231 results about "Flight altitude" patented technology

The invention discloses a method for generating an autonomous inspection orthoimage of an unmanned aerial vehicle, and relates to the technical field of unmanned aerial vehicle surveying and mapping and autonomous navigation. Global optimization of an air route is realized through a path optimization strategy fused by a genetic algorithm in combination with grid characteristics of an inspection area and image parameter constraints, and candidate waypoints are used as nodes; redundant waypoints are screened through leg smoothness factors, route complexity is reduced, a genetic algorithm takes flight height and waypoint spacing as constraints, a fitness function containing flight distance, turning times and overlapping rate is constructed, a global optimal path is found through population iteration, multi-target requirements are optimized and balanced, and it is ensured that the route meets the image acquisition precision requirement and also meets the requirement of image acquisition. The flight distance can be shortened, the turning frequency is reduced, the cruising ability of the unmanned aerial vehicle is adapted, efficient propelling of the inspection task is guaranteed, meanwhile, waypoint coordinates output through simulation directly adapt to a flight control system, and it is guaranteed that actual flight parameters are consistent with planning parameters.

The invention discloses a dense small target detection method for an unmanned aerial vehicle aerial photography scene, and belongs to the technical field of computer vision and target detection. In order to solve the problems of small target scale dynamic change and feature expression weakening caused by flight height change, imaging resolution difference and scene complexity in aerial photography of an unmanned aerial vehicle, the invention provides a detection framework fusing an attention scale selection (AGSS) module and a dynamic local self-attention (DPSA) module. The method specifically comprises the following improvements: (1) an AGSS module enhances the significance and discrimination ability of small targets in multi-scale features through global context modeling and a dynamic weight distribution mechanism; and (2) a DPSA module introduces a sparse selection mechanism in a channel dimension, and focuses computing resources on a channel sensitive to a small target, so that efficient and lightweight attention modeling is realized. The above modules cooperate with each other, so that high reasoning efficiency is maintained, and small target detection precision and robustness in a complex background, low illumination and dense target scene are significantly improved. Experimental results show that on typical unmanned aerial vehicle aerial photography data sets such as VisDrone-DET2019 and the like, the method is superior to an existing mainstream method in multiple indexes such as the average precision (mAP), the accuracy rate and the recall rate, especially has obvious advantages in the aspects of integrity and stability of small target detection, and has good practical application value and popularization prospects.

The invention relates to the technical field of unmanned aerial vehicle trajectory planning, in particular to a bidirectional tree random search method based on a complex environment node cost function, which comprises the steps of surveying obstacle data in a flight area and modeling, then introducing a target deviation strategy and a bidirectional search tree mechanism, and combining with an improved minimum cost method to obtain a random search result. Alternately expanding the two trees to generate an initial path, and integrating the path length, the obstacle distance and the flight height energy consumption by a cost function; and finally, pruning the initial path, removing redundant nodes, smoothing the trajectory by adopting a cubic spline interpolation method, ensuring curvature continuity, and generating an optimal path meeting the flight performance of the unmanned aerial vehicle. According to the invention, through an improved bidirectional minimum cost fast expansion random tree algorithm, dynamic association of obstacle constraint, target deviation and path cost in unmanned aerial vehicle path planning in a complex environment is represented, and a more efficient search convergence speed and better path quality are obtained. And rapid convergence and global optimization of the track of the unmanned aerial vehicle in a high-dynamic environment are realized.

The invention discloses a rice yield estimation method based on unmanned aerial vehicle remote sensing and rice spike feature extraction, which comprises the following steps: firstly, assuming a ground section RTK base station and combining an unmanned aerial vehicle remote sensing platform to determine a coverage range and a spatial position of a rice region, and then collecting a rice image and canopy height and performing deblurring processing; then using a rice ear detection model to obtain a rice ear segmentation mask, determining a pixel scaling factor to construct a rice ear feature index, and carrying out statistical analysis and identification on key features to form a feature data set; performing yield estimation by using a rice yield estimation model, and optimizing the model in combination with the actual yield; and finally, transmitting the data to a ground end to generate a thermodynamic diagram and a statistical diagram, and carrying out regional comparison and time sequence trend analysis. According to the method, the influence of the flight height on yield estimation is eliminated based on the rice ear segmentation result in combination with high-precision depth information, and the accuracy and efficiency of rice yield estimation are effectively improved.

