441 results about "Air traffic control" patented technology

The invention belongs to the technical field of air traffic control and conduction, and particularly relates to an intelligent question answering system method for air traffic control and conduction business knowledge. According to the method and the system, the refined and context-aware information retrieval capability of the air traffic control communication service knowledge and the expert-level air traffic control communication service knowledge question and answer capability are provided, the knowledge management and application efficiency is effectively improved, and powerful support is provided for digital transformation of related services. Comprising the following steps: S1, a document content extraction and storage process; s2, a content retrieval and generation process; s3, content slice optimization is carried out through extraction and similarity calculation of adjacent paragraphs or contents, complete contents are in the same slice, and the content retrieval efficiency is improved; according to the method, the label library and the business rule library are continuously iteratively optimized, so that the provided service is always in the optimal state.

The embodiment of the invention provides a flight plan conflict detection method, device and equipment based on a low-altitude airspace grid, and is applied to the technical field of air traffic control. The method comprises the steps of constructing a low-altitude airspace grid set, planning a flight plan, dividing an airline flight stage into a plurality of flight segments, obtaining a space-time occupation grid set corresponding to each flight segment based on the flight speed and obtained flight target physical parameters, and combining to obtain a space-time occupation grid set of the airline flight stage. Based on the space-time occupancy range and the low-altitude airspace grid set, constructing a space-time occupancy grid set corresponding to other flight stages; the flight plan space-time occupation grid set is obtained through merging and compared with the historical space-time occupation grid set, if conflicts exist, conflict information is generated, and the flight plan is re-planned according to the conflict information, so that path overlapping and conflicts between tasks are effectively avoided, the turnover rate and the utilization rate of a low-altitude airspace are increased, and the flight planning efficiency is improved. And the dense flight requirement of the low-altitude unmanned aerial vehicle is met.

The disclosed invention provides a system and method for processing air traffic control (ATC) communications to ensure real-time validation of aircraft operations and improve pilot logbook accuracy. The system receives ATC voice communications through a digital radio system, converts them to text using a natural language processing model trained on aviation terminology, and extracts key operational data, including aircraft identifiers, instructions, and corrections. This data is correlated with Automatic Dependent Surveillance-Broadcast (ADS-B) and GPS data to verify compliance with ATC instructions. The system creates a continuous transcript of ATC-pilot communications, stitching together conversations across multiple frequencies. Deviations from ATC instructions are detected, generating alerts and logging the events. The method further provides automated reporting, archiving of communications, and enhanced safety metrics in immutable pilot logbooks, using blockchain technology for secure storage. This invention improves operational safety, transparency, and flight data integrity.

The invention provides an unmanned aerial vehicle route planning method and device, electronic equipment and a storage medium, and relates to the technical field of unmanned aerial vehicles, and the method comprises the steps: determining initial routes of a plurality of unmanned aerial vehicles according to a first constraint condition of the unmanned aerial vehicles; performing space-time grid division on each initial route to obtain a plurality of airspace grids; determining a safety distance between the unmanned aerial vehicles, wherein the safety distance is expressed as a plurality of airspace grids; and according to the second constraint condition of the unmanned aerial vehicle, determining the simultaneous flight route of the plurality of unmanned aerial vehicles. According to the invention, route planning of simultaneous flight of a large number of unmanned aerial vehicles is realized, the utilization rate of airspace is improved, and maximum utilization of route airspace resources is realized. Meanwhile, the low-altitude air traffic control system can perceive, monitor and control the flight of the unmanned aerial vehicle in real time within the defined route range, and unsafe conditions such as communication loss and out-of-control are prevented. The flight density of the unmanned aerial vehicle is improved on the premise of safe flight by finely dividing the airspace of the flight route, and airspace resources of the flight route are utilized to the maximum extent.

The invention relates to the field of flight path planning, aims to solve the problem that flight safety of an unmanned aerial vehicle and safety of other personnel or facilities on the ground and in the air are affected due to disordered flight paths of the unmanned aerial vehicle caused by scale increase of the unmanned aerial vehicle, and particularly relates to an intelligent flight path planning system for the unmanned aerial vehicle based on intelligent air traffic control. According to the method, pre-generation, correction, execution, real-time intervention and final execution results of the unmanned aerial vehicle route are recorded in the whole process, a closed-loop control process is formed, it is ensured that the flight process is traceable, abnormity can be traced back, and the task reliability in a complex airspace is improved; on the basis of an initial route, airspace management data is added to optimize a flying object in an airspace and a control area route for multiple times, and a real-time intervention unit is used for quick response, so that dynamic adjustment of flight route planning is realized, the collision risk and the danger occurrence probability are reduced, and the flight route planning efficiency is improved. And the overall dynamic supervision capability of the route planning system is improved.

