220 results about "Air traffic control" patented technology

The invention provides an air traffic control scene instruction recommendation method and system combined with a knowledge graph, and relates to the technical field of air traffic control. The method comprises the following steps: firstly, establishing a dynamic matching relationship between current air traffic state data (including flight real-time operation parameters, airspace use state parameters and meteorological influence parameters) and an association rule set (including air traffic control rule entries, historical instruction execution constraint conditions and airspace resource allocation criteria), and generating a preliminary instruction set; adjusting the initial instruction set in real time according to real-time air traffic state change data (including flight position change parameters, airspace flow fluctuation parameters and meteorological condition updating parameters) to obtain an adjusted instruction set; and then verifying the compatibility between the adjusted instruction set and airspace use constraint conditions (including airspace capacity limiting parameters, flight interval safety parameters and equipment operation state parameters), outputting a compatible instruction set to cooperate as a target recommendation instruction set, and assisting air traffic control personnel to make a control instruction decision.

The invention discloses a low-altitude economic intelligent scheduling method based on multi-dimensional data fusion and dynamic topological optimization, and belongs to the technical field of aircraft air traffic control, and the method comprises the following steps: S1, collecting and fusing multi-dimensional data, including meteorological data, equipment data, airspace data, task data and historical data, S2, constructing a dynamic airspace topological network based on the fused data, the topology network comprises a vertex set and an edge set, vertexes represent unmanned aerial vehicles, and edges represent cooperative paths between the unmanned aerial vehicles, S3, generating a global optimal scheduling strategy through a multi-objective optimization algorithm according to the dynamic airspace topology network, S4, executing the global optimal scheduling strategy, updating historical data and model parameters after a task is completed, and S5, executing the global optimal scheduling strategy according to the updated historical data and model parameters. And closed-loop feedback is formed. Multi-target dynamic balance of unmanned aerial vehicle dispatching safety, efficiency and energy consumption is achieved through multi-dimensional data fusion and dynamic topological optimization, the system supports full-process closed-loop automation, and the accident rate and resource consumption are remarkably reduced.

The invention relates to the technical field of low-altitude safety, and provides an aircraft optimal trajectory screening method and system based on adjustable phase quantum search. Candidate trajectories are generated according to flight mission constraints, cost values are calculated, and Boolean markers are distributed based on cost threshold values to identify high-quality solutions; performing iterative search and measurement on the balanced quantum superposition state of the coding track index by utilizing a Grover quantum search algorithm based on the adjusted search phase to obtain an output index; and mapping the index into a track, obtaining an optimized track through classic local optimization, adaptively adjusting the phase parameter and the cost threshold value based on performance evaluation, and repeatedly executing until an end condition is met, thereby determining an optimal track. On-line reconfiguration of a strategy is realized by introducing an adjustable phase mechanism, a feedback closed loop is established to realize adaptive optimization of parameters, and the real-time requirements of scenes such as urban air traffic control and unmanned aerial vehicle clusters are met.

The invention provides a voice instruction intelligent analysis method and system applied to an air traffic control scene, relates to the technical field of air traffic control, and aims at the characteristics of voice instruction interaction between a controller and a flight crew in the air traffic control scene to construct an instruction interaction expectation model. The instruction interaction expectation model comprises an instruction sequence association rule and a semantic constraint condition set which are generated based on historical controlled call data, and an interaction feature set of speaker identity features, instruction component time sequence features, voice intonation fluctuation features and the like in a real-time capture voice interaction process; inputting an instruction interaction expectation model for dynamic matching and deviation identification, generating an interaction deviation analysis result, triggering an intention clarification and instruction confirmation process based on the analysis result, obtaining a complete instruction component set, generating an instruction analysis result meeting an air traffic control data exchange standard after structured conversion processing, and pushing the instruction analysis result to an air traffic control automation system. The accuracy and efficiency of air traffic control voice instruction analysis are effectively improved.

