859 results about "Flight track" patented technology

The invention discloses an unmanned aerial vehicle course generation method which includes the following steps: conducting view finding and flying in advance, recording flight waypoints which include location data and flight height information of an unmanned aerial vehicle; receiving and recording the flight waypoints of the unmanned aerial vehicle; generating a flight track according to the flight waypoints of the view finding and flying; compiling the flight track to obtain a new flight track; transmitting the complied flight track to the unmanned aerial vehicle to enable the unmanned aerial vehicle to fly according to the new flight track. An unmanned aerial vehicle course generation system is further provided.

The invention discloses a railway line inspection system. The railway line inspection system comprises a coming and going train information acquisition subsystem, a data and fault processing subsystem, a flight control subsystem and a data acquisition subsystem. The coming and going train information acquisition subsystem determines coming and going train information of a railway line and sends the coming and going train information to the data and fault processing subsystem. The flight control subsystem controls the flight track and attitude of an unmanned aerial vehicle and the action of avoiding coming and going trains. The data acquisition subsystem is arranged on the unmanned aerial vehicle, acquires field data of the railway line and sends the field data to the data and fault processing subsystem to be processed, wherein the field data comprises radar scanning data and field image data of the railway line. The data and fault processing subsystem receives and analyzes the field data of the railway line and determines the fault type and generation position. The technical problems that an existing railway line inspection mode is single in means and low in reliability, affects normal train driving and cannot meet the requirements for high-speed railway operation safety can be solved.

A method for generating a voted trajectory of a vehicle in a first vehicle. First trajectory data is received from at least one second vehicle in a receiver in the first vehicle. Trajectory data is calculated in a trajectory calculator in the first vehicle. The calculated trajectory data and the received first trajectory data concern a determined vehicle. The determined vehicle is determined from a group including the first and the second vehicles. The voted trajectory of the determined vehicle by a voting process based on the calculated trajectory data and the received first trajectory data.

AirScene™, through a unique fusion process, is the only NOMS system to provide such data, digitally, and in a form that is integrated with flight tracks, noise events, complaint, and operations data. Other systems provide only the flight track, noise event, and complaint, and a manual recording of various ATC frequencies. Therefore other approaches do not offer any type of automated correlation of operational information with noise and flight track data. AirScene™ offers users the ability to record, search and query vast numbers of records using all of the above parameters, where available.

The surveillance system provides a means to augment Automatic Dependent Surveillance-Broadcast (ADS-B) with “look alike ADS-B” or “pseudo ADS-B” surveillance transmissions for aircraft which may not be ADS-B equipped. The system uses ground based surveillance to determine the position of aircraft not equipped with ADS-B, then broadcasts the identification / positional information over the ADS-B data link. ADS-B equipped aircraft broadcast their own position over the ADS-B data link. The system enables aircraft equipped with ADS-B and Cockpit Display of Traffic Information (CDTI) to obtain surveillance information on all aircraft whether or not the proximate aircraft are equipped with ADS-B.

The invention discloses a motion-sensing follow-type flight control system and method. The motion-sensing follow-type flight control system comprises a remote controller and an aircraft. The remote controller comprises a power supply system, an acceleration sensor, a digital-analog converter, a microcontroller and a radio transmission module. The aircraft comprises an information receiving module, an acceleration sensor, a gyroscope sensor, a barometer sensor, a data processing module and a control driving module. The remote controller obtains the acceleration magnitude of the hand through the acceleration sensor, collects motion data of the hand, and processes the motion data through the digital-analog converter. Then, the microcontroller calculates the acceleration change of the aircraft according to the acceleration change of the hand, and transmits a corresponding control instruction to the aircraft through the radio transmission module, so that the aircraft follows motions of the hand to cope and magnify the control motions guided by the hand, the aircraft is guided to fly in various corresponding flight paths by following the motions of the hand, and the immersive feeling is brought to an operator.

The invention provides a side wind resistance landing flight track tracking control method based on side direction guide, which belongs to the flight track tracking control technology of airplanes landed under the side wind condition. The flight track tracking control method based on side direction guide is adopted, and comprises the following steps: calculating the inner ring posture control commands through a side direction guide law by the flight track tracking side direction deviation; generating steering engine control commands by an inner ring posture controller for controlling the airplane posture; and calculating the current side direction deviation by the flight line switching logics according to the current state of the airplane for the side direction guide law calculation. A transverse side direction movement model of the airplane is used for simulating the dynamic and kinematic model of the airplane. When being adopted, the side direction flight track control system based on the ground speed guide has better inhabitation effect on the side wind phenomena such as side direction gust wind, air turbulence, side direction wind shear and the like when the airplane is landed. At the same time, the side direction flight line switching logics can also meet the requirement of approach flight of the airplane under the side wind condition.

