501 results about "Flight time" patented technology

The invention relates to a low-altitude logistics unmanned aerial vehicle path planning method, which comprises the following steps of 1, discretizing an urban low-altitude region into computable grid units, a dynamic-static obstacle classification modeling technology is combined to endow a static obstacle with a basic risk degree, a height attenuation factor is introduced to quantify the influence of a high-altitude obstacle on a low-altitude path, and a collision risk of a dynamic obstacle is dynamically evaluated through a time dimension risk degree prediction model; 2, based on an improved genetic algorithm, comprehensively considering flight time, height change, risk degree and dynamic risk cost through a multi-objective optimization objective function, and generating a globally optimal task allocation scheme; 3, generating a local optimal three-dimensional path considering meteorological conditions and dynamic obstacle influence by adopting an improved particle swarm algorithm; and 4, performing path planning to feed back actual flight time and energy consumption to task allocation for optimization.

The invention discloses a civil aircraft PHM modeling method based on cross-modal coupling, a medium and equipment, and belongs to the technical field of aircrafts. The method comprises the steps of S1, multi-modal data preprocessing: performing feature extraction and time-space / event alignment for three modalities of flight time sequence data, text data and image data, and laying a foundation for subsequent fusion modeling; s2, cross-modal feature fusion and holographic data sample construction: constructing a holographic data sample library covering the whole life cycle through cross-domain fusion and dynamic optimization; and S3, PHM physical-knowledge fusion comprehensive modeling: constructing a double-layer collaborative framework combining physical simulation and knowledge reasoning, and realizing controllable fusion of physical simulation and multi-modal knowledge. The problems that in the prior art, multi-source heterogeneous data alignment is difficult, physical mechanism and data driving fusion is insufficient, and model interpretability is poor can be solved.

The invention discloses a method and a system for processing route planning data for electric power line inspection. The method comprises the following steps: acquiring line distribution and topographic feature data; gridding the power network region, determining the patrol priority, and generating a region priority sequence; the overall patrol task is decomposed, a plurality of task subsets are generated, one task is allocated to each unmanned aerial vehicle, and each task subset comprises an initial position and a target line section; generating an initial route path based on the topographic features; comprehensively analyzing all initial paths, identifying potential airspace intersections and performing conflict prediction, and generating a conflict-free route path set by performing height hierarchical adjustment on related paths; and calculating predicted flight time and energy consumption of each unmanned aerial vehicle, redistributing boundary tasks according to a load balancing principle, and finally generating a balanced multi-unmanned aerial vehicle cooperative route scheme. According to the method, the safe and efficient multi-machine collaborative inspection route can be automatically generated through systematic task decomposition, conflict prediction and load balancing optimization.

An autonomous flying device achieving a large payload and a long continuous flight time and also accurately adjust position and orientation while flying. The device includes: a main rotor and the like that provide main thrust; a sub rotor and the like that controls the orientation; an engine that generates energy for rotating the main rotor and the like and the sub rotor and the like; and an arithmetic control device that controls rotation of the sub rotor and the like. Also, the main rotor and the like are rotated by being drivingly connected to the engine, whereas the sub rotor and the like are rotated by motors driven by electric power generated from generator and the like operated by the engine. Further, when orientation control to tilt the fuselage is performed, the arithmetic control device increases the output distribution ratio of the sub rotor to above the output distribution ratio of the sub rotor when hovering is performed.

The invention belongs to the technical field of air traffic management, and relates to a flight time adjustment management method and system in a special scene. According to the method, the flight release priority sequence is constructed, the airport taxiway network topology and the dynamic limitation information are combined, the taxiing path is planned, the space-time conflict is detected, and the dynamic adjustment of flight ground operation and the coordination verification of the runway access time window are realized. The problems of frequent flight ground taxiing path conflicts, low scheduling efficiency and difficulty in accurate take-off time control in special scenes are solved, the safety and efficiency of airport ground operation are effectively improved, the flight taxiing time and the runway waiting time are reduced, the flight release sorting and the runway use plan are optimized, and the flight taxiing efficiency is improved. The flight scheduling cooperation capability in a complex operation environment is enhanced, and the orderliness and stability of flight operation are guaranteed.

