An example operation may provide receiving, at a server, one or more communications from a drone, determining the one or more communications identify a drone identifier and a current time, determining whether the one or more communications were received within a time window, assigning a token to the identified drone indicating the drone is active, and storing the token as a transaction in memory.

Disclosed is a method of detecting spoofing of a traffic alert and collision avoidance system, known as a TCAS, the TCAS having a Mode A, a Mode C and a Mode S for communicating with surrounding aircraft. The method includes: querying a suspected spoofing aircraft via Mode S of the TCAS and receiving a response to this query; deducing from the response at least some data, known as Mode S data, relating to the suspected spoofing aircraft; and validating Mode S data by querying the suspected spoofing aircraft via Mode A or Mode C of the TCAS.

The UAV 1a includes a dust sensor 16 and a dust-preventing function 17 and performs a processing for a different UAV 1b not provided with a dust-preventing function on the basis of a dust amount detected by the dust sensor 16 during a flight of the UAV 1a.

Techniques for anomaly detection are disclosed. These techniques include identifying a chain of operations for one or more systems, including a plurality of consecutive operations, and clustering operation phases in the chain of operations based on one or more operating conditions, using sensor data. The techniques further include computing statistical values for one or more parameters across the clustered operation phases, identifying one or more outlier parameters in the sensor data based on the computed statistical values, and excluding the one or more outlier parameters from the sensor data. The techniques further include computing one or more nominal values for one or more parameters of a first sub-system, of a plurality of sub-systems in the one or more systems, using the sensor data with the one or more outlier parameters excluded, and detecting an anomaly in the first sub-system based on the computed one or more nominal values.

One or more unmanned aerial vehicles (UAVs) having a ground map stored therein are employed to assist an aircraft in landing at an airfield. A determination is made that the aircraft requires assistance landing at the airfield. Instructions are sent to the one or more UAVs to synchronize a flight path with the aircraft. The one or more UAVs receive sensor data regarding conditions surrounding the aircraft and the airfield. The aircraft is controlled by the one or more based upon the ground map, the flight characteristic profile, and the group map. The controlling of the aircraft by the one or more UAVs is discontinued upon the aircraft landing at the airfield.

Systems and methods of the present invention are provided to generate a plurality of flight trajectories that do not conflict with other aircraft in a local area. Interventions by an air traffic control system help prevent collisions between aircraft, but these interventions can also cause an aircraft to substantially deviate from the pilot's intended flight trajectory, which burns fuels, wastes time, etc. Systems and methods of the present invention can assign a standard avoidance interval to other aircraft in the area such that a pilot's aircraft does not receive an intervention by an air traffic control system. Systems and methods of the present invention also generate a plurality of conflict-free flight trajectories such that a pilot or an automated system may select the most desirable flight trajectory for fuel efficiency, speed, and other operational considerations, etc.

An aircraft system for an own-ship aircraft includes an ADS-B unit configured to receive ADS-B messages with flight information from other aircraft over a plurality of time periods, the other aircraft including a first aircraft. The system further includes a database configured to store at least a portion of the flight information associated with the other aircraft over the plurality of time periods. The system further includes a processing unit configured to compare the flight information for a current time period to the flight information for a previous time period to identify missing flight information from the current time period relative to the previous time period, the missing flight information including the flight information associated with the first aircraft, and initiate an annunciation to an operator of the own-ship aircraft based on the missing flight information associated with the first aircraft.

A system onboard a vehicle may include a vehicle management system (VMS) and a mission management system (MMS). The VMS may include a plurality of VMS nodes for controlling operation of the vehicle. The MMS may include a plurality of MMS nodes for controlling equipment associated with a mission of the vehicle. The system may also include a flexible deterministic communications network. The flexible deterministic communication network may be configurable for communications between each of the VMS nodes, between each of the MMS nodes and between the VMS nodes and the MMS nodes. The VMS nodes communicate using static, deterministic messages and the MMS nodes communicate using dynamic, non-deterministic messages.

A method for integrating a new navigation service is implemented in an avionics onboard system comprising a DAL+ core computer and a DAL peripheral computer for managing the application. The method of integration determines an optimal functional and physical distribution of the elementary functions FU(i) of the new service within the onboard avionics system over the set of possible distributions which minimizes a global cost criterion CG, dependent on several parameters, including at least the additional development cost of the elementary functions integrated within the digital DAL+ core computer, and carries out the integration of the new service.

An avionics system allows aircraft to introduce bogus ADS-B Out messages that are recognized as false only by authorized users. The system enables aircrafts flying at low altitudes to prevent misuse of their ADS-B Out information by maliciously operated cyber and physical attack tools. Aspects of the illustrative embodiment include the system architecture, including an Airborne ATC Processor and Ground ATM System Processor; a process employed by aircraft for generating authorized bogus ADS-B Out messages; a process employed by aircraft for transmitting authorized bogus ADS-B Out messages; and a process employed by air traffic control and other aircraft for decoding the authorized bogus ADS-B Out messages.