial photography unmanned aerial vehicle; and carrying out monitoring aerial photography actions and carrying out geological disaster prevention and control alarm and strategy updating according to analysis results of geological disaster monitoring aerial photography images so as to reasonably plan aerial photography paths and monitoring strategies of multiple unmanned aerial vehicles in a large-area range, thereby improving geological disaster monitoring efficiency and saving geological disaster air monitoring resources. And updating and adjusting of aerial photography paths and monitoring strategies of multiple unmanned aerial vehicles can be carried out.

The invention discloses an AI-based unmanned aerial vehicle automatic positioning and navigation system, and the system comprises an unmanned aerial vehicle body which obtains a starting point coordinate through a navigation module by manually inputting a terminal point coordinate and a planned flight time length value t, flies to the terminal point coordinate at a flight speed value V1 and a flight height value H1 from the starting point coordinate, automatically completes a flight task, and automatically judges a return flight; and the monitoring unit is used for acquiring an initial electric quantity value Q of the unmanned aerial vehicle body, transmitting the initial electric quantity value to the coordinate unit, monitoring the output power of the storage battery in real time during flight, and generating a feedback signal and transmitting the feedback signal to the correction unit when abnormal output power is generated during flight. The problems that when an existing unmanned aerial vehicle automatic positioning navigation system is used, the endurance problem of the unmanned aerial vehicle is not considered, and the unmanned aerial vehicle cannot return or even falls in the flight process in the actual flight process are solved.

The invention relates to a method for vehicle-based control of a drone (60). The method comprises determining a flight route (92) of the drone (60) and a drone speed profile for the flight route (92) of the drone (60) based on a driving route (90) of a vehicle (50), wherein the drone (60) is controlled from the vehicle (50) via a communication link (70) between the vehicle (50) and the drone (60), an exchange of the flight route (92) and the drone speed profile takes place between the vehicle (50) and the drone (60) so that both the vehicle (50) and the drone (60) have the flight route (92) and the drone speed profile stored, and in the event of at least one interruption of the communication link (70), the drone (60) flies the flight route (92) at a drone speed corresponding to the drone speed profile.

The invention provides an unmanned aerial vehicle entering stage air collision risk analysis method, which comprises the steps of modeling unmanned aerial vehicle entering modes, including a horizontal entering-vertical descending entering mode and a waiting circle-waiting point entering mode; establishing a collision risk model, and calculating position errors of the unmanned aerial vehicle in the horizontal direction and the vertical direction according to a horizontal alarm threshold and a vertical alarm threshold of an unmanned aerial vehicle navigation system; calculating a safety interval between adjacent unmanned aerial vehicles based on a collision risk model; the method comprises the following steps: performing Monte Carlo simulation by considering the randomness of speed error, wind shear and flight speed as well as a pitch angle and a course angle to obtain a relative speed, calculating collision risks at different intervals, comparing safety target levels, and calculating the minimum safety interval of the unmanned aerial vehicle in a horizontal approach-vertical descent approach mode; and calculating a minimum route included angle in the approach mode by using the waiting circle and the waiting point, and planning safety intervals in different approach modes.

The utility model discloses a separable unmanned aerial vehicle intelligent flow measuring device, which relates to a device for measuring fluid velocity, and comprises an unmanned aerial vehicle and a buoyancy tank positioned below the unmanned aerial vehicle, a hanging frame is fixedly mounted on the unmanned aerial vehicle, the buoyancy tank and the hanging frame are detachably connected together, a pull wire is further connected between the hanging frame and the buoyancy tank, and the buoyancy tank and the hanging frame are connected together. The unmanned aerial vehicle is used for driving the buoyancy tank to float on the water surface, and when the buoyancy tank and the unmanned aerial vehicle float along with a river, the unmanned aerial vehicle can directly measure the speed of water flow. The buoyancy tank is arranged on the unmanned aerial vehicle, when water flow is measured, the unmanned aerial vehicle directly floats on the water surface with the buoyancy tank and flows along with the water surface, and when the unmanned aerial vehicle and the buoyancy tank flow along with the water flow together, the flying speed of the unmanned aerial vehicle is the flowing speed of the water flow, and the flying speed of the unmanned aerial vehicle is the speed of the water flow. And an additional flow velocity measuring device is not needed. And the unmanned aerial vehicle and the buoyancy tank are in direct contact with water flow, so that measured data are more accurate.