The invention provides a four-dimensional flight track dynamic prediction method based on ADS-B information updating. By communicating with networks among ADS-B receivers, a ADS-B data decoding module is adopted to obtain real-time velocity information, height information, longitude information and latitude information of a flight, and consistency check is conducted on a predicted flight track and the real-time velocity, height, longitude and latitude of the flight, so that the dynamic, online and real-time flight track prediction capability is achieved. The method can provide important technical support for developing the automation and intellectualization of air traffic control and achieving the flight-track-based operation.

The invention provides a multi-target route planning and united searching method of a drone in an urban low-altitude environment, and belongs to the technical field of drone route planning. The method comprises steps of firstly, based on a static-state known obstacle, constructing a static-state safe index map, and based on an obstacle which is actively detected by the drone in a flight process and is not marked in a geographical map, constructing a dynamic state safe index map on an airborne platform; and then, based on offline searching and online searching, solving and optimizing a multi-target route planning problem of flight time and flight safety of the drone in an united manner. According to the invention, a path costing little from a start point to a termination point is planned in an offline manner; when an unknown obstacle is detected, a changed flight track is planned in an online manner through online searching, so a dynamic obstacle is avoided; and there is a quite small searching space in the online searching, so a safe route can be planned again from the drone rapidly, so requirements on real-time planning of routes for drones are met.

The invention belongs to the field of unmanned helicopter flight track planning, and relates to a fast flight track planning method aiming at an unmanned helicopter. The unmanned helicopter flight track planning method adopts a mapping control to add the map function into the flight track planning application, realizes flight track point confirmation through mouse selecting and flight track point modification through mouse dragging on a high accurate digital map, and considers specific flight performances of the helicopter during constraint condition planning, such as the hovering characteristic. The method solves the problem of practicability in unmanned helicopter flight track planning, requires no manual edition of flight track point coordinate position, is convenient to operate, is fast in planning, and has high interactivity.

A system, comprising a data receiving arrangement to receive target data points from a data feed arrangement, each target data point including data corresponding to a location of a target aircraft and additional information on the target aircraft, a data analyzing arrangement to analyze the target data points and store each target data point in a target flight record, the target flight record corresponding to the target aircraft a data generation arrangement to generate a flight track for the target aircraft using the data stored in the target flight record and a data distribution arrangement to organize the flight track and the additional information into a displayable file and distribute the file to users of the system, wherein the displayable file is displayed on a single graphical user interface including the flight track and the additional information.

The invention discloses an unmanned plane aerial photographing system and method of a photographing accompanying aircraft, and belongs to the application field of unmanned planes. The system comprises a main flight aircraft and a flight accompanying unmanned plane carrying aerial photographing equipment. The system further comprises a positioning identification device and a synchronizer. The positioning identification device obtains position information of the main flight aircraft and the flight accompanying unmanned plane, and calculates and obtains a relative position relation between the main flight aircraft and the flight accompanying unmanned plane. The synchronizer plans in real time the flight track of the flight accompanying unmanned plane according to the relative position relation, generates a flight construction controlling the flight accompanying unmanned plane, controls the flight of the flight accompanying unmanned plane, and ensures that the relative position relation is within a preset range. The aerial photographing equipment automatically tracks and photographs the main flight aircraft. The a flight accompanying unmanned plane carrying the aerial photographing equipment is utilized to photograph the main flight aircraft that is flying, and a position identification and synchronization mechanism is also adopted, so a photographing process is effectively completed.

The invention discloses a real-time closed loop predictive tracking method of a maneuvering target, which is a closed loop real-time self-adaptive processing method of on-line predictive immediate tracking in a maneuvering small target imaging tracking system and is mainly used for fields of photoelectric imaging tracking, robot vision, intelligent traffic control and the like. Due to the adoption of the method, a captured target can be extracted to to establish a flight track, the target flight track is filtered, the position of a target at a next collection time is predicted, a platform is processed in real time on line with high performance of a DSP main processor and a FPGA coprocessor, a prediction algorithm which can cope with target maneuver with higher accuracy is adopted to predict the motion state of the target in real time and a prediction result is utilized to drive a piezoelectric ceramic motor two-dimensional motion station to carry out overcompensation, thereby the self-adaptive predictive tracking is realized. The invention has the advantages that the method can overcome the defect of a largened tracking error caused by system delay and can still carry out continuous and stable tracking when the target maneuvers or is temporarily sheltered.