A system and a method include a monitoring control unit configured to compare an initial flight plan, as generated by a flight planner for an aircraft, and an assessed flight plan, as determined by air traffic control. The monitoring control unit is further configured to determine one or more alternate initial flight plans that differ from the initial flight plan in response to determining one or more differences between the initial flight plan and the assessed flight plan.

The invention discloses an unmanned area unmanned aerial vehicle non-visual flight dynamic threat assessment management and control method, and belongs to the technical field of air traffic control systems, and the method comprises the steps: obtaining the multi-source sensing data in the flight process of an unmanned aerial vehicle in real time, and generating the state reference parameters of the unmanned aerial vehicle; generating a multi-source quantitative threat data set based on the multi-source sensing data; the state reference parameters of the unmanned aerial vehicle and the multi-source quantitative threat data set are fused to generate a comprehensive flight risk assessment result; generating an adaptive flight management and control strategy based on the comprehensive flight risk assessment result; generating a dynamic adjustment control instruction set based on the adaptive flight control strategy; and performing feedback adjustment based on the execution effect of the dynamic adjustment control instruction set. The technical means of quantifying multi-source threats, carrying out comprehensive risk assessment, generating a self-adaptive control strategy and carrying out feedback optimization based on an execution effect are adopted, so that the autonomous flight safety and intelligent level of the unmanned aerial vehicle in a complex dynamic environment can be remarkably improved.

The invention provides a dynamic path planning method and system based on a generative adversarial network model, and the method comprises the steps: firstly receiving a flight task instruction of an air traffic control system and an airspace real-time operation data set, inputting the flight task instruction and the airspace real-time operation data set into a generator unit of a generative adversarial network, and generating a plurality of candidate dynamic flight paths; and calling a discriminator unit to evaluate the candidate dynamic flight paths and output comprehensive evaluation values by taking the airspace control constraint rule and the path operation efficiency index as references, feeding back the candidate dynamic flight path with the highest comprehensive evaluation value to the generator unit to adjust parameters, and repeating evaluation and adjustment operations until a preset optimization threshold value is reached. And the final path is sent to an air traffic control command system, so that the airspace utilization rate and the flight operation efficiency can be improved, and the flight safety is guaranteed.

Systems, methods, and non-transitory computer readable media for identifying a cockpit alert context during an aircraft mission are provided. The system includes a controller configured to: store message content in a clearance look-up table for one or more clearance messages received from air traffic control (ATC) during the aircraft mission that contain cockpit data about which an avionic system in an aircraft may later sense and generate a cockpit system alert for display on a cockpit display device; monitor a plurality of avionic systems in the aircraft for a cockpit system alert; retrieve an ATC clearance message from the clearance look-up table that corresponds to a detected cockpit system alert when a cockpit system alert is detected; and signal an aircraft display device to display the ATC clearance message in a visually distinguishable manner that indicates that the displayed ATC clearance message relates to a detected cockpit system alert.

The invention discloses a dynamic planning method for an approaching track of a vertical take-off and landing airport. The method comprises the following steps of: constructing a structured airspace which takes the airport as a center and comprises a plurality of layers of annular waiting rings; assigning a serial number to the aircraft requesting approach and assigning the serial number to a specific waiting sector; dynamically planning an interlayer transfer track based on a multi-constraint optimization model; the airspace state is monitored in real time, and dynamic re-planning is triggered in case of emergencies; and finally generating a final approach trajectory to guide the aircraft to complete landing. According to the method, a funnel-shaped structured airspace which is formed by a plurality of layers of annular waiting circles and takes an airport as a center is constructed, a traditional disordered approaching airspace is converted into an air corridor with a clear spatial level, and each waiting circle is further divided into independently managed sector seats; a plurality of vertical take-off and landing aircrafts can obtain isolated waiting positions in a three-dimensional airspace, so that the complexity of air traffic control command is greatly simplified, and the aircrafts are prevented from scrambling and flying conflicts in the airspace above an airport.

