34 results about "Air traffic control" patented technology

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 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 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.

The application provides a regulation voice segmentation method based on speech recognition and endpoint detection, which is applied to air traffic control voice audio stream segmentation, and comprises the following steps: step 1, constructing a punctuation model based on speech recognition and a speech endpoint detection model; step 2, using the punctuation model based on speech recognition to recognize the audio data stream of the regulation voice, and outputting the corresponding text and sentence end identifier of the audio data stream; step 3, using the speech endpoint detection model to judge the speech starting point and ending point contained in the audio data stream of the regulation voice; step 4, segmenting the audio data stream of the regulation voice into audio segments; and step 5, applying the audio segments as data materials to the speech recognition process of the air traffic control system. Through the combination of speech recognition and endpoint detection, the application realizes the automatic segmentation of the air traffic control voice audio stream, and improves the accuracy and efficiency of the segmentation.

The invention relates to a computer system and a coordination method suitable for that system, which enables airborne early warning and control (AEW&C) air platforms and reconnaissance / intelligence unmanned aerial vehicles (UAVs) to perform distributed task sharing, allowing the continuation of AEW&C missions including airspace surveillance, command and control, reconnaissance, intelligence, communication, computation, and emergency air traffic control even if one or more platforms become inoperable.

The application relates to the technical field of speech recognition, and provides an end-to-end speech recognition method and system based on a keyword-enhanced attention mechanism, which comprises the following steps: a keyword retriever extracts entity keywords; a speech buffer manager receives continuous air traffic control audio segments, converts the audio segments into audio mel spectrum graphs, and then converts the audio mel spectrum graphs into audio embedding sequences; a keyword encoder unit maps a word embedding representation sequence into a keyword embedding sequence; an audio transcription decoder unit performs keyword-enhanced attention calculation, converts an audio embedding sequence, a transcription start flag and a splicing vector of a word embedding representation sequence into a predicted text sequence; a new word embedding representation sequence is input into a text transcriptioner through self-recurrence until a transcription end flag is output by the audio transcription decoder unit; and the predicted text sequence is output as a speech recognition text. The application realizes real-time recognition of streaming input speech, and has the advantages of high recognition accuracy, low response delay and flexible deployment.

The application discloses a kind of multi-runway airport runway operation mode dynamic adjustment decision methods, comprising: obtaining the runway operation mode dynamic adjustment decision influence factor of digitization;Based on decision influence factor, establish runway operation mode adjustment alarm prompt trigger rule;Runway operation mode adjustment decision processing is carried out, and various runway operation mode adjustment decision suggestions are generated;Decision selects the flight of switching runway operation mode to start execution;According to decision information, command flight to switch runway operation mode.The method of the application can be widely applied in tower control automation, air traffic control automation system, improve airport operation capacity, safety, efficiency, reduce flight delay.

The application provides an air traffic control radar modeling method, comprising the following steps: selecting initial sample points, and obtaining the flyable range of each initial sample point by designing a simulation system for an air traffic control radar; constructing a training sample set; reducing the data dimension by using a principal component dimension reduction method and reconstructing the kernel function of a Kriging model; selecting different correlation functions and regression functions for combination, obtaining different Kriging model modeling schemes; solving the weight of each Kriging model modeling scheme; obtaining the output result of each Kriging model modeling scheme; constructing a weighted average aircraft flight range prediction model based on the output result of each Kriging model modeling scheme and the weight of each Kriging model modeling scheme; and the model can quickly calculate the reasonable flight range of an aircraft according to weather and air resistance information. The application improves the efficiency and accuracy of air traffic control radar modeling.

The application verifies the flight program by the linkage simulation verification mode of the flight simulator and the control simulator, and comprises the creation of the static structure of the airspace where the flight program is located, the compilation of the dynamic air traffic control operation scene, the compilation of the flight simulator flight practice plan and the control training plan, the real-time simulation verification of the controller and the pilot, the operation index analysis after the flight, etc. A reasonable and sustainable flight program operation analysis method is provided in the air traffic control field, and a reference direction is provided for the comprehensive flight program verification, so that the problem of incomplete verification content of the existing simulation verification and the field verification flight test is solved, the problem of lack of flight program operation evaluation method and means is solved, the targeted suggestions for the optimization and improvement of the flight program design are provided, and thus the problem of low flight program utilization rate is solved.