The invention relates to an unmanned aerial vehicle trajectory optimization and resource allocation method. The method comprises the following steps: S1, modeling an unmanned aerial vehicle trajectoryoptimization and resource allocation problem based on an unmanned aerial vehicle base station system; S2, planning an unmanned aerial vehicle trajectory optimization and resource allocation problem to ensure the fairness of unmanned aerial vehicle service for each user; S3, jointly optimizing the bandwidth and the power of the unmanned aerial vehicle under the condition of giving the track of theunmanned aerial vehicle; S4, optimizing the trajectory of the unmanned aerial vehicle under the condition of given bandwidth and unmanned aerial vehicle power; S5, comprehensively considering the S3and S4, and solving the problems of unmanned aerial vehicle trajectory optimization and resource allocation. According to the invention, the service quality of edge users, users blocked by obstacles and the like can be improved; bandwidth, power distribution and flight path of the unmanned aerial vehicle are optimized at the same time, so that the bandwidth, the power distribution and the flight path of the unmanned aerial vehicle are matched with one another, and communication efficiency of a communication system is greatly improved under limited communication resources.

The invention discloses a Wi-Fi signal fingerprint positioning algorithm for assisting in speculating flight tracks of pedestrians. A PDR positioning algorithm and a Wi-Fi signal fingerprint positioning algorithm are utilized for estimating positions alternatively, and the respective errors of the two algorithms are respectively amended by utilizing the result of the other one; the initial position P(x) of a user is equal to{x(0), y(0)} and is obtained by the KWNN (K weighted nearest node) based Wi-Fi signal fingerprint positioning algorithm; after the user begins to move, the variation of speed and angular speed is measured by an accelerometer and a gyroscope; the coordinate of each step of the user is estimated by utilizing the PDR positioning algorithm; Wi-Fi fingerprint positioning is carried out based on KWNN once until the user proceeds by the preset steps m, and the Wi-Fi fingerprint positioning result acts as the current result of the user; in the following m steps, the PDR positioning calculation is carried out based on the previous Wi-Fi fingerprint positioning result, and the operations are repeated in the way. The KWNN algorithm in Wi-Fi signal fingerprint positioning the corner is restrained by utilizing the movement distance and a corner output by the PDR, and the selection of the movement distance and a corner constraint reference point is obtained by the PDR within short time, so that the aim of improving the positioning precision by utilizing the KWNN algorithm is realized.

A prediction correcting guidance method of a deep space exploration returning process comprises the steps that (1) a heeling angle section used for deep space exploration returning process track prediction is determined; (2) the amplitude value | sigma 0 | of the heeling angle of a current point is computed in an iterative mode; (3) a salutatory reentry flight track of a returning device is divided into an initial reentry stage, a primary reentry descending stage, a primary reentry ascending stage, a Kepler stage and a final reentry stage, a final guidance rule of the returning device is determined, and the final guidance rule is that when the returning device is in the initial reentry stage or the primary reentry descending stage or the primary reentry ascending stage or the final reentry stage, the amplitude value | sigma 0 | determined in the step (2) of the heeling angle sigma 0 of the current point is used for guidance; and when the returning device is in the Kepler stage, | sigma 0 | = 180 degrees is used for guidance, and accordingly prediction correcting guidance of the deep space exploration returning process is completed. The guidance rule is designed at the Kepler stage of the track for achieving overload restrain on the deep space exploration returning process, and safe and accurate landing of the returning device is guaranteed.

There is provided a method for displaying aircraft positions, which is capable of effectively avoiding the occurrence of near miss or collision. The method displays the terrain of an air space under air traffic control apparently in three dimensions on a display screen, displays aircraft marks at positions on the display screen so as to correspond to the three-dimensional positions of the respective aircraft, and displays a warning mark when a distance between two aircraft is shorter than a threshold value, wherein the warning mark comprises a triangle having three apexes, which comprise the aircraft marks, and a position that is apart from the aircraft mark of one of the aircraft along a vertical line extending perpendicular to the one aircraft toward a ground surface of the terrain by a distance corresponding to an altitude difference between both aircrafts on the display screen. A certain warning mark may be displayed when protective air spaces for both aircraft are predicted to conflict each other based on flight trajectories and flight conditions.