A method for communication between an air traffic control system and a communication module, the communication method includes a step of determining environmental optimization time slots based on the air traffic absorption capacities of the various flight information regions, the environmental optimization time slots at least partially covering one or more flight information regions, each environmental optimization time slot having an associated efficiency level; a step of negotiation, between the pilot via the communication module and the air traffic control system, to negotiate changes to the flight plan on the basis of the environmental optimization time slots and the environmental optimization levels of the environmental optimization time slots.

The invention relates to a track prediction method based on multi-resolution hierarchical reasoning. The method comprises the steps that firstly, historical track data are acquired and preprocessed, and a track prediction data set is obtained; then, a track prediction model based on multi-resolution hierarchical reasoning is constructed, and the track prediction model comprises a track encoder module oriented to trend extraction, a probability type key point predictor module based on a mixed density network, a dynamic sampling module, a linear interpolation module based on learnable residual errors and a Transformer decoder module; then, inputting the track prediction data set into the track prediction model based on multi-resolution hierarchical reasoning for model training, and optimizing model parameters in combination with an uncertainty loss function; and finally, pre-processing real-time track data, inputting the pre-processed real-time track data into the trained track prediction model based on multi-resolution hierarchical reasoning, and outputting to obtain a future track prediction result. And the prediction performance and precision of the flight path in a complex air traffic control scene are improved.

A method for reducing cost of airflight, the method comprising reducing cost of Air Traffic Control (ATC) and / or reducing maintenance cost of the Air Traffic Control (ATC)'s radar system. Reducing of maintenance cost may include reducing operational cost of estimation, based on data, of bias (e.g.) in the Air Traffic Control (ATC) radar system including at least once, basing the estimation of bias (e.g.) at least partly on data from commercial aircraft / s, to reduce or eliminate need for flying dedicated calibration aircraft to provide a source of data for the bias estimation and / or parameter Calibration.

The invention provides a flight management system based on cloud-edge collaboration and an air route planning method thereof. The flight management system comprises an airborne end, a cloud platform and an edge computing node, the route planning method of the flight management system comprises the following steps: step 1, calculating an optimal flight path by a cloud platform, and predicting a meteorological condition on the flight route and corresponding real-time airspace information; 2, the cloud platform completes the route optimization of the current flight according to the data in the step 1, and sends the data to an edge computing node and an airborne end; step 3, when an emergency occurs, the edge computing node computes a corresponding release path and issues the corresponding release path to the airborne end and the air traffic control center, and the air traffic control center determines whether the aircraft executes the release path or not; according to the method, the defects of a traditional FMS in the aspects of dynamic planning capability, computing power limitation and the like can be overcome, and an extensible, high-reliability and low-cost solution is provided for a next-generation flight management system.

The invention discloses an ADS-B (Automatic Dependent Surveillance-Broadcast)-based unmanned aerial vehicle and manned aerial vehicle fusion airspace monitoring method, and belongs to the technical field of air traffic control. According to the method, attitude vectors of a manned aerial vehicle are collected through a ground ADS-B receiver and an unmanned aerial vehicle broadcast double channel, and relative measurement vectors of a self-sensing sensor of the unmanned aerial vehicle are combined and converted into absolute attitude vectors under a global coordinate system; carrying out weighted fusion on the signal credibility based on the three types of acquisition channels to obtain an accurate attitude vector; extracting position, speed and course angle change sequence features, and calculating various flight intention probabilities; predicting a mixed future position and a covariance based on the intention probability; and finally, constructing a space kernel function and introducing a directional amplification factor to generate an intention risk field. The attitude vector precision is improved through multi-source information fusion, modeling is optimized in combination with the intention probability and the directivity risk amplification mechanism, and fusion airspace monitoring accuracy and risk assessment reliability are remarkably improved.