The invention relates to an ADS-B (Automatic Dependent Surveillance-Broadcast)-based civil aviation flight pre-arrival data calculation method, which integrates ADS-B data, meteorological satellite data, airport runway state monitoring data and air traffic control real-time instruction data through multi-source data fusion, and dynamically adjusts the weight of each data source according to the flight stage of a flight. A dynamic adjustment time synchronization interval mechanism is adopted, a short synchronization interval is set in the take-off stage and the landing stage so as to capture rapidly-changed data, and the synchronization interval is prolonged in the cruise stage so as to optimize computing resources. Meanwhile, the deep learning model based on the Transform architecture utilizes a multi-head self-attention mechanism and position coding to enhance the feature capture capability, and reduces the calculation burden through a sparse activation strategy. The system is provided with a real-time monitoring layer, log records and visual analysis tools are integrated, and interpretability and traceability of the model are ensured. An efficient aviation management decision is supported, and the efficiency and safety of overall aviation traffic management are improved.

The invention relates to the technical field of flight simulation training, in particular to an air traffic control response system based on a flight simulator and a response training method. The method comprises the steps that a voice input module receives input voice audio data and sends the voice audio data to a voice recognition module; the voice recognition module recognizes and converts the voice audio data into voice text data; the instruction understanding module processes the voice text data to generate structured data corresponding to air-ground communication and sends the structured data to the instruction text generation module; the instruction text generation module generates a corresponding air traffic control instruction text according to the structured data; the voice synthesis module converts the air traffic control instruction text into corresponding voice audio data and sends the voice audio data to the voice output module; and the voice output module outputs the generated voice audio data. According to the invention, the recitation condition of the student can be intelligently evaluated, the workload of a teacher is effectively reduced, and the teacher can concentrate on guiding the flight operation of the student.

The invention relates to the technical field of air traffic control and voice recognition, in particular to an air traffic control instruction end-to-end voice recognition method under a high-noise condition, which comprises the following steps: preprocessing to-be-recognized voice, and extracting to obtain original voice frequency characteristics; carrying out noise reduction intensity control, frequency band gain control and fundamental tone tracking processing on the original voice frequency characteristics by adopting a self-adaptive attention noise reduction module to obtain noise-reduced voice; preprocessing the noise-reduced voice, and extracting to obtain noise-reduced voice frequency characteristics; a voice recognition module is adopted to carry out shared encoder coding, connection time sequence classification decoder decoding and attention-based encoder-decoder decoding on the noise reduction voice frequency characteristics, and an output voice recognition transcription text is obtained; according to the invention, the voice recognition precision of the air traffic control instruction under the high-noise condition can be improved.

The invention discloses a method for determining an air operation program under shielding of a civil aviation radar by an obstacle, and belongs to the technical field of civil aviation air traffic control monitoring. The method comprises the following steps: S1, extracting air operation program parameters of a civil aviation airport needing to be analyzed, and establishing a flight path model; s2, establishing a radar model according to radar equipment parameters to be analyzed; s3, extracting parameters of an obstacle needing to be analyzed, and establishing an obstacle model; s4, calculating a horizontal shielding range and a vertical shielding range of shielding the radar by the obstacle so as to determine a space shielding range of shielding the radar by the obstacle; and S5, accurately determining the air operation program influenced by the obstacle according to the space shielding range of the obstacle shielding radar. According to the method, the affected air operation program can be accurately locked from hundreds of programs, and the analysis efficiency and accuracy of radar professionals are greatly improved.

Systems and methods for detecting anomalies in aviation data communication systems (e.g., air traffic control surveillance systems), include a processor receiving device status information. A variational autoencoder receives and optimizes the device status information and determines whether it qualifies as an anomaly. Optimized device status information is compared to either non-anomalous or anomalous device status data in a latent space of the variational autoencoder. The latent space preferably includes an n-D point scatter plot and hidden vector values. The processor optimizes the device status information by generating a plurality of probabilistic models of the device status information and determining which of the plurality of models is optimal. A game theoretic optimization is applied to the plurality of models, and the best model is used to generate the n-D point scatter plot in latent space. An image gradient sobel edge detector preprocesses the device status information prior to optimization.

The invention relates to a critical flight identification and guarantee plan inversion method based on LTOT, and the method comprises the steps: data integration and preprocessing, critical flight identification, multi-objective optimization, guarantee plan generation, real-time monitoring and feedback, emergency response and the like. Intelligent monitoring and optimal scheduling of flight states and airport resources are realized by using the multi-layer technology and large model layer technologies such as a deep neural network, reinforcement learning, ensemble learning and natural language processing, and the system has real-time data acquisition, risk prediction, dynamic threshold adjustment and a cross-department collaboration platform, can quickly respond to emergencies, optimizes resource allocation, and improves the scheduling efficiency. The flight punctuality rate and the operation efficiency are improved, the data security and privacy are ensured, and the intelligent level and the emergency response capability of aviation scheduling are remarkably improved.

