A HAPS platform may execute a neural network (a “HAPSNN”) as it monitors air traffic; the neural network enables it to classify, predict, and resolve events in its airspace of coverage in real time as well as learn from new events that have never before been seen or detected. The HAPSNN-equipped HAPS platform may provide surveillance of nearly 100% of air traffic in its airspace of coverage, and the HAPSNN may process data received from a drone to facilitate safe and efficient drone operation within an airspace.

Transponder transmissions may be monitored through a direct, shielded connection of an RF coupler to a transponder antenna cable. The transponder interrogated pressure altitude may quickly change and measuring accurate data including position and pressure altitude is critical. A global positioning system (GPS) may be onboard a universal access transceiver (UAT) and may be utilized to correct the transponder interrogated pressure altitude and position. The UAT may transmit data that may include a corrected pressure altitude and a subsequent position to improve air traffic control radar beacon systems (ATCRBS).

Disclosed are an emergency vehicle supporting device and system using a drone that resolve forward traffic congestion on a road on which an emergency vehicle is driving via the drone and supports securing of a driving path for the emergency vehicle. According to the present invention, an emergency vehicle supporting device mounted on the emergency vehicle generates drone control information and transmits the generated drone control information to the drone. Further, the drone flies according to the drone control information and a location change of the emergency vehicle and broadcasts an avoidance warning to surrounding vehicles around the flying drone, so that the surrounding vehicles may help the emergency vehicle secure a driving path and thus the emergency vehicle may arrive at a destination within a desired time.

Methods and systems for automatic sequencing of an ownship aircraft behind a lead aircraft on an approach to a runway. The method determines that the ownship aircraft is in an instrument approach. A pilot selection of the lead aircraft is confirmed as matching the lead aircraft identified in an air traffic control (ATC) command. The method includes calculating, an arrival time of the lead aircraft at the runway; processing the arrival time of the lead aircraft at the runway with a desired separation time to determine a target point for the ownship aircraft to merge onto a centerline of the runway; and automatically, and without further human input, generate lateral guidance, vertical guidance, and speed targets for the ownship aircraft to join the runway centerline at the target point at the desired separation time after the lead aircraft.

The present disclosure relates to the secure transmission of an aircraft trajectory that is to be flown or that has been flown. A ground-referenced description of the trajectory of the aircraft expressed in ground-referenced parameters is converted, using a description of an imaginary atmospheric model describing imaginary atmospheric conditions along the trajectory, into an air-referenced description of the aircraft trajectory expressed in air-referenced parameters. For decryption, knowledge of the imaginary atmospheric conditions allows the air-referenced description of the aircraft trajectory to be converted back into the ground-referenced description of the aircraft trajectory. Thus, the ground-referenced trajectory may be though of as the plain text, the imaginary atmospheric model as the cipher key and the air-referenced trajectory as the cipher text.

A collaborative aviation information collection and distribution system includes a plurality of aircraft data transmitters and an aircraft data processing system. Each aircraft data transmitter is configured to selectively transmit aircraft data associated with a subscribing aircraft. The aircraft data processing system is in operable communication with each of the aircraft data transmitters and includes a data receiver, a data transmitter, and a data processor. The data receiver receives aircraft data transmitted from each of the aircraft transmitters. The data transmitter selectively transmits actionable aircraft data to one or more of the subscribing aircraft or subscribing ground-based users. The data processor determines which of, and when, the one or more subscribing aircraft or subscribing ground-based users should receive actionable aircraft data, generates actionable aircraft data from at least a portion of the received aircraft data, and supplies the generated actionable aircraft data to the data transmitter for transmission.

Embodiments of this application provide a method for detecting an unauthorized uncrewed aerial vehicle, an apparatus, and a system. An AMF sends a tracking indication message to a network device, where the tracking indication message is used to indicate to report attribute information of user equipment in a coverage area of the network device when the attribute information of the user equipment meets a preset condition; and obtains the attribute information of the user equipment. In this way, after the attribute information of the user equipment is obtained, an identity status of the user equipment may be identified based on the attribute information of the user equipment, that is, whether the user equipment is an unauthorized uncrewed aerial vehicle is identified. This implements detection on an unauthorized uncrewed aerial vehicle that has accessed the 3GPP network.

In some embodiments, apparatuses and methods are provided herein useful to allocate unmanned aircraft system (UAS). Some embodiments, provide UAS allocation systems, comprising: a UAS database that stores for each registered UAS an identifier and corresponding operational capabilities; an allocation control circuit configured to: obtain a first set of multiple task parameters specified by a first customer and corresponding to a requested first predefined task that the customer is requesting a UAS be allocated to perform; identify, from the UAS database, a first UAS having operational capabilities to perform the first set of task parameters while implementing the first task; and cause an allocation notification to be communicated to a first UAS provider, of the multiple UAS providers, associated with the first UAS requesting the first UAS provider to allocate the identified first UAS to implement the first task.

An air turbulence analysis system and method includes an air turbulence control unit that is configured to receive a position signal from an aircraft within an air space. The air turbulence control unit determines a location of air turbulence within the air space based on the position signal. In at least one embodiment, the position signal is an automatic dependent surveillance-broadcast (ADS-B) signal.

A system may include a display and a processor. The processor may be configured to: output a view of an airport moving map (AMM), the AMM depicting a location of an aircraft on an airport surface; receive aircraft state data and airport surface data, wherein the airport surface data includes information of the airport surface, wherein the aircraft state data includes a current position of the aircraft; generate taxi routing guidance content, wherein the taxi route data includes information of a taxi route for the aircraft on the airport surface, wherein the taxi routing guidance content includes graphical and/or audio content to be presented to a flight crew to guide the aircraft along the taxi route, wherein the taxi routing guidance content further includes an approaching runway annunciation, wherein the approaching runway annunciation indicates that the aircraft is approaching a runway; and output the taxi routing guidance content.