The invention discloses a dynamic combination site optimization method and device for an air traffic control multi-point positioning system, and the method comprises the steps: building a site dynamic weight evaluation model, so as to determine a site weight; establishing a geometric accuracy factor lookup table for dynamically extracting geometric accuracy factors of the site combination; and determining an optimal site combination by adopting a self-adaptive combination optimization algorithm. According to the method, through a dynamic site optimization mechanism, site signal quality, geometric distribution and redundancy are evaluated in real time, site combinations participating in positioning are adjusted in a self-adaptive mode, and robustness in a complex scene is improved; according to the method, a multi-objective optimization model based on dynamic weight is adopted, and parameters such as a signal time difference of arrival error, a geometric accuracy factor and computing resource consumption are combined, so that rapid screening of an optimal site combination is realized, the computing load is effectively reduced, and the positioning reliability is guaranteed.

An aviation anomaly detection system may include an interface configured to receive audio communications between an air traffic control station and a plurality of aircraft, a speech-to-text converter configured to convert the received audio communications from the interface to text data, and a processor. The processor may be configured to determine at least one aviation anomaly from the text data with a variational autoencoder (VAE) deep learning model, and generate an alert based upon the at least one aviation anomaly.

1. The name of the design product: air traffic control detector. 2. The use of the design product: for detection and analysis of air traffic control products. 3. The design points of the design product: in shape. 4. The picture or photo that best indicates the design points: perspective view.

This invention relates to the field of computer graphics data processing technology, specifically a method for hot-plugging dynamic outer contour meshes driven by three-dimensional spatial domain and time slices. The steps include: S1, receiving air traffic control message information in real time via a transmission protocol, converting geographic coordinates into target world coordinates, and simultaneously generating management files; S2, constructing a spatial domain mesh in real time based on the four types of management files using a combination of outer contour extrusion and ear-cutting methods; S3, mapping the spatial domain ID and time slice from the message to the spatial domain mesh constructed in S2, constructing a double-key hash index of spatial domain ID and time slice, which serves as the sole basis for the hot-plug manager to determine whether to update or create a mesh, dynamically executing spatial domain mesh hot-plugging. Employing the contour extrusion-ear-cutting method and vertex cache reuse mechanism, combined with the "spatial domain ID and time slice" double-key hash index, it supports dynamic construction and hot-plugging operations of the mesh model, meeting the low-latency rendering requirements of real-time air traffic control data.

The utility model discloses a crawling ladder type low-altitude unmanned control tower integrally designed with a lifting type lamp panel system, the control tower comprises a tower column, the lifting type lamp panel system, lifting type maintenance platforms and a multi-section vertical crawling ladder matched with a lifting device are arranged on the tower column, so that maintenance personnel can conveniently reach each maintenance platform to maintain the control tower; two equipment mounting platforms are arranged below the maintenance platform at the top of the tower column, and an unmanned aerial vehicle detection radar, an adversarial radar, a high-power bird repelling system, a detection monitoring radar, an unmanned aerial vehicle positioning system, an aviation obstruction light, a 360-degree high-definition monitoring system and the like can be loaded on the equipment mounting platforms so as to realize the functions of air traffic control positioning, communication command and the like; a communication base station antenna, an ADS-B (Automatic Dependent Surveillance-Broadcast) antenna, an air traffic control multipoint positioning antenna, a phased array monitoring radar, a lightning rod and the like can be arranged on the equipment mounting rack on the extension rod at the top of the tower column; therefore, the unmanned control tower is reasonable in structure, rich in equipment, capable of effectively meeting the monitoring, communication and illumination requirements and convenient to maintain.

To provide a control device for facilitating addition and subtraction of a control object airspace by a computer.SOLUTION: A control device includes: an input section for inputting a control object airspace map which indicates an airspace for a flying body to fly; a division section for dividing the control object airspace map into a plurality of convex closed areas; a classification section for respectively classifying the convex closed areas divided by the division section into one or more areas among a merging convex closed area, a branch convex closed area, a translation convex closed area, a taking-off / landing convex closed area, and an uninvadable convex closed area; and an output section for outputting a control object airspace map on which a classification result of the convex closed areas is reflected.SELECTED DRAWING: Figure 11