The invention discloses a method for designing an airport climate-adaptive target detection system, and aims to solve the problem that an airport monitoring system is poor in target detection effect under atrocious weather conditions. According to the system, input video streams are analyzed in real time through a weather classification algorithm, real-time weather conditions such as sunny days, foggy days and rainy days can be recognized, real-time weather forecast information is obtained through an API, and the real-time weather category of an airport is obtained through a weather classification algorithm module; according to the weather category, in combination with a preset image enhancement algorithm, selecting a matched algorithm to process the image; inputting the enhanced image into a target detection algorithm, and carrying out the recognition and detection of a target object in the airport; effective target data of image detection and data of the millimeter wave radar and the laser radar are subjected to fusion processing, and finally a target detection result is output. According to the method, an adaptive climate image enhancement mode is adopted, the airport scene target detection effect under various climate conditions is improved, and the airport governance efficiency and the troubleshooting capability of air traffic control potential safety hazards are improved.

The invention provides an intelligent intelligent supervision system for civil aviation VoIP communication equipment, relates to the basic field of civil aviation air traffic control equipment, and solves the limitation problems of non-centralized supervision, imperfect supervision, non-autonomous supervision and the like existing in an existing supervision mode. The system comprises a system architecture module which adopts a layered modular design to construct a double-layer system comprising a top layer management architecture and a bottom layer operation architecture; the function service module comprises an equipment state monitoring unit, a risk assessment engine and an operation and maintenance management unit; the data processing architecture forms a multi-stage processing channel by a data acquisition layer, a data transmission layer, a data storage layer, a data calculation layer and a data application layer which are connected in sequence; the technical support system comprises a micro-service component group, a continuous integration platform and a security authentication module. The intelligent supervision network architecture of the VoIP communication equipment is subjected to brand-new autonomous design, transformation from passive response to active management is completed, and the supervision efficiency and the treatment efficiency are improved.

A method for an Unmanned Aerial Vehicle, UAV, for generating a temporary flight-plan for a region is provided. The method includes determining whether any air traffic control station is emitting a flight-plan for the region. If it is determined that no air traffic control station is emitting a flight-plan for the region, the method further includes determining a score for the UAV based on properties of the UAV and receiving scores from other UAVs within the region. Additionally, the method includes determining whether the UAV is a master UAV or a slave UAV for generating the temporary flight-plan based on the calculated score for the UAV and the received scores from the other UAVs. If it is determined that the UAV is a master UAV, the method includes performing a first task in generating the temporary flight-plan.

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.

Methods, devices, and systems for air traffic control (ATC) flight management are described herein. One device includes a memory, and a processor to execute executable instructions stored in the memory to receive airport information associated with an airport, generate, using the airport information, an ATC flight management analysis that includes an airport map showing locations of aircraft at the airport and a card panel including a number of flight cards, where each respective one of the number of flight cards corresponds to a different respective one of the aircraft at the airport, and a user interface to display the ATC flight management analysis in a single integrated display.

To provide an air mobility control system that can perform an emergency landing promptly in the event of an emergency when an abnormality occurs in an aircraft during the flight of an air mobility.SOLUTION: An air mobility control system 100 and 100A includes: an air mobility control unit 101 that performs flight control of an air mobility 106; an air traffic control unit 102 that performs air traffic control of the air mobility 106 and selects a flight route and an emergency landing site based on information obtained from the air mobility control unit 101; a ground traffic control unit 104 that generates instructions for ground traffic to operate based on the flight route and the emergency landing site of the air mobility 106; a ground traffic management unit 105 that controls ground traffic means based on the instructions from the ground traffic control unit 104; and an interface 103 between air traffic control and ground traffic control that provides intercommunication of information between the air traffic control unit 102 and the ground traffic control unit 104.SELECTED DRAWING: Figure 1

The invention relates to the technical field of traffic control, in particular to an airspace situation prediction method and system based on a self-adaptive grid, and the method comprises the following steps: collecting the information of all aircrafts in a current airspace, including the number, speed, x coordinate, y coordinate, z coordinate, course, pitch angle and time of the aircrafts; according to the x coordinate, the y coordinate and the z coordinate of the aircraft, mapping the acquired information of the aircraft into grids of a pre-constructed airspace basic grid network, and obtaining an input feature sequence; and inputting the input feature sequence into an airspace grid situation prediction model based on 3D CNN-GCN-Transform, and outputting to obtain an airspace situation prediction result. According to the invention, accurate prediction of airspace situation change can be realized, and technical support is provided for air traffic control.