The invention relates to the technical field of unmanned aerial vehicle cluster control, in particular to an unmanned aerial vehicle cluster control method and system, and the method comprises the steps: predicting the remaining flight time of an unmanned aerial vehicle cluster for safely arriving at a destination in a current carrying state; calculating a cluster energy consumption deviation degree according to the current energy consumption parameter, predicting the remaining endurance time of each unmanned aerial vehicle, and determining the minimum predicted endurance time; dynamically generating a safe flight time threshold according to the minimum predicted endurance time and a preset safety margin; if the remaining flight time is smaller than the safe flight time threshold value, a cooperative control instruction is generated according to the offset, the offset speed and the cluster energy consumption deviation degree; and distributing the cooperative control instruction to the corresponding unmanned aerial vehicle in the unmanned aerial vehicle cluster. And the flight endurance crisis caused by non-uniform energy consumption in the irregular article carrying process is effectively solved.

The invention provides an unmanned aerial vehicle flight path dynamic planning method and system, and relates to the technical field of flight path planning, and the method comprises the steps: obtaining the starting and ending points of the flight of an unmanned aerial vehicle, and planning an initial unmanned aerial vehicle flight path based on the starting and ending points of the flight of the unmanned aerial vehicle and a preset constraint; constructing an unmanned aerial vehicle flight environment model based on a preset flight area map, the elevation information and the obstacle information; route optimization is carried out based on the initial unmanned aerial vehicle flight route and a flight environment model, and an unmanned aerial vehicle initial obstacle avoidance route is generated; the unmanned aerial vehicle initial obstacle avoidance route is optimized based on a preset iterative optimization model, and an optimized unmanned aerial vehicle obstacle avoidance route is obtained; and updating the optimized unmanned aerial vehicle obstacle avoidance route to the initial unmanned aerial vehicle flight route to generate a final unmanned aerial vehicle flight route. According to the invention, the flight time and cost are saved, the adaptability to the environment, especially the urban complex environment, is enhanced, and the safety is guaranteed.

The invention relates to a multi-unmanned aerial vehicle maritime cooperative reconnaissance method based on an Archimedes algorithm and hierarchical scheduling, and the method comprises the steps: defining a patrol task region and task targets, and constructing a topological model of an unmanned aerial vehicle cluster for each task target; according to the cooperation characteristic of the unmanned aerial vehicle cluster, Archimedes patrol path planning is carried out on various unmanned aerial vehicles; based on the performance of the unmanned aerial vehicle, factors such as path length, flight time, unmanned aerial vehicle scanning range and search efficiency are comprehensively considered, and the path of the unmanned aerial vehicle is optimized, so that the unmanned aerial vehicle has relatively high execution efficiency and stability; when the leader unmanned aerial vehicle finds a target during patrol, the cluster dispatches the investigation unmanned aerial vehicle to perform a tracking task; and the investigation data is returned to the command center, and next task planning is carried out. The cooperative reconnaissance capability of the unmanned aerial vehicle cluster in complex tasks can be effectively improved.

The invention discloses a power line anomaly detection method and system based on an unmanned aerial vehicle. The method comprises the steps that a server analyzes a power line detection request to obtain a detection area and a detection time period; planning an initial detection track, generating a power line detection instruction based on the initial detection track, the detection area and the detection time period, and issuing the instruction to the unmanned aerial vehicle; the unmanned aerial vehicle executes an inspection task in the electronic fence, the initial detection track is dynamically corrected in the inspection process, and a flight time sequence image is collected; analyzing the flight time sequence image through a line anomaly detection model, and outputting a line anomaly detection result; an actual detection track is recorded, and abnormity marking is carried out on the actual detection track; and recording, encrypting and uploading an inspection log to the server. The method has the advantages that the detection efficiency, the intelligent level and the safety management capability of power line anomaly detection are greatly improved.

The embodiment of the invention provides a transducer echo line sequence test method and a transducer echo line sequence test device, and the method comprises the steps: enabling a detection surface and a horizontal plane to form a first angle in an echo detection state, comparing waveform data of feedback signals obtained by reflecting the ultrasonic signals emitted by the plurality of test array elements through the detection surface with preset qualified data to determine a performance result of the transducer; in the line sequence detection state, a second angle is formed between the detection surface and the horizontal plane, and the actual flight time difference value of each adjacent test array element in the plurality of test array elements is determined according to waveform data of feedback signals obtained by reflecting ultrasonic signals emitted by the plurality of test array elements through the detection surface, and according to a comparison relation between a difference value between the actual flight time difference value and the theoretical flight time difference value and a preset threshold value, whether welding of each test array element is correct or not is determined. Therefore, an echo performance detection function and a multi-array element line sequence detection function can be integrated.