A flight path generation system for generating a three-dimensional flight path for an unmanned aerial vehicle includes an acquisition device to acquire route data including information of a two-dimensional flight path of the unmanned aerial vehicle and map data including information of elevation at each point on the two-dimensional flight path, and a processor configured or programmed to generate the three-dimensional flight path by determining a flight altitude of the unmanned aerial vehicle from a ground on the two-dimensional flight path based on the two-dimensional flight path and the elevation. The processor is configured or programmed to determine the flight altitude in an excess region with an altitude not exceeding a first altitude and a first region with an altitude not exceeding the first altitude, such that a maximum value of the flight altitude of the unmanned aerial vehicle in the excess region does not exceed the first altitude.

The invention discloses an unmanned aerial vehicle channel inspection path optimization method based on dynamic environment perception, and relates to the technical field of unmanned aerial vehicle intelligent path planning. Comprising the following steps: establishing a three-dimensional environment model based on channel geographic information data and surveying and mapping point cloud data, and generating an initial routing inspection path set with a coverage range meeting requirements; predicting and generating an obstacle envelope sequence changing along with time by using a dynamic obstacle trajectory collected by an airborne radar and a camera, performing space-time superposition calculation on the obstacle envelope sequence and the initial inspection path, and removing path fragments conflicting with a future obstacle movement range to obtain an inspection path set after obstacle avoidance correction; and according to elevation information in the three-dimensional environment model, predicting a local area and a spatial range in which communication shielding may occur in the inspection path of the unmanned aerial vehicle, carrying out secondary correction on a path segment which is about to enter a communication shielding area, and outputting a corresponding flight height and speed sequence.

The invention discloses an intelligent navigation method and device of an unmanned aerial vehicle, equipment and a storage medium. The method comprises the following steps: acquiring point cloud data and motion data, and calibrating to obtain a relative position and time synchronization parameter; performing map construction on the point cloud data and the motion data to generate a three-dimensional point cloud map; analyzing the boundary coordinates of the flight area, the flight height and the route step length, and generating route planning parameters; the boundary of the target inspection area is defined by combining the three-dimensional point cloud map, and an optimized route and corresponding waypoint sequence data are generated through route planning; acquiring real-time pose data of the unmanned aerial vehicle, comparing the current position with the waypoint sequence, and triggering image acquisition when a preset waypoint reaches a tolerance range; inspection data is obtained; and integrating the real-time pose data, the three-dimensional point cloud map, the flight state and the inspection data to form an intelligent navigation route. According to the invention, high-precision positioning and linkage of waypoints and data acquisition are realized, and the navigation precision, the inspection efficiency and the operation safety are improved.

The invention belongs to the technical field of induced polarization detection, and provides an air-ground capacitance non-contact frequency spectrum induced polarization detection system and method.The air-ground capacitance non-contact frequency spectrum induced polarization detection method is characterized in that a plurality of power supply electrodes are arranged at intervals along a detection route, and a capacitance plate acquisition module is carried on an unmanned aerial vehicle flight module; the unmanned aerial vehicle flight module and the mobile platform unit are controlled to run along the detection route; an excitation signal with preset amplitude, current, voltage or / and frequency is sent to the power supply electrode, and feedback data generated by the capacitor plate acquisition module is obtained; calculating an optimal detection flight height according to the feedback data; and after the detection tasks of all the measuring points are completed, performing comprehensive processing and imaging inversion on the collected full-band data, generating an apparent resistivity distribution map and a polarization parameter profile map of the underground medium, and obtaining electrical information of the earth surface. According to the invention, the electrical information of the earth surface and the shallow layer in a large area can be rapidly obtained, and the method is suitable for high-efficiency induced polarization detection under various topographic conditions.