This invention discloses an online real-time interactive air traffic control simulation training method, applied to the client and server sides of air traffic control simulation training. The method includes: encrypting, decrypting, updating, and synchronizing traffic training data between the client and server; constructing a simulation environment on the server based on the synchronized data; calculating and updating aircraft flight attitude information in real time; and distributing the calculated aircraft flight attitude results. This method employs online remote interactive training, decoupling location and time, allowing trainees to participate in training anytime, anywhere. This flexibility reduces trainees' time and space costs, and increases their enthusiasm and convenience for participation.

Example implementations relate to systems and techniques for coordinating and assigning aircraft and ground vehicles to runways to prevent wrong surface events and to minimize runway incursions. An aircraft initially receives instructions identifying a runway for use by the aircraft generated by an Air Traffic Control Tower (ATCT) and then subsequently receives a runway identification (ID) code transmitted by a sensor subsystem positioned proximate the runway, which is used by a runway-aircraft pairing management system. An onboard verification system of the aircraft then compares the runway ID code with the runway identified in the ground navigation instruction and uses an onboard transmitter to transmit a confirmation to the sensor subsystem positioned proximate the runway when the code and runway match. The aircraft then displays instructions for the aircraft to proceed with use of the runway.

This invention belongs to the field of aviation flight simulation training technology, and relates to an intelligent air-ground collaborative training and debriefing system and method for flight and air traffic control, solving the problem that existing systems cannot meet the demands of modern joint aviation training for realism, standardization, and precision. The air-ground linkage subsystem of this invention establishes a two-way voice communication link based on SIP and RTP protocols, and realizes real-time broadcasting and distribution of radar surveillance data using the UDPTLV protocol; the collaborative training subsystem issues training control commands and emergency commands through a TCP isolated channel, and achieves process synchronization and dual-end synchronous triggering of emergency commands based on a unified training state machine and a global clock; the intelligent debriefing subsystem uses a deep learning model to convert the voice stream into text, unifies the time alignment of multi-source data and automatically identifies training events, and completes multi-view playback and debriefing report generation based on a unified timeline. This invention improves the realism, collaboration, and automation of training.

This invention discloses a dynamic collaborative decision-making method for airport resources. By integrating collaborative exploration decision-making, temperature control optimization, and parallel computing acceleration, it achieves intelligent planning of the optimal airport access sequence for returning aircraft. This invention deeply integrates real-time airport status, aircraft demand, and dynamic resource constraints. Leveraging a "search agent" group collaborative evolution and simulated annealing perturbation mechanism, it overcomes the limitations of traditional manual decision-making or rule-based systems under dynamic multi-constraint conditions. Through the collaborative work of functional modules such as real-time data updates, problem modeling, group evolution, fine-grained search, and parallel evaluation, it achieves rapid response and optimized decision-making in multi-task, multi-airport collaborative support scenarios. This invention employs a two-layer acceleration architecture of "group parallel evaluation" and "computation vectorization," significantly improving computational efficiency while ensuring decision quality, meeting the real-time requirements of air traffic control, and realizing collaborative optimization of aircraft return scheduling and airport resources under complex conditions.

The utility model relates to air traffic control transponder check appearance technical field, and it relates to a kind of air traffic control transponder field check appearance, including display control unit, digital processing unit, radio frequency unit and power module;The display control unit is connected by serial port with digital processing unit;The digital processing unit is connected by communication interface with radio frequency unit;The power module is electrically connected with display control unit, digital processing unit and radio frequency unit respectively, for providing multistage voltage power supply, the utility model can effectively solve the detection precision low, the adaptation range narrow, power flexibility difference and the problems, such as complex structure, existing in existing field detection equipment, applicable to the rapid, accurate detection of multiple models of transponder, significantly improve maintenance support efficiency and safety.

This invention discloses a method and system for playing back air traffic control data based on message timing. The method includes: a reading thread extracting the timestamp and hexadecimal message data of each line of the message based on a two-level timestamp extraction strategy; a decoding thread extracting the message and sorting it using a sliding time window double threshold sorting algorithm before sending it to the decoding queue; a sorting thread transmitting the message data; and a sending thread and a dynamic scheduling algorithm based on a reference time calculating the precise sending time of each message and sending it to the target system for playback. The advantages of this invention are as follows: (1) The playback timing accuracy is naturally matched with the protocol accuracy, and the time error is strictly controlled within 1 / 128 seconds; (2) It effectively solves the trajectory distortion caused by the disorder of the original data; (3) The system resource occupancy rate is low, supporting high-concurrency playback tasks; (4) The startup delay is short, meeting the fast response requirements of the playback system; (5) The processing throughput is high, adapting to high-density air traffic control data playback application scenarios.