The invention discloses a heterogeneous unmanned aerial vehicle cluster task allocation and region boundary point joint planning method. The method comprises the following steps: constructing an unmanned aerial vehicle motion model; constructing a collaborative detection distribution income measurement index, an estimated detection time difference measurement index and an energy consumption measurement index which take unmanned aerial vehicle task node selection parameters as optimization variables, and taking the weighted sum of the three indexes as a measurement index of collaborative detection task efficiency; establishing a heterogeneous unmanned aerial vehicle cluster task allocation and region boundary point joint planning model by taking given unmanned aerial vehicle voyage, endurance, effective communication distance and inter-vehicle anti-collision distance limitation as constraint conditions and taking minimization of a heterogeneous unmanned aerial vehicle cluster cooperative detection task efficiency cost function as an optimization target; and solving the optimization model by combining an interior point and an improved Hungary algorithm. According to the method, optimal distribution of the heterogeneous unmanned aerial vehicle cluster task area, the base takeoff point and the area boundary entry point is realized, and the heterogeneous unmanned aerial vehicle cluster cooperative detection performance is effectively improved.

The invention relates to the technical field of ultrasonic flow measurement, and discloses a relative flight time estimation method based on an ultrasonic flowmeter, and the method comprises the steps: carrying out the time domain alignment of uplink and downlink echo signals through prior absolute flight time, and preventing phase cycle skipping; carrying out FFT (Fast Fourier Transform) and frequency domain conjugate multiplication on the signal, and extracting amplitude and phase information; and a cost function is constructed by using frequency spectrum amplitude weighting, residual delay is estimated through least square fitting, and finally high-precision relative flight time is obtained. According to the method, correlation operation is realized in the frequency domain, the calculation complexity is remarkably reduced, the estimation precision and the anti-noise capability are improved, and the method is suitable for an embedded low-power-consumption system.

An autonomous flying device achieving a large payload and a long continuous flight time and also accurately adjust position and orientation while flying. The device includes: a main rotor and the like that provide main thrust; a sub rotor and the like that controls the orientation; an engine that generates energy for rotating the main rotor and the like and the sub rotor and the like; and an arithmetic control device that controls rotation of the sub rotor and the like. Also, the main rotor and the like are rotated by being drivingly connected to the engine, whereas the sub rotor and the like are rotated by motors driven by electric power generated from generator and the like operated by the engine. Further, when orientation control to tilt the fuselage is performed, the arithmetic control device increases the output distribution ratio of the sub rotor to above the output distribution ratio of the sub rotor when hovering is performed.

The invention discloses an airship type unmanned aerial vehicle inspection system and inspection method, and belongs to the field of inspection unmanned aerial vehicles. The system comprises a laser radar, an image acquisition device, an airship capsule filled with helium, a standby safety airbag, a communication module and a ground control center, in the method, the ground control center sets an inspection path and issues the inspection path, and the unmanned aerial vehicle flies according to a preset path. During fault detection, the high-definition camera collects images to recognize line cracks and broken strands, the thermal infrared imager monitors the joint temperature, the gas sensor detects abnormal gas, and multi-source data fusion assists in defect positioning. The routing inspection takes a starting point-terminal point connecting line of a power transmission line as a reference, identifies main obstacles and surrounding nodes to perform global planning, performs key routing inspection on a risk area in combination with historical data, and initializes and guides a flight direction through a Q value to reduce invalid exploration. The four-rotor unmanned aerial vehicle solves the problems of short flight time and poor stability of a four-rotor unmanned aerial vehicle, improves the inspection stability and cruising ability, and improves the inspection efficiency of a power transmission line and the reliability of a power system.

The invention relates to a multi-domain collaborative ocean emergency rescue method, which solves the technical problems of short endurance, small operation range and low recognition accuracy of persons in distress when an unmanned aerial vehicle or an unmanned ship or an underwater robot is adopted to carry out a search and rescue task in the prior art, and combines the unmanned aerial vehicle, the unmanned ship and the underwater robot for mutual cooperation. The unmanned aerial vehicle carries out investigation traversal in the air to find a search and rescue target, the unmanned aerial vehicle gets close to the search and rescue target and sends the position information of the target to the control center, the unmanned ship sails to the position of the target, the at least two underwater robots are transferred along with the unmanned ship, and the unmanned ship controls the at least two underwater robots to work cooperatively. The method can be widely applied to deep ocean emergency rescue, and an'air-sea-submerged 'multi-domain cooperative new normal form is formed.