The invention discloses an unmanned aerial vehicle automatic collision avoidance system, including an unmanned aerial vehicle situation sensing module used for single level or pixel level target detection, tracking and recognition and abstraction of global cognition of environment from information to realize cognition of environment; an unmanned aerial vehicle collision threat assessment and prediction module used for making a threat assessment and conflict prediction of static obstacles, extreme weather and moving targets in a detected area when an unmanned aerial vehicle runs in airspace; and an unmanned aerial vehicle decision collision avoidance module used for generating corresponding behavior selection after the unmanned aerial vehicle obtains a flight conflict trend through assessment prediction, planning a feasible optimal collision avoidance path in time through a flight path planner, and outputting an avoidance decision and a maneuvering instruction. The unmanned aerial vehicle automatic collision avoidance system can realize automatic sensing and avoidance during flight of the unmanned aerial vehicle in the air, realizes systemization, automation and intelligentization of unmanned aerial vehicle collision prevention, and remarkably improves flight safety of all aircrafts when the unmanned aerial vehicle and other aircrafts share airspace.

Micro / nano mono-wing aircraft with the wing configured as a winged seed (Samara) is uniquely suited for autonomous or remotely controlled operation in confined environments for surrounding images acquisition. The aircraft is capable of effective autorotation and steady hovering. The wing is flexibly connected to a fuselage via a servo-mechanism which is controlled to change the wing's orientation to control the flight trajectory and characteristics. A propeller on the fuselage rotates about the axis oriented to oppose a torque created about the longitudinal axis of the fuselage and is controlled to contribute in the aircraft maneuvers. A controller, either ON-board or OFF-board, creates input command signals to control the operation of the aircraft based on a linear control model identified as a result of extensive experimentations with a number of models.

The invention provides an unmanned plane flight path drawing method, device and system. The method comprises the steps of: planning a flight destination and a flight path of an unmanned plane; receiving a position signal returned in the flight process of the unmanned plane every a set time interval, and drawing the flight path of the unmanned plane on an electronic map according to the position signals; and if failing to receive the position signals in the set time interval, then setting the position, corresponding to the last received position signal, on the electronic map as a starting point of a virtual path, starting drawing the virtual path, using the flight speed of the unmanned plane at the time of the last received position signal as an analog flight speed of the unmanned plane, determining the flight direction at the present position of the unmanned plane according to the direction of the destination, determining the next arrived position of the unmanned plane after the set time interval, and drawing the virtual path of the unmanned plane on the electronic map according to the next position. By adopting the unmanned plane flight path drawing method, a user is enabled to estimate the position of the unmanned plane after the unmanned plane is lost, and the user is enabled to be still ready for unmanned plane recovery.

The invention provides an unmanned aerial vehicle space navigation method, an unmanned aerial vehicle control system and an unmanned aerial vehicle control device. The unmanned aerial vehicle space navigation method includes the first step of determining the flight range of an unmanned aerial vehicle and adjusting the image acquisition range of an image acquisition device according to the flight range, wherein the image acquisition device is used for collecting images of the unmanned aerial vehicle in real time, the second step of determining information of the position where the unmanned aerial vehicle is located currently and parameters of the current state of the unmanned aerial vehicle according to the images, collected by the image acquisition device in real time, of the unmanned aerial vehicle, the third step of determining adjustment information of the unmanned aerial vehicle according to the position information, the state parameters and a preset flight track of the unmanned aerial vehicle, and the fourth step of transmitting the adjustment information to the unmanned aerial vehicle so that the unmanned aerial vehicle can adjust the current course and speed according to the adjustment information to complete the preset flight track. Through the unmanned aerial vehicle space navigation method, the flight state of the unmanned aerial vehicle can be accurately mastered indoors or outdoors, and intelligent flight of the unmanned aerial vehicle is achieved.

The invention discloses a combat type unmanned aerial vehicle simulation training system and an operation method thereof. The system comprises a flight path planning equipment end, a flight control equipment end, a load and fire control equipment end, a visual simulation equipment end, a teaching management end and a route equipment end, wherein the flight path planning equipment end is used for planning flight tracks and is in communication connection with the flight control equipment end, the flight control equipment end controls the unmanned aerial vehicle to fly according to the flight track and simulates the environment in a flying process, the load and the flight control equipment end is used for carrying out load control and emission according to the flight track and the flight environment, the visual simulation equipment end is used for receiving onboard downlink data and is in communication connection with the teaching management terminal through a router. The system is high in simulation degree, and the real elevation data and the high-precision satellite film are adopted for manufacturing the three-dimensional terrain. An external field real-flight experience is provided. The system has an in-training task reminding function and a plurality of task mode selective training functions. One-to-many functions is provided, and the combat type unmanned aerial vehicle simulation training system can simultaneously access multiple groups of trainees for training.

