346 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 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 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 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.

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.

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 provides a flight time adjusting method and device, electronic equipment and a storage medium, and the method comprises the steps: carrying out the all-day data fusion of the basic capacity of an airport, the temporary air traffic control capacity and the ground guarantee capability, and taking the capacity with the minimum value as the capacity fusion data in each preset time period; based on the guarantee plan data, determining the total flight plan amount in each preset time period; performing evaluation processing based on the capacity fusion data and the total flight plan amount, and determining the flight calling-out amount of each airline in the excessive time period and the flight calling-in amount of each airline in the spare time period; and scoring each flight of each airline in the excess time period, and determining a plurality of timing flights based on the timing score of each flight of each airline and the number of scheduled flights of the airlines. Intelligent recommendation of the flight time adjustment scheme is realized, the flight time adjustment efficiency is improved, the influence of flight delay is minimized, and the problem of low manual operation efficiency is solved.

The embodiment of the invention discloses a flow refined prediction method driven by air traffic flow pattern recognition, and relates to the technical field of air traffic situation awareness and flow management. According to the method, spatial-temporal characteristics in a flight path are efficiently extracted, a local flow mode is accurately identified, a graph model is constructed based on a representative flow mode, and fine-grained prediction of traffic flow in an airspace is realized, so that the fineness and dynamic response capability of local region regulation and control are greatly improved. The method is especially suitable for deep analysis of flight path data in an airspace sector, and provides accurate auxiliary decision support for air traffic control, route planning and airspace design.

A method includes receiving, by an air traffic control (ATC) system and from an unmanned aerial system (UAS), a routing request, the routing request including a first start position and a first end position, generating a three-dimensional path based on a directed airspace reservation graph and the routing request, the path beginning at the first start position, concluding at the first end position, and including a set of path segments, modifying the directed airspace reservation graph to include at least part of the set of path segments, and causing the UAS to travel from the first start position to the first end position in accordance with the at least part of the set of path segments.

In an embodiment a remote pilot station includes a communication device configured to communicate with an aircraft and an air traffic control tower configured to control the aircraft, and a processor configured to transmit status information of the aircraft to the air traffic control tower, convert a voice command received from the air traffic control tower into a command keyword, and control the communication device to transmit an instruction corresponding to the command keyword to the aircraft to remotely control the aircraft.