The invention discloses a photovoltaic station unmanned aerial vehicle three-dimensional route planning method and system based on field angle self-adaption and terrain modeling. The method comprises the following steps: acquiring geographic position information of a photovoltaic panel; determining a vertical field angle according to the unmanned aerial vehicle image equipment parameters; generating a reference point based on geographic position information, performing horizontal clustering by adopting a density clustering algorithm to form an initial row group, and completing row-column grouping through linear fitting completion and correction of a row structure; dynamically determining a flight height for each waypoint through geometric model calculation based on a grouping result in combination with a vertical field angle and a pitch angle, and generating a three-dimensional waypoint; and determining a waypoint connection sequence based on a distance optimal principle, detecting and optimizing acute-angle turning, and generating a smooth three-dimensional flight path. According to the invention, full-automatic three-dimensional planning of the photovoltaic inspection route is realized, the system can adapt to complex terrains, the shooting quality is ensured, and the inspection efficiency is improved.

The invention relates to the technical field of noise modeling, in particular to a low-altitude aircraft environment noise modeling method and system. Sound source directivity data of the low-altitude aircraft at different positions under the spherical coordinate system are reprojected to a hemispherical surface and then converted into sound source directivity tensors; converting the environmental topographic information and the building geometric information into topographic layout tensors; fusing the advanced features of the sound source directivity tensor, the advanced features of the terrain layout tensor, the frequency features of the low-altitude aircraft at the current moment and the flight height features of the low-altitude aircraft at the current moment to obtain multi-modal potential features at the current moment; and inputting the multi-modal potential features at the current moment into the diffusion model, and outputting a noise intensity graph of the low-altitude aircraft at the current moment. According to the method, complex multi-modal conditions such as noise source characteristics, terrain layout and flight height of the low-altitude aircraft can be accurately captured and fused, and the efficiency, precision and generalization ability of noise modeling are effectively improved.

The invention discloses an unmanned aerial vehicle autonomous route planning method and system capable of adapting to environmental changes. The method comprises the steps of obtaining a dynamic three-dimensional situation map of a flight area of an unmanned aerial vehicle based on multi-source data of the flight area of the unmanned aerial vehicle; acquiring a current no-fly zone and weather forecast information of the flight area of the unmanned aerial vehicle, and analyzing and acquiring a flight risk distribution condition of the flight area of the unmanned aerial vehicle based on the dynamic three-dimensional situation map; considering the flight risk distribution condition of the unmanned aerial vehicle flight area, the unmanned aerial vehicle flight task and the unmanned aerial vehicle self-state information to generate an unmanned aerial vehicle reference route; and automatically adjusting the flight speed, the flight height and the flight course of the unmanned aerial vehicle according to a preset flight parameter adjustment model based on the acquired multi-source data and the state information of the unmanned aerial vehicle in the process of flying along the reference route. According to the invention, the reliability and safety of flight task execution of the unmanned aerial vehicle in a complex dynamic environment can be improved.

The invention belongs to the technical field of remote sensing image processing and target inversion, and particularly relates to a hyperspectral image aerial aircraft height and spectral reflectivity inversion method based on wake clouds and shadows of the wake clouds. In order to solve the technical problems of low aerial aircraft height inversion precision and inaccurate spectral reflectivity inversion in the prior art, firstly, wake cloud and shadow detection, matching and geometric modeling are performed on a hyperspectral image, and the aircraft flight height is inverted by using a stable geometric relationship between the wake cloud and the shadow; high-precision height extraction is realized; and then combining flight height information to establish a radiation transmission model for coupling the aerial aircraft and the background environment, and inverting the spectral reflectivity of the model. Through integrated processing of wake cloud detection, shadow matching, height inversion and spectral reflectivity inversion, the accuracy and applicability of aerial aircraft characteristic inversion are significantly improved, and an effective technical support is provided for application of hyperspectral remote sensing in aerial aircraft monitoring and identification.