The invention relates to the technical field of computer graphic data processing, and belongs to a three-dimensional airspace and time slice driven dynamic outer contour grid hot plug method, which comprises the following steps of: S1, receiving air traffic control message information in real time through a transmission protocol, converting geographic coordinates into target world coordinates, and generating a management file at the same time; s2, based on the four types of management files, constructing an airspace grid in real time by combining outer contour extrusion with an ear cutting method; and S3, mapping with the airspace grid constructed in the S2 according to an airspace ID and a time slice transmitted by a message, constructing an airspace ID and time slice double-bond hash index, and dynamically executing airspace grid hot plugging as a unique basis for a hot plugging manager to judge whether to update or newly build the grid. A contour extrusion-ear cutting method and a vertex cache multiplexing mechanism are adopted, in combination with'airspace ID and time slice 'double-bond hash index, dynamic construction and hot plug operation of a grid model are supported, and the low-delay rendering requirement of real-time air traffic control data is met.

The invention provides a track segmentation method, system and device based on space-time perception and adaptive learning, and belongs to the technical field of artificial intelligence and track data processing. The track segmentation method comprises the following steps: preprocessing original track data, and dividing an unlabeled data set and a labeled data set; the method comprises the following steps: constructing an encoder-decoder model based on Transform, and carrying out self-supervision pre-training through mask reconstruction and a contrast learning task; introducing a segmentation decision head, and performing supervised fine tuning on the pre-training model by using a small amount of labeled data; after model deployment, continuous adaptive learning is realized by constructing a dynamic database and regularly performing online mixing loss fine adjustment. The method effectively reduces the dependence of the model on labeled data, improves the generalization ability, long-term stability and decision interpretability in a complex scene, and is suitable for air traffic control, target intention recognition, trajectory prediction and other scenes.

The present application relates to the technical field of aviation safety and artificial intelligence, in particular to an ADS-B time series data adversarial sample generation method based on improved WGAN-GP, comprising the following steps: obtaining ADS-B historical flight data, extracting the longitude, latitude, height, speed and heading five-dimensional features to construct a time series data set; building an adversarial sample generation model based on an improved Wasserstein distance generative adversarial network, and configuring a multi-objective composite loss function for the generator; the present application builds a generator and a discriminator based on LSTM, designs a composite loss function that integrates adversarial loss, concealment loss and time series smoothness loss, adopts gradient penalty and asymmetric update strategy to train the model, and the generated adversarial sample has high concealment and physical consistency, can effectively avoid various unsupervised anomaly detection models, the model training is stable, and technical support is provided for building a safer air traffic control defense mechanism.

The invention relates to the technical field of air traffic control, in particular to a multi-mode fusion real-time intelligent monitoring system for air traffic control command. According to the method, a three-dimensional intelligent analysis system of interface situation analysis-voice instruction recognition and understanding-air traffic control information fusion is constructed, and a safety monitoring closed loop of an air traffic control command whole process is realized on the premise that an existing system architecture is not changed; and real-time deduction and risk early warning of the airspace security situation are realized. The generated early warning information is synchronously pushed to a radar controller, an assistant controller and a main controller in a standardized visual and audio coding form through a newly-added safety information prompting module, a three-in-one cooperative cognitive space is constructed, the problem of information asymmetry among multiple seats and multiple on-duty roles in a traditional mode is effectively solved, and the safety of the system is improved. And important technical guarantee is provided for safe operation of civil and aviation pipes.

The invention provides a multi-link automatic switching device and method for an air traffic control system. A multi-path input interface module accesses a message link, and the output end of the multi-path input interface module is connected with a core processing and control module; the core processing and control module executes data acquisition, state judgment and algorithm decision; the output interface module is used for receiving an instruction of the core processing and control module and transmitting data of a selected link to post-stage communication equipment; the emergency bypass circuit is used for communicating a specified primary link input port with the output interface module through a physical switch; the communication module core processing and control module performs data interaction with a remote monitoring host through the communication module; when the system runs normally, the link state is monitored in real time, and data of the RS-232 interfaces are read; and when the data of the input port is abnormal, the application layer controls the multi-path input module to quickly switch the output signal to the optimal link interface. According to the method, the message data flow can be kept smooth through physical direct connection under the extreme condition of complete downtime of the device.