The invention relates to the technical field of unmanned aerial vehicle obstacle avoidance, in particular to an unmanned aerial vehicle autonomous obstacle avoidance method and system based on visual SLAM, and the method comprises the steps: obtaining multi-source sensor data of an unmanned aerial vehicle, the multi-source sensor data at least comprises load data, visual image data, inertial vibration data and system energy state data; constructing an obstacle environment map according to the visual image data and the inertial vibration data; determining a maneuvering energy index according to the system energy state data and the load data; and determining an obstacle avoidance path based on the current flight speed of the unmanned aerial vehicle, the load data and the maneuvering energy index, and generating an emergency obstacle avoidance instruction based on the obstacle avoidance path and an obstacle environment map, so as to control the unmanned aerial vehicle to realize emergency obstacle avoidance according to the emergency obstacle avoidance instruction. The method has the effect of improving the obstacle avoidance precision and stability of the unmanned aerial vehicle under the high-load condition.

The invention discloses an unmanned aerial vehicle pay-off device and a using method, and belongs to the technical field of power transmission line construction, the unmanned aerial vehicle pay-off device comprises an unmanned aerial vehicle, a central control unit, a pay-off device, a tension pay-off device, a guide rope and an identification device, the pay-off device is installed at the bottom of the unmanned aerial vehicle, and the pay-off device is connected with one end of the guide rope in a clamping mode; the other end of the guide rope is connected with a cable unwound by the tension pay-off device, the tension pay-off device is arranged on the ground, the pay-off speed of the tension pay-off device is controlled to be consistent with the flight speed of the unmanned aerial vehicle, so that the guide rope and the cable are in a straightened state, and the situation that pay-off is affected by too large sag of the cable is avoided; the unmanned aerial vehicle, the pay-off device and the tension pay-off device are all in signal connection with the central control unit, operation of workers is facilitated, accurate positioning of the unmanned aerial vehicle in complex terrains is ensured, and meanwhile, an identification device is arranged on a tower where a cable needs to be installed so that the unmanned aerial vehicle can accurately recognize the preset position.

The invention provides an unmanned aerial vehicle deployment and transmission method, electronic equipment and a readable storage medium. The method aims at a scene that a plurality of unmanned aerial vehicles are used for providing transmission services for a plurality of robots which are distributed in a certain area and move randomly. According to the scene, an unmanned aerial vehicle deployment and task transmission optimization model which takes maximization of the total transmission success number as a target and takes the flight speed, the safety distance and the like of the unmanned aerial vehicle as constraints is disclosed, and an optimal unmanned aerial vehicle deployment and task transmission scheme is solved by using simulated annealing and a Hungary algorithm. In addition, the invention further discloses a scheme for solving the optimal number of the unmanned aerial vehicles by using a tripartite search algorithm and aiming at maximizing the weighted value of the expected total transmission success number and the deployment cost to deploy an unmanned aerial vehicle number optimization model constrained by the total budget.

The invention relates to the technical field of unmanned aerial vehicle image processing, in particular to an aerial photography rail pushing zooming method and system. The method comprises the steps that the fixed acceleration of the unmanned aerial vehicle is calculated according to the obtained initial shooting distance between a shooting device and a shooting object, a specified frame rate, a specified frame zoom ratio and a progress judgment threshold value, and the shooting device is arranged on the unmanned aerial vehicle; and when a video is shot at a specified frame rate and the shooting device is controlled to carry out digital zooming on the shot video according to a specified frame zooming ratio, the unmanned aerial vehicle is controlled to fly away from a shot object in a uniformly accelerated manner along the optical axis direction of the shooting device according to the fixed acceleration starting from the initial shooting distance, so that aerial photography push-rail zooming is realized. According to the invention, the flight control difficulty of the unmanned aerial vehicle is simplified, more flexible digital zooming and flight speed control matched with the digital zooming can be realized, so that the automatic management of rail pushing zooming is realized, the video shooting quality is improved, and the method can be widely applied to multiple fields such as film shooting and advertisement production.