The invention provides a low-altitude traffic operation control method and system based on moving block. The method comprises the following steps: layering an airspace according to aircraft type performance and service types for the vertical take-off and landing aircraft, and distributing corresponding entering and leaving areas according to flight height layers of the aircraft; quasi-moving block is introduced into a low-altitude traffic system, an air route network and operation rules are designed, a free area-buffer area-block area three-level space structure of an aircraft is dynamically constructed according to the state of the aircraft, when the front aircraft occupies a certain block area, the first area in front of the block area is a buffer area, and the second area in front of the block area is a block area. The second zone in front of the blocking zone is a free zone, the aircraft flies in the free zone according to the current speed, and the aircraft is selected for braking in the buffer zone according to the braking distance obtained through calculation. According to the method, the braking curve is generated by dynamically dividing'free area-buffer area-block area 'and combining the braking performance, so that the safety redundancy is increased, and the safety and airspace utilization rate is improved.

The invention discloses a multi-unmanned aerial vehicle electric power inspection task allocation method and system, and the method comprises the steps: building an optimization objective function according to the constraints of a total flight distance, an average flight height, and a terrain threat; by improving a random step size search strategy based on distance weight, the predation stage of the black wing plinualism algorithm is optimized, and the global search ability of the algorithm is enhanced; an optimal individual selection strategy based on fitness and distance is introduced, and the global search efficiency and optimization precision of the black-wing plinary algorithm in the migration stage are enhanced; a cooperative predation mechanism of the Arctic Sea-Sharrow algorithm is introduced, positions are updated through individual cooperation, and the ability of the algorithm to jump out of local optimum is effectively improved. The method has remarkable advantages in the aspects of task allocation efficiency and precision in complex mountain environment simulation, collision-free paths between generated task points are shorter, and an efficient solution is provided for unmanned aerial vehicle task allocation and path planning under complex terrains.

The invention relates to a logistics unmanned aerial vehicle multi-objective optimization method based on an MODDPG-NSGA2 double-layer architecture. The method comprises the following steps: (1) establishing a logistics unmanned aerial vehicle scheduling model of multiple objective functions (a minimum distance function, a maximum time limit-reaching rate function and a minimum energy consumption function) and multiple constraint conditions (load balance, flight height, distribution distance, distribution speed and order distribution time constraint); (2) developing an MODDPG module to perceive a dynamic environment in real time, and quickly responding to a local strategy to complete re-planning according to sudden changes of the environment and orders; and (3) developing an NSGA2 module to globally optimize a multi-objective function, searching an optimal solution set, a balance path, an aging standard-reaching rate and an energy consumption target condition under complex constraints, and enhancing the adaptability and operation efficiency of the logistics unmanned aerial vehicle in a complex urban environment. Through deep fusion of the MODDPG module and the NSGA2 module, the method has the sensitive response of a dynamic scene and the multi-target global optimization capability, the transportation efficiency under complex constraints is greatly improved, and organic unification of real-time decision and global optimization is realized.

The invention relates to an unmanned aerial vehicle control method, system and device for high-rise fire extinguishing and a medium. According to the method, a height-lift mapping model is constructed before a task, and a cooperative controller and a state observer are initialized, so that a foundation is laid for real-time control; during operation, a reference lift is obtained according to a real-time flight height query model, meanwhile, the dynamic resistance loss of a pipeline is estimated by using a state observer, and the reference lift and the dynamic resistance loss are fused to generate an accurate dynamic demand lift; and with the above as a target, a pump rotating speed instruction is output through a feedforward-feedback algorithm, pump power consumption is predicted synchronously, real-time flight power consumption is combined, power distribution is optimized and solved by a cooperative controller, and finally a coordination instruction is generated. Therefore, in the continuous change process of the flight height, accurate maintenance of the fire extinguishing lift and dynamic optimal distribution of flight and pumping power energy are achieved, and the problems of lift pressure self-adaptive regulation and control and airborne energy competition in high-rise fire extinguishing are effectively solved.