This disclosure presents a method, system, electronic device, and storage medium for air traffic control airspace risk early warning. The method includes: acquiring multi-source heterogeneous airspace data; performing spatiotemporal alignment on the multi-source heterogeneous airspace data to obtain a fused data stream, and correcting, denoising, and converting the fused data stream using outlier detection and interpolation compensation methods; processing the fused data stream using a risk assessment model to obtain the comprehensive risk level of the current airspace, and triggering a corresponding early warning strategy based on the comprehensive risk level; issuing an early warning based on the early warning strategy; and optimizing the risk assessment model based on early warning feedback data and manually corrected records. This disclosure can improve the real-time performance and accuracy of airspace risk perception, support dynamic assessment of complex scenarios such as flight conflicts, weather threats, and traffic overload, optimize early warning strategies based on environmental changes, support flexible expansion to multi-node deployment, and improve airspace resource utilization efficiency and aircraft operational safety.

The application provides a land-air communication sound source identity identification method, an air traffic control system and a readable storage medium. The land-air communication sound source identity identification method comprises the following steps: acquiring an RSSI value corresponding to a very high frequency receiver of a very high frequency station according to a preset acquisition frequency; judging whether the RSSI value is greater than a first threshold value, and if yes, recording a current time stamp as a start time stamp; after recording the start time stamp, judging whether the RSSI value is less than or equal to the first threshold value, and if yes, recording a current time stamp as an end time stamp; calculating an arithmetic mean value of all RSSI values collected between the start time stamp and the end time stamp; and if the arithmetic mean value is greater than or equal to a second threshold value, determining that the sound source identity is a controller, and if the arithmetic mean value is greater than the first threshold value and less than the second threshold value, determining that the sound source identity is a pilot. The application further provides an air traffic control system and a readable storage medium applying the method. The method can efficiently, accurately, reliably and conveniently realize land-air communication instruction acquisition, segmentation and speaker differentiation.

We provide control systems and other equipment that enable safe operation management in a variety of situations. [Solution] The memory unit 601 stores the position of the aircraft. The decision unit (flight plan decision unit 603) uses the communication difficulty distance, which indicates the length of the self-position estimation difficulty region, which is a region in the flight path where it is difficult for an individual aircraft to estimate its own position, to determine the number of aircraft that can estimate their own position. The creation unit (flight plan decision unit 603) uses the number of aircraft, the flight path, and the position of the aircraft to determine the aircraft that will travel along the flight path and create a flight plan for each aircraft. The output unit 604 outputs the flight plan and information about the aircraft that will travel along the flight path.

The application relates to the technical field of distributed data distribution and reliable storage, and provides an air traffic control distributed storage middleware based on data consistency copy and a consensus algorithm, which comprises a storage module using Redis as a storage basic platform, a client request processing module used for listening to a network port, asynchronously receiving a client request and pre-processing the client request, a Raft log management module used for distributing operation sequences to distributed nodes through a Raft algorithm and maintaining the operation sequences on the distributed nodes through the Raft algorithm, an asynchronous execution module used for executing the operation sequences on the distributed nodes through the Raft algorithm and storing data according to a consistency storage rule of the storage basic platform, and a data persistence module used for persisting storage data through a system snapshot. According to the characteristics of air traffic control field data, the application realizes a data storage method which takes into account data consistency and partition tolerance, guarantees response time and as far as possible guarantees availability.

The application discloses a tower control visual field efficiency optimization method based on improved gaze point rendering, relates to the technical field of air traffic control simulation, and comprises the following steps: acquiring objects in a current scene, control task data, interactive data of a controller and a simulated tower system, and a current gaze point rendering picture; performing feature extraction on the objects in the current scene and the control task data; inputting the extracted feature data and the interactive data into a preset Bayesian information gain framework to output an attention distribution of a current controller; calculating parameters of a Gabor kernel based on the Gabor kernel function according to the attention distribution of the current controller; generating Gabor noise based on the parameters of the Gabor kernel, superimposing the Gabor noise on the current gaze point rendering picture, and forming a current final rendering image. The application significantly improves the rendering efficiency and enhances the immersion and visual reality of a user.