The surveillance system provides a means to augment Automatic Dependent Surveillance-Broadcast (ADS-B) with “look alike ADS-B” or “pseudo ADS-B” surveillance transmissions for aircraft which may not be ADS-B equipped. The system uses ground based surveillance to determine the position of aircraft not equipped with ADS-B, then broadcasts the identification / positional information over the ADS-B data link. ADS-B equipped aircraft broadcast their own position over the ADS-B data link. The system enables aircraft equipped with ADS-B and Cockpit Display of Traffic Information (CDTI) to obtain surveillance information on all aircraft whether or not the proximate aircraft are equipped with ADS-B.

The invention provides a multi-unmanned aerial vehicle (UAV) track planning method based on a culture ant colony search mechanism, which includes the following steps: (1) carrying out mesh generationon a standard space according to a grid method; (2) building a multi-UAV track planning model, including the number of UAVs, the start and end points and a threat model; (3) initializing the start point and the end point; (4) initializing an ant colony algorithm, including: initializing an ant colony and calculating a heuristic factor and a guide factor; and (5) assigning all ants to an initial node, and updating taboo knowledge; selecting next node for transfer according to the taboo knowledge and the state transfer probability until there is no optional node or a destination node is selected, updating historical knowledge, and updating pheromones according to the historical knowledge; and outputting a shortest path if the maximum number of iterations is achieved, and continuing the process until U multi-UAV optimal multi-path tracks are obtained. The problem that it is difficult to find the optimal flight tracks of unmanned aerial vehicles due to slow search and heavy computing burden is solved, and multi-UAV track planning is realized.

The invention discloses a Doppler channel correlation two-stage dimension reduction method for an onboard multiple input multiple output (MIMO) radar. The method includes constructing an onboard MIMO radar clutter signal model and a target space time two-dimensional guide vector; utilizing Doppler filtering to conduct time domain dimension reduction processing on the echo data; resolving weight vectors formed by a space domain transmitting-receiving two-dimensional wave beam into a Kronecker product of a receiving weight and a transmitting weight, building a dyadic and square cost function, utilizing alternative computation to calculate the optimal weight, utilizing the optimal weight to conduct receiving and transmitting two-dimensional self-adaptation wave beam forming and restraining clutter. By means of the method, the dimension of the obtained weight vectors is greatly reduced, optimum covariance matrix estimation can be obtained through less samples, and the clutter restraining performance is greatly improved under small samples. Meanwhile, high-dimensional sampling covariance matrix inversion is avoided, and the calculation quantity is greatly reduced. By means of clutter restraining, further target detection, target location and tracking and flight track forming are facilitated. The method is applied to various actual systems like navigation systems.

The invention discloses a space-time synchronization matching method used for double unmanned aerial vehicle cooperation. According to the method, cooperation costs from the current node to all expandable nodes of each unmanned aerial vehicle are calculated according to a defined double unmanned aerial vehicle cooperation cost function, the expandable node with the lowest cooperation cost is selected as an expandable flight track node, and therefore current flight track sections of double unmanned aerial vehicles are obtained. The double unmanned aerial vehicle cooperation cost function overcomes the defect that in an existing method, a cost function only considers flight track planning constrain conditions of a single unmanned aerial vehicle, in this way, double unmanned aerial vehicle synchronization is added in the process of generating flight track points, and the method is closer to the real process. Flight tracks of the double unmanned aerial vehicles are divided into flight track sections, time cooperation is converted into a flight track cost which is embedded into the cost function of flight track section planning of each unmanned aerial vehicle, time deviation and flight track conflicts when the double unmanned aerial vehicles reach flight track section nodes are eliminated, and the problem that in the prior art, flight track planning and task cooperation are separated, and influences on flight track planning by space-time synchronization are not considered is solved.

The invention relates to an intelligent command system for air traffic control. The system comprises a monitoring data processing module, a flight plane data processing module which is in a communication connection with the monitoring data processing module, a 4D flight track prediction module which is in a communication connection with the monitoring data processing module and the flight plan data processing module, a short-term and mid-term conflict detection module which is in a communication connection with the monitoring data processing module, the flight plane data processing module and the 4D flight track prediction module, as well as a conflict solution calculation module which is in a communication connection with the flight plane data processing module, the short-term and mid-term conflict detection module. The system provided by the invention has the advantages that automatic control of aircrafts can be implemented in an existing airspace environment; and a probability for human factors to cause occurrence of unsafe events can be reduced.