Relates to the technical field of airborne situation awareness of large-scale airport scene operation, in particular to an airport scene airborne situation enhancement method based on multi-modal information fusion, which comprises the following steps: acquiring an air traffic control instruction text and a sliding track image of an aircraft, and respectively performing feature extraction on the air traffic control instruction text and the sliding track image to obtain a feature extraction result; obtaining text features and visual features; performing multi-modal feature fusion on the text features and the visual features based on an adaptive Transform network to obtain multi-modal features; performing intention recognition and key parameter analysis on the multi-modal features to obtain aircraft behavior intention and aircraft key parameters; taking the behavior intention of the aircraft and the key parameters of the aircraft as airborne situation auxiliary information, and providing assistance for subsequent flight decision making; according to the invention, the understanding capability of the air traffic control instruction can be improved.

The invention discloses portable emergency rescue unmanned aerial vehicle cooperative command equipment which comprises a multi-heterogeneous unmanned aerial vehicle flight control docking system, an unmanned aerial vehicle load data large-capacity high-concurrency fusion processing system, an emergency field air traffic control flight service system, a multi-vehicle cooperative operation command system and a digital battlefield airspace fusion flight situation digital twin system. The five systems are subjected to hardware and environment installation adaptation and are jointly integrated into an unmanned aerial vehicle cooperative command equipment platform, environment perception, path planning, task allocation, cooperative decision making, cooperative positioning, formation control, collision avoidance and the like are combined together, the control effect of distributed control is enhanced, and the cluster stability is improved; moreover, an emergency field digital base is provided for superposing the airspace flight state, and digital airspace fusion flight recovery diagnosis and deduction analysis are provided, so that the system has the real-time sensing capability of the field condition, and support is provided for emergency field commanders to make decisions.

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.

The invention discloses a real-time aviation flow prediction method based on aviation situation awareness, and the method comprises the steps: constructing a flow data set fusing spatial-temporal characteristics, and achieving the efficient conversion from trajectory data to aviation flow data based on time slice division; extracting multi-source spatio-temporal features; a light GBM is adopted to construct a prediction model, and the core lies in that a Tweedie loss function is used to model the zero expansion and long tail distribution characteristics of flow data, and the robustness of the model is ensured through five-fold cross validation; establishing a multi-dimensional evaluation system; in the application stage, the airspace is divided into dynamic grids, and flight traffic in a plurality of minutes in the future in the airspace is predicted in real time in combination with radar return trajectory data. The method supports dynamic feature extraction and flow prediction based on real-time radar data, can effectively support an aviation flow management and control decision through actual measurement verification, can quickly respond when the airspace flow changes, meets the timeliness demand of dynamic management and control of air traffic control, and remarkably improves the scientificity and response speed of air traffic control decision.

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 discloses a quantitative evaluation method for a high-altitude air route emergency handling effect. The method comprises the following steps: dividing emergency types; establishing an evaluation index system for handling different types of emergencies; setting a secondary evaluation index calculation method and an evaluation standard; objective operation data of each secondary evaluation index is extracted and calculated; calculating the specific numerical value of each secondary evaluation index; and obtaining a quantitative score of the emergency command level of the controller in the high-altitude route emergency. The method solves the problem that the ability and effect of the controller to deal with unconventional emergencies of a high-altitude air route cannot be accurately and quantitatively described in the existing air traffic control command work, and provides support for scientifically evaluating the skills of the controller and guaranteeing the safe operation of an air traffic control system. An air traffic control unit can use the method to comprehensively evaluate the emergency command capability of the controller, and can apply the method to annual retraining or skill fighting of the controller, so that special skill training and targeted review training can be conveniently organized to improve the training effect and quality.

The invention provides an air traffic control dialogue type speech recognition method and device based on multi-task learning. Cooperative optimization of voice segmentation and content recognition is realized by constructing a joint learning model of a voice feature representation learning module and a voice activity detection module. The method comprises the following steps: firstly, designing a segmented shielding comparison pre-training strategy, and constructing a supervision signal through a product quantization codebook, so that a speech feature representation learning module learns fine-grained acoustic features in unlabeled data; secondly, a double-branch joint training mode fine tuning model is designed, a main branch optimizes a voice recognition task through connection time sequence classification loss, an auxiliary branch improves voice segment boundary detection precision through binary cross entropy loss, and meanwhile, a dynamic task weight adjustment strategy is combined to balance a multi-target optimization direction; and finally, innovatively introducing a dynamic local window attention mechanism, and focusing context modeling of an effective voice segment according to a real-time segmentation index.

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.