Disclosed is a controller for controlling brake action of an aircraft based on a current runway condition of the runway. The controller receives an expected condition of the runway and expected brake action for the aircraft from air traffic control, or other entity. The controller sends actual measured brake pressure applied by the aircraft while landing, along with sensor data from sensors on the aircraft configured to detect contaminants such as fluid or ice on the runway to a machine learning model. The machine learning model is configured to output a predicted brake action for the aircraft and predicted runway condition. The controller compares the expected brake action and expected runway condition to the predicted brake action and predicted runway condition. If there is any discrepancy, the controller sends the predicted brake action and runway condition to air traffic control to update the expected brake action and expected runway condition.

The application discloses an air traffic control primary radar target detection method based on end-to-end, relates to the field of air traffic control primary radar, and solves the problem that the prior art relies on artificial experience and an existing deep learning model is difficult to effectively utilize radar space-time information. The method comprises the following steps: acquiring and pre-processing real-time radar data to obtain a real-time matrix, combining the real-time matrix with historical matrices of two continuous time points into a space-time three-dimensional data block; inputting the data block into a trained target segmentation model to obtain a binary segmentation graph; extracting a multi-dimensional feature vector of each connected region through connected domain analysis; inputting the multi-dimensional feature vector into a trained target classification model to obtain a probability value of each set belonging to a real target; and finally outputting a target track list through threshold screening, non-maximum suppression and coordinate mapping. The application realizes end-to-end automation of the detection process, can adapt to complex environments, significantly improves detection performance and reduces dependence on artificial experience.

This invention relates to the field of aviation technology, specifically to a fuel level monitoring and alarm method for civil aircraft based on ACARS and ADS-B. This method extracts the master flight path from historical ADS-B data, obtains real-time remaining fuel and historical fuel consumption for each flight phase using ACARS data, and calculates the estimated flight time by matching the current flight position with the master flight path. This allows for accurate estimation of remaining fuel at the destination airport, triggering an alarm when the remaining fuel falls below a set threshold. This invention eliminates reliance on airline computer plans and air traffic control flight plans, improves fuel level prediction accuracy by fusing historical and real-time data, reduces false alarms and missed alarms, and supports airports in developing ground support plans in advance. It is applicable to fuel level safety monitoring during civil aircraft flight.

This invention relates to the interdisciplinary field of aviation safety and artificial intelligence, specifically to an improved WGAN-GP method for generating adversarial examples from ADS-B time-series data. The method includes the following steps: acquiring historical ADS-B flight data and extracting features from five dimensions—longitude, latitude, altitude, speed, and heading—to construct a time-series dataset; building an adversarial example generation model based on an improved Wasserstein distance generative adversarial network and configuring a multi-objective composite loss function for the generator. This invention constructs an LSTM-based generator and discriminator, designs a composite loss function integrating adversarial loss, concealment loss, and temporal smoothness loss, and trains the model using gradient penalty and asymmetric update strategies. The generated adversarial examples possess both high concealment and physical consistency, effectively circumventing various unsupervised anomaly detection models. The model training is stable, providing technical support for building a safer air traffic control defense mechanism.

The application discloses an air traffic control voice communication method and system, the method comprises the following steps: obtaining voice information of an air traffic control voice sending end, performing hidden conversion on the voice information to add a digital signature and obtain a voice data packet; transmitting the voice data packet to an air traffic control voice receiving end through an IP packet network and performing recovery conversion to extract the digital signature and recover the voice information; identifying the communication type of the voice information according to the digital signature, and selecting a corresponding communication channel to forward the voice information according to the communication type. The application adds a digital signature to the voice information to realize information hiding, realizes ground-ground voice communication and ground-air voice communication forwarding according to different channels, saves air-ground voice communication frequency resources, reduces interference between multiple subjects in the same frequency band, changes the communication between ground controllers into a point-to-point visible mode, enhances the privacy and security of voice communication, and supports more communication channels.

The application discloses an airport delay level prediction method based on association rules and LSTM, which comprises the following steps: constructing an airport delay level prediction system; calculating average delay time and flight delay rate of each airport at different time periods; dividing delay levels of each airport at different time periods; constructing an airport delay transaction set; applying a time-space association rule mining method based on FP-Growth to mine time-space association rules of airport delays; and applying an LSTM method to predict future delay levels of the airport and calculate prediction accuracy. The airport delay level prediction model constructed by the application applies the time-space association rules with time-space information to the LSTM model, considers the influence of delay conditions of other airports on the predicted airport and the influence of different time periods on the predicted period, and improves the optimization speed of the LSTM model. The application provides a new modeling idea for the research field of domestic airport delay prediction, enriches the research method in the field of delay prediction, and the delay prediction result can provide a decision basis for the airport, the airline company and the air traffic control.