An artificially intelligent air traffic control system is provided. The system can include an artificially intelligent (AI) sensor configured to detect and remotely communicate with one or more flying vehicles and an AI local server communicatively coupled to the AI sensor. The artificially intelligent local server can send control instructions including authorization for the one or more flying vehicles to fly in an airspace and a flight path to fly through the airspace. The system can also include an AI cloud server communicatively coupled to the AI local server. The AI cloud server can receive data from the AI local server and the AI sensor associated with the one or more flying vehicles. The AI local server can send the authorization and the flight path to the one or more flying vehicles via the AI sensor based on the received data stored on the AI cloud server.

Systems, devices, methods, and computer-readable media provide improved flight path selections. A system includes a graph representation operator configured to generate a graph of potential flight paths and actual obstacles in the potential flight paths, the potential flight paths extending from a takeoff location to a destination location, a predictive analysis model configured to receive the graph and environmental data and generate predictions of future environmental conditions based on the graph and the environmental data, a cost function and heuristic estimate operator configured to determine costs associated with flight paths of the potential flight paths based on the future environmental conditions, and a predictive pathfinding model configured to identify a flight path of the potential paths based on the costs, aircraft specific performance data, air traffic control constraints, current environmental conditions, and the future environmental conditions.

The application relates to the field of low-altitude safety technology and provides an aircraft optimal trajectory screening method and system based on an adjustable phase quantum search. A candidate trajectory is generated according to flight task constraints, and a generation cost is calculated, a high-quality solution is identified based on a cost threshold value, an adjustment search phase is based on, a balanced quantum superposition state of an encoded trajectory index is iteratively searched and measured by using a Grover quantum search algorithm to obtain an output index, the index is mapped to a trajectory, and an optimized trajectory is obtained through classical local optimization, a phase parameter and a cost threshold value are adaptively adjusted based on performance evaluation and repeated execution until an optimal trajectory is determined by meeting an end condition. The adjustable phase mechanism is introduced to realize online reconfiguration of the strategy, a feedback closed loop is established to realize adaptive optimization of the parameters, and the real-time requirements of urban air traffic control, unmanned aerial vehicle clusters and other scenes are met.

The application provides an air traffic control primary radar signal processing automatic test method and system, relates to the radar test field, and solves the technical problems of fragmentation of the prior art process, single evaluation dimension and poor traceability. The method specifically comprises: obtaining radar test data and structured test configuration; recursively analyzing the test configuration to generate an instruction set; loading data and executing signal replay according to the instructions to drive the software; synchronously collecting video data and processing results of each stage to form a multi-dimensional feature sequence; correlating and analyzing the two and extracting features to generate a holographic feature vector sequence; progressively comparing the sequence with a baseline determination model in layers to obtain a test determination result; integrating test item identifiers, video data, multi-dimensional feature sequences, holographic feature vector sequences and test determination results to record and generate a final test log report. An end-to-end automatic, multi-dimensional deep analysis and full-link evidence tracing radar automatic test method is realized.

This invention relates to a method and system for tracking partially distinguishable group targets based on augmented label RFS. The method includes: acquiring a set of measurement points; judging the set of measurement points to obtain measurement points for distinguishable and indistinguishable targets; clustering the measurement points of indistinguishable targets and calculating the centroid as equivalent measurement; recursively estimating the target state using a GALMB filter to obtain a set of estimated target states; updating the target type in the augmented label using the Bernoulli elements obtained from updating the equivalent measurement in the GALMB filter update step; dividing the estimated target state set into group structures and updating the group structure part in the filter label to obtain target trajectory, state, and group structure information. This invention is applicable to complex application scenarios such as air defense early warning, air traffic control, and battlefield situational awareness.