This application discloses an aerial photography flight path planning method, which includes: acquiring a planar polygonal region; generating a first photography point; selecting a second photography point from the first photography point and setting constraints; if no set of second photography points satisfying the conditions exists, decreasing the focal length in the preset camera parameters and / or increasing the preset drone flight altitude, and then re-executing the step of calculating the rectangular coverage area to select the second photography point; if a set of second photography points satisfying the conditions exists, recording the current camera parameters and drone flight altitude, then increasing the focal length and / or decreasing the flight altitude, and re-executing the step of calculating the rectangular coverage area to select the second photography point; using the set of second photography points that last satisfied the constraints as the final planning result; planning the flight path and generating an aerial photography flight path file. This application can be used to solve the technical problems of low coverage efficiency and poor image clarity in existing aerial photography methods.

The embodiment of the invention provides an unmanned aerial vehicle real-time visual positioning method and system, electronic equipment and a storage medium, and belongs to the technical field of visual positioning. According to the scheme, a flight detection sequence of a takeoff stage is obtained; controlling the unmanned aerial vehicle to descend in the target landing area according to the current position information of the landing stage and a preset landing point; performing visual reference detection according to the current image information, and judging whether a landing marker is detected or not; if the landing marker is not detected, whether reference marker information exists or not is judged according to the current flight height; if the reference marker information exists, performing feature point matching according to the current image information based on the reference marker information, and determining a target positioning point; and controlling the unmanned aerial vehicle to land on the ground according to the target positioning point. The positioning error caused by environmental interference can be reduced, and the positioning precision is improved.

The invention provides a multi-modal fusion input unmanned aerial vehicle ground target identification and positioning method and system, and belongs to the technical field of intelligent target identification and precise positioning. The method comprises the following steps: firstly, through improving a YOLOv5 target identification network, obtaining a pixel position of a to-be-identified target in an image obtained by an unmanned aerial vehicle under visible light and infrared modal fusion data; secondly, converting the obtained pixel coordinates of the recognition target in a series of coordinate systems by using a multi-stage coordinate system conversion calculation method, and finally obtaining WGS84 latitude and longitude coordinates after the pixel coordinates of the recognition target point are converted in combination with unmanned aerial vehicle information such as latitude and longitude, flight height, flight attitude and camera internal parameters of the unmanned aerial vehicle and embedded digital elevation model data; according to the invention, accurate calculation of the ground target by means of the unmanned aerial vehicle platform in various low-altitude operation scenes can be realized.

This invention discloses an AI-based automatic positioning and navigation system for unmanned aerial vehicles (UAVs), comprising: a UAV body that obtains the starting coordinates through a navigation module by manually inputting the destination coordinates and the planned flight duration t, and then flies from the starting coordinates to the destination coordinates at a flight speed V1 and a flight altitude H1, automatically completing the flight mission and automatically determining the return-to-home status; and a monitoring unit that acquires the initial battery level Q of the UAV body, transmits the initial battery level to the coordinate unit, and monitors the output power of the battery in real time during flight. When abnormal output power occurs during flight, a feedback signal is generated and transmitted to the correction unit. This invention relates to the field of UAV technology and solves the problem that existing UAV automatic positioning and navigation systems do not consider the UAV's battery life, which can easily lead to the UAV being unable to return to home or even crashing during flight.

The application discloses a kind of unmanned aerial vehicle autonomous inspection orthographic image generation method, it is related to unmanned aerial vehicle surveying and mapping and autonomous navigation technical field, the path optimization strategy of the present application is fused by genetic algorithm, global optimization is realized to route in combination with the image parameter constraint of inspection area grid feature, with candidate navigation point as node, through the smoothness factor of navigation section, redundant navigation point is filtered, and the complexity of route is reduced, genetic algorithm is constrained with flight height, navigation point spacing, constructs fitness function including flight distance, number of turns, overlap rate, finds global optimal path by population iteration, optimizes and balances multi-objective demand, ensures that route meets image acquisition accuracy requirement, can also shorten flight distance, reduce number of turns, adapt to the endurance of unmanned aerial vehicle, guarantee that inspection task is efficiently promoted, simultaneously, the navigation point coordinates of simulation output are directly adapted to flight control system, ensure that actual flight parameter is consistent with planning parameter.

