The method can include performing inference using the system; and can optionally include training the system components. The method functions to automatically interpret flight commands from a stream of air traffic control (ATC) radio communications. The method can additionally or alternatively function to train and/or update a natural language processing system based on ATC communications. Additionally, the method can include or be used in conjunction with collision avoidance and/or directed perception for traffic detection associated therewith.

The present invention is for an autonomous aerial vehicle that enables near real-time and offline data processing among heterogenous devices that are in unreliable or unconnected network service areas, wherein the heterogenous devices are associated with heavy industrial systems. The autonomous aerial vehicle may obtain data from a first physical asset, and segment the obtained data as suitable for a local area compute node and/or a cloud compute node. The autonomous aerial vehicle may identify a location associated with the one or more destination devices and may compute a flight path to the destination location. The aerial device may thereafter travel to the destination location and upload relevant data to the at least one destination upon arrival.

A system may include a display and a processor communicatively coupled to the display. The processor may be configured to: output, to the display, a view of an airport moving map (AMM); receive aircraft state data and airport surface data; at least based on the current position of the aircraft and at least one factor, obtain commonly used taxi route data from a data structure, the data structure including taxi route data, the taxi route data including information of commonly used taxi routes for the airport, wherein the commonly used taxi route data includes information of a commonly used taxi route for the aircraft on the airport surface; based at least on the commonly used taxi route data, the aircraft state data, and the airport surface data, generate taxi routing guidance content; and output, to the display, the taxi routing guidance content.

A system and method for interference detection. The system and method receives flight data comprising a plurality of flights. The system and method identifies a plurality of signal drop events based on at least the flight data. The system and method determines one or more co-located signal drop event subsets based on at least the plurality of signal drop events and filter criteria. The system and method determines one or more interference events based on the one or more co-located signal drop event subsets, wherein each of the one or more co-located signal drop event subsets is based on at least two or more of the plurality of signal drop events.

The present disclosure describes systems and methods for providing real-time holding and diversion information to a pilot of an aircraft. In one aspect, the pilot uses an electronic flight bag (EFB) or a flight management computer (FMC) to display in a GUI the holding and diversion information. For example, the EFB can receive ADS-B data that can be used to determine the location of the aircraft in the holding queue (i.e., the aircraft's queue position) and predict the amount of time before the aircraft will be able to land. The EFB or FMC can also display diversion information regarding one or more alternate locations (e.g., alternate airports) in the GUI. In one aspect, the EFB or FMC calculate a bingo fuel and the time until reaching the bingo fuel and the pilot must divert.

Methods and systems are provided for monitoring an aircraft. An exemplary method involves capturing, by a computing system at a ground location, a flight tracking image associated with the aircraft that is displayed on a first display device at the ground location, and communicating the captured flight tracking image to the aircraft for display on a second display device onboard the aircraft.

A device receives a request for a mission that includes traversal of a flight path from a first location to a second location and performance of mission operations, and calculates the flight path from the first location to the second location based on the request. The device determines required capabilities for the mission based on the request, and identifies UAVs based on the required capabilities for the mission. The device generates flight path instructions for the flight path and mission instructions for the mission operations, and provides the flight path/mission instructions to the identified UAVs to permit the identified UAVs to travel from the first location to the second location, via the flight path, and to perform the mission operations at the second location.

Systems and methods for providing improved situational awareness for an aircraft while taxiing. An exemplary method generates reflectivity data based on an associated emission at a transceiver located on an aircraft. At a processor, targets are determined if a portion of the generated reflectivity data is greater than a predefined threshold. Then, the analyzed targets are determined as to whether they are within a dynamically defined three-dimensional envelope. The envelope is based on wingtip light module speed and trajectory. On a display device, an indication of the nearest target is presented at the associated range to the nearest target.

Various embodiments provide methods for controlling landings of a UAV in a landing zone including a plurality of landing bays. Various embodiments include a method implemented on a computing device for receiving continuous real-time sensor data from a transceiver and from sensors onboard the UAV, and detecting a target landing bay within the plurality of landing bays within the landing zone that is available for landing based on the continuous real-time sensor data. Orientation and position coordinates for landing in the target landing bay may be calculated based on the continuous real-time sensor data. Information regarding positions and flight vectors of a plurality of autonomous UAVs may be obtained, and a flight plan for landing in the target landing bay may be generated based on the orientation and the position coordinates, positions and flight vectors of the plurality of autonomous UAVs and a current orientation and position of the UAV.

A device receives a request for a flight path for a UAV from a first location to a second location, credentials for the UAV, and component information for the UAV. The device determines, based on the credentials, whether the UAV is authenticated for utilizing the device and a network, and determines whether the UAV is capable of flight based on the component information and maintenance information. The device calculates, the flight path based on capability information for the UAV and/or other information, and determines whether the UAV is capable of traversing the flight path based on the capability information and/or the other information. The device generates flight path instructions for the flight path, and provides the flight path instructions to the UAV to permit the UAV to travel from the first location to the second location via the flight path.