The invention discloses a communication and inductance integration method for a communication waveform in a high mobile environment. The method comprises the following steps: constructing a UAV-ISAC system based on AFDM; constructing a model of a communication signal sent by the UAV to the base station and a model of an echo signal received by the UAV and perceived by a ground user; determining the signal-to-noise ratio of each time slot communication part link and the signal-to-noise ratio of a sensing part echo based on a communication signal model and an echo signal model, thereby determining the capacity of each time slot communication link and the sensing mutual information amount of each user, and determining the total sensing mutual information amount, the total communication capacity of the UAV in the whole flight time, and the total consumed energy; constructing a total optimization problem by using the total communication capacity and the total consumed energy, and decomposing the optimization problem into three sub-problems of user scheduling optimization, transmitting power optimization and UAV trajectory optimization; and by constructing different constraint conditions and solving the three sub-problems, an optimization result is obtained. According to the invention, the energy efficiency of the UAV-ISAC system based on AFDM can be maximized.

In a method of determining position information of a client device, reference devices include a master device and target devices. Target device clocks are synchronized with the master device clock based on one-way message information. For each of the target devices a first time correction is determined based on a two-way ranging message. A first message transmitted from / to the respective target device is timestamped by several target devices corrected for the first time correction. Position information of the client device is determined based on time-of-flight information of the first messages in which the first timestamp is corrected for the first time correction. As a result, the timestamps of the first messages applied by the target devices will experience a same offset error. Consequently, the corresponding pseudo-ranges will all have the same error. Typically, positioning algorithms are insensitive to constant errors in the pseudo-ranges or can easily deal with them.

A time of flight (TOF) ranging system includes multiple emitters, each emitting a signal whose intensity, amplitude or polarization is modulated by a corresponding delayed modulation signal. Each delayed modulation signal is a delayed version of a time varying multi-valued modulation signal, the amount of delay being determined by a spatial position of the emitter and direction of a target point on the target. The signal reflected by the target is correlated with the original modulation signal to generate an output having a peak representing the TOF to the target point. The same process is performed to detect other target points. Another TOF ranging system includes one emitter and multiple detectors; the signal from each detector is delayed in a similar manner and their sum is correlated with the original modulation signal to generate an output representing TOF. Yet another TOF ranging system includes multiple emitters and multiple detectors.

The invention relates to the technical field of urban low-altitude flight control, in particular to a low-altitude aircraft path planning and dynamic adjustment method for urban low-altitude logistics. Constructing a dynamic evaluation model of the flight risk factor R based on the urban three-dimensional environmental parameters; planning the path of the aircraft by adopting a multi-objective optimization algorithm, and determining an optimal path; dynamically adjusting paths by using an environment prediction model and a reinforcement learning algorithm: constructing a conflict graph between paths of each aircraft, and constructing a path collaborative optimization model according to path cost, energy consumption, flight time, path conflict and formation collaborative income; and outputting an optimized path set through the path collaborative optimization model, and generating a formal deployment scheme of multi-aircraft path collaborative scheduling. Compared with an existing static optimization and single path scheduling method, the method has the advantages that the path planning precision, the dynamic response capability, the multi-aircraft cooperation efficiency and the complex airspace adaptability are remarkably improved.

To provide a new technique for dynamically and efficiently operating an arrival and departure field when operating the number of unmanned aircrafts exceeding the number of simultaneous arrivals and departures at the arrival and departure field.SOLUTION: A transport control system causes a plurality of unmanned aerial vehicles to sequentially fly back and forth from a predetermined transport start point along flight routes set for the respective unmanned aerial vehicles, thereby transporting the unmanned aerial vehicles to respective given transport destinations. The transport control system repeatedly executes prediction of a predicted return time of each unmanned aerial vehicle to the transport starting point, and adjusts a flight time along a flight route of an unmanned aerial vehicle that satisfies a predetermined congestion condition based on a temporal relationship of the predicted return time, thereby adjusting the return time and adjusting the congestion.SELECTED DRAWING: Figure 3