The invention relates to the technical field of unmanned aerial vehicle control, and discloses an unmanned aerial vehicle accurate landing method based on image recognition, which comprises the following steps: an unmanned aerial vehicle receives a guide signal or a GPS coordinate from a landing platform, and flies to the sky of a landing area; the unmanned aerial vehicle vertically and downwards shoots an image containing a preset landing mark through an airborne camera; preprocessing and feature enhancement are carried out on the shot image, then the image is input to a target detection network, and a center pixel coordinate of a landing mark and contour information of the landing mark in the image are identified; and combining flight height sensor data of the unmanned aerial vehicle according to the corresponding relationship between the pixel size of the identified landing mark and the real-world size of the landing mark. The method is switched to a high-frame-rate image acquisition mode in a short-distance landing stage, realizes sub-centimeter-level position alignment precision through real-time visual servo fine adjustment, effectively eliminates accumulated deviation before final grounding, and provides key space alignment guarantee for stable and accurate landing of the unmanned aerial vehicle.

The invention relates to the field of photogrammetry, in particular to a three-dimensional terrain reconstruction method and system based on an unmanned aerial vehicle image. A three-dimensional terrain reconstruction system based on an unmanned aerial vehicle image comprises an information acquisition module, a terrain difference judgment module, a flight mission planning module and a terrain reconstruction module. According to the method, key parameters such as the flight height, the overlapping rate, the speed and the exposure interval can be dynamically updated in the flight process through a period adjustment mechanism driven by a difference index and a neural network task parameter solving model; when the wind speed suddenly increases, the illumination changes or the landform drastically fluctuates in the measured area, the system automatically shortens the refresh cycle and executes global or local adjustment, so that potential holes or fuzzy images are compensated in time, high-coverage and high-definition acquisition of the complex landform is realized, and manual intervention or expensive hardware addition is not needed.

An unmanned aerial vehicle includes a plurality of electric motors each to drive a respective one of a plurality of first rotors included in a plurality of rotors, an internal combustion engine, an electric generator that is driven by the internal combustion engine to generate electric power, a battery to store the electric power, and a controller configured or programmed to control flight of the unmanned aerial vehicle and to change an upper limit of a flight altitude of the unmanned aerial vehicle according to a charging state of the battery.

The application discloses a kind of ship compliance monitoring methods based on unmanned aerial vehicle and AIS data fusion.The method controls satellite positioning module, IMU and vision sensor of unmanned aerial vehicle to collect data;Satellite positioning antenna is compensated using IMU real-time attitude lever arm effect, and the corrected unmanned aerial vehicle coordinates are obtained;Based on vision SFM algorithm and unmanned aerial vehicle positioning displacement baseline, the relative position vector of ship is solved, and the absolute coordinate of ship is obtained by space projection;Through linear interpolation, the time and space alignment of measured data and AIS data is realized;Finally, coordinate deviation is calculated, and dynamic threshold based on flight height, sea state and other environmental parameters is combined to determine the compliance of ship.The application realizes independent high-precision solution and full-dimensional verification of ship position, heading and speed, effectively solves the problems of AIS data fraud identification difficulty, large environmental interference and other problems, and greatly improves the accuracy and intelligent level of maritime non-site law enforcement.

The application relates to a flight path height determination method and device of a UAV, electronic equipment and a medium, the method comprising: acquiring a scene type where the UAV is located, a UAV model and a signal strength coefficient; according to the UAV model, acquiring a wind force grade coefficient and a fuselage size parameter corresponding to the UAV model; if the scene type is a first scene, according to the fuselage size parameter corresponding to the UAV model, the wind force grade coefficient and the signal strength coefficient, determining the flight path height of the UAV; if the scene type is a second scene, acquiring a UAV speed, and according to the UAV speed, the fuselage size parameter, the wind force grade coefficient and the signal strength coefficient, determining the flight path height of the UAV. Through the method, the scene type where the UAV is located, the UAV model, the navigation signal strength and the flying UAV speed are comprehensively considered, the accuracy of the flight path height calculation is improved, and the flight adaptability and task execution capability of the UAV in a complex environment are enhanced.