The utility model relates to the technical field of unmanned aerial vehicles, in particular to an unmanned aerial vehicle support adjusting mechanism which comprises an unmanned aerial vehicle chassis, a fixing block is fixedly connected to the surface of the unmanned aerial vehicle chassis, a first support is rotationally connected to the surface of the fixing block, and a second support is rotationally connected to the surface of the fixing block. A dislocation block is fixedly connected to the surface of the first support, a first connecting plate is rotatably connected to the surface of the dislocation block, an air cylinder is fixedly connected to the surface of the first connecting plate, a second connecting plate is fixedly connected to a piston rod of the air cylinder, and the second connecting plate is rotatably connected to the surface of the second support. The angles of the first support and the second support at the bottom of the chassis of the unmanned aerial vehicle are adjusted in the rotating process, so that the first support and the second support can be folded and stored at the bottom of the chassis of the unmanned aerial vehicle, the wind resistance of the unmanned aerial vehicle is reduced, and the unmanned aerial vehicle is prevented from consuming more electric power and reducing the flying speed during flying.

This utility model discloses an adjustable two-dimensional tail nozzle, belonging to the field of two-dimensional tail nozzle technology; it includes a connected engine and an adapter casing. A servo is provided on one side of the adapter casing. The output side of the adapter casing consists of a rectangular opening formed by two oppositely arranged fixed plates and two oppositely arranged adjusting plates. A power arm is provided at the output end of the servo. The right end of the power arm is connected to two parallel first connecting rods by a pin shaft. The other ends of the two first connecting rods are respectively connected to two second connecting rods. It can be applied to small afterburning turbojet engines to improve the flight speed of UAVs. Its structure is simple. The synchronous opening and closing movement of the adjusting plates is achieved through a single servo drive source, reducing the control difficulty, realizing engine thrust adjustment, reducing the number of structures, and making it lightweight, highly reliable, and low in cost. By setting a support rod on the outside of the adjusting plate, the adjusting plate can be limited. The structure is simple and the use effect is good.

An ultra-high-speed helicopter with stowed single-blade coaxial rotors is provided and relates to the technical field of aircrafts. The ultra-high-speed helicopter includes a fuselage. Wings and tails can be arranged on the fuselage, respectively. Tail blades can be arranged at a tail end of the fuselage. A rotor mechanism can be arranged on a top of the fuselage. The rotor mechanism includes rotors. The rotor mechanism can drive the rotors to be stored in a rotor storage cabin of the fuselage. When the helicopter flies at high speed, the rotors stop working, and tail blades provide propulsive force and the wings provide lift force, so that the defects in the aerodynamic characteristics of the rotors are avoided during high-speed flight. In addition, the rotors can be retracted and stowed in a fuselage to further reduce drag and increase the maximum flight speed.

The application discloses a kind of unmanned aerial vehicle autonomous landing method and system based on vision, realize the dynamic landing pad autonomous landing of unmanned aerial vehicle under unknown environment;Adopt the feature extraction and state estimation method of unmanned aerial vehicle vision sequence, according to the center position of the dynamic landing pad, motion direction, motion speed and other features extracted from processed visual information, estimate the relative pose of itself and dynamic landing pad, predict dynamic landing pad space-time state and motion behavior;According to the perception result of unmanned aerial vehicle, directly generate the control instruction of the motion direction, lifting height, flight speed and other of unmanned aerial vehicle, realize the dynamic landing pad landing task of unmanned aerial vehicle under GPS denial unknown environment;The method combines the multi-control network cooperative control based on deep reinforcement learning and target space-time state prediction method, so that unmanned aerial vehicle autonomously completes the dynamic landing pad landing task of unmanned aerial vehicle under unknown environment without human intervention, greatly improves the autonomy and intelligence of unmanned aerial vehicle.

The invention discloses an unmanned aerial vehicle control method for territorial space planning, and relates to the technical field of unmanned aerial vehicle control, and the method comprises the steps: obtaining an attitude angle anomaly coefficient data set, a flight speed data set and a flight height data set of an unmanned aerial vehicle, calculating a flight stability coefficient data set of the unmanned aerial vehicle, and sending out a flight anomaly analysis instruction; after the flight anomaly analysis instruction is received, calculating a flight anomaly index of the unmanned aerial vehicle, and sending out a flight anomaly early warning of the unmanned aerial vehicle; after a flight abnormity early warning of the unmanned aerial vehicle is received, calculating an overlapping degree coefficient and an image quality coefficient of the image data, and calculating a sampling abnormity index of the image data; according to the method, the flight anomaly index of the unmanned aerial vehicle and the sampling anomaly index of the image data are acquired, the land data acquisition anomaly index is calculated, the re-flight position of the unmanned aerial vehicle is marked, and the unmanned aerial vehicle is controlled to perform data acquisition on the re-flight position again, so that the data anomaly position can be accurately positioned, and the accuracy and integrity of land data acquisition are ensured.