The invention relates to a target guidance-oriented multi-unmanned aerial vehicle task planning and cooperative positioning method and system, and the method comprises the steps: building an optimized pairing relation between multiple unmanned aerial vehicles and a cluster target through the cooperative scheduling of a multi-unmanned aerial vehicle system and a depth traversal method; optimizing a target guiding area by combining target tracking, laser irradiation and threat avoidance; planning a flight path satisfying flight time, speed and threat avoidance based on an RRT method, superposing a minimum separation distance constraint to ensure the safety of a flight path interval, and optimizing the length of the flight path through a Dubins curve; a positioning model is constructed, the formation with more than three machines uses multi-machine laser ranging information, and the double-machine formation uses ranging and angle measurement information to carry out target positioning; calculating target coordinates by adopting a total least square method; for multiple targets in the photoelectric image, selecting a proper image for positioning according to target distribution, and calculating coordinates by combining collinear positioning and adjustment; according to the invention, the target positioning precision of multiple unmanned aerial vehicles is improved.

Systems and methods for mitigating time of flight interference are provided. Based on a determination that time of flight interference may occur or is occurring at a victim base station, a node of a non-terrestrial network is identified. Based on the determination and the identification, a victim UE connects to the node of the non-terrestrial network. In aspects, the victim UE forms an uplink connection with the node of the non-terrestrial network while maintaining a downlink connection with the victim base station. In other aspects, the victim UE forms a complete connection with the node of the non-terrestrial network.

The invention discloses a tension porcelain insulator detection device based on an unmanned aerial vehicle, and belongs to the field of power detection devices. The rotation detection assembly is arranged at the bottom of the unmanned aerial vehicle body, and the rotation detection assembly is mainly used for carrying out range rotation detection on the tension porcelain bottle; the rotation detection assembly comprises a first motor, a connecting rod and a second motor, the first motor is fixedly installed at the top of the unmanned aerial vehicle body, the output end of the first motor slidably penetrates through the top of the unmanned aerial vehicle body and extends to the lower portion, and the output end of the first motor is fixedly connected with a first rotating rod; through the effect of the rotary detection assembly, wide-angle coverage can be realized, the tension porcelain insulator can be detected in a range, the porcelain insulator does not need to be independently detected by an unmanned aerial vehicle during detection, collision possibly caused by frequent flight of the unmanned aerial vehicle is avoided, the endurance time is shortened, and the coverage range of detection operation is enlarged.

The invention relates to the technical field of aircraft navigation, and discloses an aircraft return path construction method based on visual intelligence. According to the method, a flight environment multi-view image sequence is collected through an airborne vision sensor, and vision observation data with a unified timestamp and space coordinates are generated through space-time alignment processing; calculating a motion vector field of the aircraft relative to a ground reference object based on continuous inter-frame optical flow characteristics in the data, and establishing a three-dimensional environment kinematics model by combining attitude data of the inertial measurement unit; reversely deducing a current flight path by using the model, extracting a historical path key waypoint set, and constructing a return path initial topology network according to the spatial distribution density of the historical path key waypoint set; carrying out dynamic weight distribution on a network node connection relationship, and generating a wind disturbance resistance candidate return path set in combination with a real-time meteorological wind field intensity parameter; and evaluating the candidate set by using a multi-objective optimization algorithm, and outputting an optimal return path meeting a fuel consumption threshold value and a flight time constraint.

This invention relates to a vision simulation method, system and device based on flight conditions, which provides a more natural and continuous vision switching effect and enhances the realism of the simulated flight. [Solution] The method includes obtaining simulation parameters for the current simulated flight, including flight time, visibility parameters in the simulated environment, and the attenuation rate of the projector; dividing the flight time into multiple sections, and calculating and obtaining the brightness percentage to be projected by the projector in different sections based on the different sections in combination with the visibility parameters and the attenuation rate; controlling the brightness percentage of the projected vision of the projector and tuning the color configuration parameters of the color wheel based on the flight state, thereby realizing the simulation of the flight state and vision.