The invention relates to a method for evaluating fuel gas jet radiation heating, which comprises the following steps of: defining a jet boundary as a semi-cylindrical outer surface and an arc surface outer surface which have the same diameter as a nozzle outlet according to a flight height, and determining the arc surface outer surface by calculating an initial expansion angle, a radius of an arc, a Mach number of the nozzle outlet and a Prandt-Myer angle; calculating the angle coefficient of each point at the bottom when the jet flow boundary is the semi-cylindrical outer surface; carrying out engine ground test run, measuring the radiation heat flow of the engine, estimating the angle coefficient of the bottom heat flow measuring point position and the jet radiation heat flow, correcting the fuel gas equivalent blackness, and calculating the radiation heat flow of each point when the jet boundary is the semi-cylindrical outer surface and the radiation heat flow of each point when the jet boundary is the arc surface outer surface; according to the method, high-temperature fuel gas jet flow field calculation and high-temperature gas spectrum radiation characteristic and transmission calculation do not need to be carried out, and engineering rapid prediction of radiation heating of the aircraft tail mounting object is realized by utilizing ground engine test run test measurement data association.

The invention provides a laser height measurement system for an aircraft and a calculation method of the laser height measurement system. The system comprises an inertial measurement unit, an information processing computer and a laser range finder, the inertial measurement unit acquires the acceleration and angular velocity of the aircraft in real time and periodically transmits the acceleration and angular velocity to the information processing computer; the information processing computer solves the real-time attitude angle of the aircraft through a strapdown inertial navigation algorithm; when the aircraft meets a preset launching condition, the aircraft departs from the orbit and enters a flight state, and the information processing computer sends a laser ranging instruction to the laser range finder; after the laser range finder receives the range finding instruction, the laser range finding function is started, the target distance is measured, and obtained distance data is transmitted back to the information processing computer according to a set period; and the information processing computer calculates the current flight height of the aircraft in real time according to the attitude angle of the aircraft, the ranging value of the laser range finder and the mounting angle of the laser range finder. The system provided by the invention has the characteristics of high measurement precision and good electromagnetic compatibility.

The application discloses a photovoltaic station unmanned aerial vehicle three-dimensional route planning method and system based on field of view angle self-adaption and terrain modeling. The method comprises the following steps: acquiring photovoltaic panel geographic position information; determining a vertical field of view angle according to an unmanned aerial vehicle image device parameter; generating a reference point based on the geographic position information, performing horizontal clustering by using a density clustering algorithm to form an initial row grouping, and then completing row and column grouping by linear fitting completion and correction of row structure; dynamically determining a flight height for each flight point by a geometric model calculation based on the grouping result, a vertical field of view angle and a pitch angle, and generating a three-dimensional flight point; determining a flight point connection sequence based on a distance optimization principle, detecting an optimized acute angle turning, and generating a smooth three-dimensional flight path. The application realizes full-automatic three-dimensional planning of a photovoltaic inspection route, can adapt to complex terrains, guarantees shooting quality and improves inspection efficiency.

The present application provides a kind of rocket program angle determination method, device, medium and equipment, comprising: obtaining standard trajectory program angle binding data table;Determine Lagrange fitting order, determine program angle fitting function according to Lagrange fitting order and standard trajectory program angle binding data table;Determine the fitting program angle corresponding to current time according to current time and program angle fitting function;Thus, even if with larger time interval binding program angle, the present application can select Lagrange fitting order according to launch task demand, and the fitting program angle under current time is obtained by Lagrange interpolation according to standard trajectory program angle binding data table, since the higher Lagrange fitting order, the higher the precision of fitting program angle, therefore suitable Lagrange fitting order can be selected to obtain suitable fitting function, flight altitude is substituted into fitting function to obtain fitting program angle, reduce the influence of interference moment received by rocket body, improve the control precision of rocket attitude.