The utility model relates to the technical field of ore blasting, and particularly discloses an ore blasting flying stone prevention device which comprises a top plate and a base, a reinforcing plate is arranged between the top plate and the base, inclined baffles are arranged on the left side and the right side of the reinforcing plate, the upper ends of the inclined baffles are fixedly connected with the top plate, and multiple sets of hanging rod structures are arranged on the sides, away from the reinforcing plate, of the inclined baffles. A plurality of first tires are hung on the hanging rod structure, and the first tires are stacked; the top of the top plate is provided with a plurality of second tires which are stacked, and the top of the top plate is provided with a positioning rod set used for limiting shaking of the second tires. The inclined baffle can block broken stones coming from the front, the top plate can block the broken stones falling from the upper portion, when the inclined baffle is impacted by flying stones, the tires can buffer the flying stones coming from impact, the flying speed and harm of the flying stones are reduced, the reliability of the inclined baffle is improved, and the tires are assembled in a hanging mode, so that replacement and maintenance are convenient for workers.

The embodiment of the invention provides an unmanned aerial vehicle self-adaptive telegraph pole insulating paint spraying method and device, and the method comprises the steps that in the spraying operation process, operation environment parameters are obtained in real time, the operation environment parameters are input into a pre-trained reinforcement learning model, and the operation environment parameters comprise the wind speed, the paint temperature and the telegraph pole surface coating state; the reinforcement learning model generates and outputs a pumping pressure adjusting instruction and a flight control instruction in real time according to the input environmental parameters; and according to the pumping pressure adjusting instruction and the flight control instruction, a spraying mechanism is synchronously controlled to conduct atomization spraying at the target pumping pressure, and the unmanned aerial vehicle is controlled to fly along the spraying object at the target flight speed till the thickness of the coating on the surface of the telegraph pole meets the target thickness. The stability and the consistency of the spraying quality are improved, and the coating thickness error is controlled within a preset range; the coating waste caused by environmental fluctuation is greatly reduced, the working efficiency is improved, manual high-altitude operation is avoided, and corresponding safety risks are thoroughly eliminated.

The application relates to the technical field of unmanned aerial vehicle control, and discloses an unmanned aerial vehicle endurance prediction method and system, which comprises the following steps: setting a dynamic sensing area based on a flight speed direction and a body, and cooperatively collecting sensing data sets; performing multi-source space-time registration on laser point clouds and millimeter wave echoes based on pose information to obtain a fusion candidate point set; performing state classification identification and effective target condensation on the candidate point set to obtain a current obstacle target; performing space parameter solving and time sequence stabilization processing on the current target to generate a structured obstacle target; judging a safety corridor according to a flight path and a work line direction to obtain a forward passing state; and finally, calculating a risk level by comprehensively considering the forward passing state and motion characteristic parameters, mapping the risk level to a risk action mapping strategy, and outputting corresponding control instructions; the application can improve the efficiency of unmanned aerial vehicle endurance prediction.

The unmanned aerial vehicle pod retracting and releasing mechanism comprises a vehicle body, a rectangular groove is formed in the bottom end of the vehicle body, a door closing mechanism covering the rectangular groove is arranged at the bottom of the vehicle body, two fixing boxes are vertically and fixedly connected to the inner wall of the bottom end of the vehicle body, and lead screws are vertically and rotationally connected to the inner walls of the bottom ends of the two fixing boxes correspondingly; the tops of the two lead screws are rotationally connected with the same fixing plate, the two lead screws both penetrate through the fixing plate, a cabin is arranged below the fixing plate, and a movement mechanism which rotates firstly and then puts down the cabin is arranged in the machine body. According to the unmanned aerial vehicle pod, the rectangular groove in the bottom of the unmanned aerial vehicle is covered, a large amount of wind is prevented from entering the unmanned aerial vehicle body in the flying process of the unmanned aerial vehicle, the influence on the flying speed of the unmanned aerial vehicle is reduced, and therefore the working efficiency of the unmanned aerial vehicle is improved, the unmanned aerial vehicle pod is convenient to fold and unfold, and the space of the unmanned aerial vehicle is saved.