The invention provides an amphibious posture self-switching power system and an amphibious wheel-foot mechanical dog, and the self-switching power system comprises a motor assembly which outputs power through a transmission shaft; the wheel assembly is provided with a second transmission disc with a plurality of second sliding inclined holes; the first transmission disc is provided with a plurality of first sliding inclined holes, the first transmission disc sequentially and annularly sleeves the transmission shaft, and the second sliding inclined holes and the first sliding inclined holes are coaxially communicated to form output posture switching sliding grooves for transmission sliding pins to slide; when the transmission sliding pin leaves the first sliding inclined hole under the action of gravity, the first transmission disc and the second transmission disc are decoupled; when the transmission sliding pin enters the first transmission disc under the action of gravity, the first transmission disc drives the second transmission disc to coaxially rotate. Output modes can be automatically switched between the flight attitude and the walking attitude based on the sliding stroke of the transmission sliding pin under gravity, the self weight is reduced, the endurance time is prolonged, and especially the endurance time of the flight attitude is greatly prolonged.

The invention relates to the technical field of unmanned aerial vehicles, in particular to a shared unmanned aerial vehicle distribution method and system based on route planning, and the method comprises the following steps: collecting data related to an unmanned aerial vehicle distribution task, including geographic information and climate condition data, associating a place coordinate with a time label through geocoding, and carrying out the data arrangement according to a time sequence, and generating a task serialization list. According to the method, the accuracy of task planning is remarkably improved by utilizing geographic information and climate condition data, so that the unmanned aerial vehicle distribution can more effectively cope with the problems of different geographic environments and climate changes, and accurate sorting of task priorities is realized by dynamically analyzing the emergency degree, the customer level and the expected delivery time of the tasks; the service pertinence and the task response speed are improved, the flight time and the energy consumption prediction are combined, the resource allocation is optimized, the cost effectiveness of the flight plan is improved, and the flight route and the task allocation are dynamically adjusted by monitoring the environment change and the state of the unmanned aerial vehicle in real time.

The invention discloses an energy consumption optimization path planning method and system for unmanned aerial vehicle routing inspection, and relates to the technical field of unmanned aerial vehicle routing inspection path planning, and the method comprises the steps: calculating an evaluation function during node expansion in each step: a heuristic function represents the accumulated cost from a starting point to a current node, and a heuristic function represents the estimated cost from the node to a target point; the heuristic function is composed of a distance component and an energy consumption component, and the expression of the heuristic function is as follows: the linear distance from the current node to the target node, the minimum additional energy consumption estimated according to the height change and the flight resistance, and the weight coefficient; the improved heuristic function can preferentially avoid a high-energy-consumption area, a flatter and smoother air route is selected, and accumulated energy consumption and flight time of a global path are remarkably reduced; meanwhile, due to the introduction of the multi-dimensional cost, the global planning is more accurate and reliable, and the search efficiency of the algorithm in a complex three-dimensional environment is improved.

The invention discloses a low-altitude unmanned aerial vehicle path planning method and system based on deep learning. The method comprises the following steps: acquiring flight state information and environment data of an unmanned aerial vehicle in real time; task priority calculation: calculating the task priority according to the unmanned aerial vehicle state information in combination with the task emergency degree and the task type; based on collaborative decision-making of deep reinforcement learning, decision-making is carried out on task allocation and flight paths through a deep learning algorithm in combination with unmanned aerial vehicle state and environment data and task priority information; planning an optimal flight path for the unmanned aerial vehicle according to the intelligent decision comprehensive environment data; the flight path is a discrete point set path planning target which minimizes the flight time on the premise of avoiding a no-fly zone and an obstacle; and in the process of executing the path planning by the unmanned aerial vehicle, when abnormality is detected, making a decision again, and performing path planning again until the unmanned aerial vehicle finally reaches the target position point.

The invention relates to a resource orchestration method and device for a collaborative network, equipment, a storage medium and a program product. Comprising the following steps: constructing an optimization model taking maximization of total satisfaction, minimization of service duration and minimization of energy consumption of an unmanned aerial vehicle as targets; the total satisfaction is the sum of the satisfaction of each target area, the service duration is the sum of the sensing duration, the transmission duration, the calculation time and the flight time corresponding to each target area, and the energy consumption of the unmanned aerial vehicle is the sum of the sensing energy consumption, the transmission energy consumption, the flight energy consumption and the hovering energy consumption corresponding to each target area; solving the optimization model under the constraint of a preset constraint condition to obtain a computing resource allocation strategy and a sensing communication strategy; comprise computing time, sensing duration, service sequences, flight heights and transmission power of various computing resources. By adopting the method, multi-target collaborative optimization is realized, namely, the service duration and the energy consumption of the unmanned aerial vehicle are minimized while the total satisfaction degree of the system is maximized.