The present invention relates to the technical field of airport FOD detection, and more particularly to a radar- and camera-based unmanned aerial vehicle (UAV) FOD detection system, comprising a background central radar, a camera, and a detection UAV. The present invention optimizes radar detection when the UAV is equipped with the radar and camera. First, range migration correction is performed on the radar echo signal to compensate for interference with radar detection (echo) caused by the flight speed of the UAV equipped with the radar. Simultaneously, a secondary confirmation is performed on the radar detection. By comparing a large amount of data, secondary screening of FOD detection is performed, reducing invalid detections, increasing detection accuracy, and saving detection time. A fixed-focus camera is used to perform detailed identification of suspected FOD objects by category, size, risk level, etc. after preliminary radar detection, thereby improving detection efficiency and accuracy.

The invention provides a satellite navigation-free unmanned aerial vehicle position estimation method capable of predicting a flight path. The method comprises the following steps: S1, obtaining a detection image of a front downward view field of an unmanned aerial vehicle; s2, performing multi-source image fusion processing on the detection image to obtain a fused image; s3, perspective projection transformation is carried out on the fused image, feature matching is carried out on the fused image and DEM data, and feature point information is obtained; and S4, determining the current coordinates of the unmanned aerial vehicle based on the relative height of the unmanned aerial vehicle relative to the ground, the altitude of the unmanned aerial vehicle, the flight speed of the unmanned aerial vehicle and the feature point information, wherein the current coordinates are used for predicting the flight path of the unmanned aerial vehicle. Compared with the prior art, the non-satellite navigation unmanned aerial vehicle position estimation method capable of predicting the flight path can estimate the position coordinates of the unmanned aerial vehicle without satellite navigation, so that the current coordinates of the unmanned aerial vehicle are obtained, and flight path prediction and autonomous navigation are facilitated; a fault protection mechanism is provided for the unmanned aerial vehicle when the satellite navigation signal is lost, and smooth flight tasks of the unmanned aerial vehicle are guaranteed.

The invention relates to the technical field of gliding guidance of intelligent unmanned aerial vehicles, in particular to a gliding guidance control method and system based on satellite navigation, and the method comprises the steps: determining an actual attack angle of an intelligent unmanned aerial vehicle; determining the flight stability of the intelligent unmanned aerial vehicle at the current moment by combining the difference between the actual flight speeds at all adjacent collection moments based on the extreme distribution condition of the actual flight speeds at all collection moments; determining the lift force change rate of the intelligent unmanned aerial vehicle at the current moment; and determining an ideal attack angle based on the flight stability, the lift force change rate and the actual attack angle, and regulating and controlling the attack angle in gliding guidance in combination with a PID control algorithm. According to the method, the actual flight data and the simulated flight data are comprehensively analyzed, so that the attack angle control precision in the gliding guidance process of the intelligent unmanned aerial vehicle is improved.

The invention provides a flying net projectile. The flying net projectile comprises a head shell case, a tail shell case and a flying net assembly. The head cartridge case and the tail cartridge case are buckled to form a constraint cavity, and the windward side of the head cartridge case is provided with an air hole array communicated with the constraint cavity; the flying net assembly comprises a flexible net piece and a plurality of traction elastic pieces, and the flexible net piece is connected with the traction elastic pieces through traction wires. The traction elastic pieces are distributed in the restraining cavity in a circumferential array mode, and an elastic element is arranged between every two adjacent traction elastic pieces. Wherein the head cartridge case and the tail cartridge case are separated under the compression of air flow entering the restraint cavity through the air hole array, and when the head cartridge case and the tail cartridge case are separated, the traction elastic pieces drive the flexible meshes to be opened under the elastic pushing action of the elastic elements. According to the flying net projectile provided by the invention, the separation opportunity of the head shell and the tail shell can be associated with the flying speed of the flying net projectile, so that the projectile structure can be greatly simplified, and the interception stroke and precision can be improved.

The invention provides a catapult kinetic energy measurement method and device, electronic equipment and a storage medium, and the method comprises the steps: inputting a print image generated by the impact of a catapult launched by a catapult and the bullet correlation information of the catapult into an improved target detection model, obtaining an imprint prediction frame and an imprint prediction category in an imprint image output by the improved target detection model; after the target area image in the print prediction frame is optimized, the actual print area is calculated according to the optimized target area image; calculating the kinetic energy of the catapult according to the mass of the catapult and the flight speed after launching, and calculating the unit area kinetic energy of the catapult according to the kinetic energy of the catapult and the actual print area; the improved target detection model is obtained through training by taking an imprint image sample and corresponding bullet correlation information as samples and taking an imprint category labeling result and an imprint frame labeling result in the imprint image sample as labels. According to the invention, rapid and accurate measurement of kinetic energy measurement is realized.