Embodiments of the present disclosure describe a secure, scalable and extensible aircraft and other system and device identity management (IdM) system that enables services for identity provisioning (idP), and identity validation, verification and authentication (idVV&A). The identity and management system uses dual-mode local broadcast and network connected device communication elements across a wide area network. The system serves as a Source System of Record (SSoR) that securely ingests private registration data, system/device identity verification and authentication requests and returns validated identity and activity information.

Systems, methods, and apparatus for identifying and tracking UAVs including a plurality of sensors operatively connected over a network to a configuration of software and/or hardware. A computing device can tune the RF receiver to a particular frequency set. The computing device can receive RF signal data corresponding to a plurality of RF signals via the RF receiver. The computing device can detect a plurality of signal characteristics corresponding to the plurality of RF signals from the RF signal data. The computing device can identify a matching RF signal by comparing the RF signal data to a plurality of known RF signals. The computing device can apply a predetermined rule set to the matching RF signal to determine at least one action to take.

Methods, devices, and systems for ground traffic aircraft management are described herein. One device includes a user interface, a memory, and a processor configured to execute executable instructions stored in the memory to receive airport information associated with an airport, generate, using the airport information, a map of the airport, display an intersection on the map of the airport, receive a selection of the intersection, and display flight information of each of a plurality of aircraft passing through the intersection within a particular period of time and the map of the airport in a single integrated display responsive to receiving the selection of the intersection.

An exemplary system and method provide flight management monitoring for small, non-commercial aircrafts, e.g., for training/monitoring and maintenance tracking, using a smart phone and its associated sensors (or a remote instrumentation device of the same). The exemplary system and method employ low-cost sensors available on the smart phone or a small sensor instrument and analysis system to identify, in non-real time, flight regimes recorded for a given flight that can be later utilized by the flight or maintenance crew in flight training for the pilot or maintenance operations by the pilot or flight mechanic.

A control device includes a storage unit, a communication unit configured to communicate with a vertical take-off and landing aircraft, and a control unit. The control unit is configured to: when a landing request is received from the vertical take-off and landing aircraft via the communication unit, determine whether the vertical take-off and landing aircraft is adapted to a runway landing; and when the vertical take-off and landing aircraft is adapted to the runway landing, acquire reference information indicating an environment for landing of the vertical take-off and landing aircraft, and transmit an instruction to the vertical take-off and landing aircraft to land in one landing mode out of a vertical landing and the runway landing based on the reference information.

Systems, methods, and devices for automatic signal detection in an RF environment are disclosed. A sensor device in a nodal network comprises at least one RF receiver, a generator engine, and an analyzer engine. The at least one RF receiver measures power levels in the RF environment and generates FFT data based on power level data. The generator engine calculates a power distribution by frequency of the RF environment in real time or near real time, including a first derivative and a second derivative of the FFT data. The analyzer engine creates a baseline based on statistical calculations of the power levels measured in the RF environment for a predetermined period of time, and identifies at least one signal based on the first derivative and the second derivative of the FFT data in at least one conflict situation from comparing live power distribution to the baseline of the RF environment.

The present invention concerns a vehicle tracking device for tracking one or more vehicles at a geographic location of a transport network within which the one or more vehicles are able to move, the vehicle tracking device comprising: one or more infra-red (IR) sensors having a field of view and being configured to detect IR radiation being emitted from or reflected by the one or more vehicles at the geographic location within the field of view; a receiver configured to receive unique identification data which uniquely identifies each of the one or more vehicles and position data which indicates an initial position of each of the one or more vehicles when the one or more vehicles enter the field of view at the geographic location; a processor configured to determine current kinematic data of the one or more vehicles in at least two dimensions based upon the IR radiation detected by the one or more IR sensors, the received unique identification data and the received position data; and a transmitter configured to transmit the determined current kinematic data of a particular vehicle of the one or more vehicles to a kinematic data receiver spaced apart from the transmitter. The transmitter of a first vehicle tracking device is configured to transmit the current kinematic data determined at the first vehicle tracking device and unique identification data of the one or more vehicles to a second vehicle tracking device of the plurality of tracking devices and the receiver of the first vehicle tracking device is configured to receive current kinematic data determined at a third vehicle tracking device of the plurality of vehicle tracking devices and unique identification data of the one or more vehicles from a third vehicle tracking device.

A system and method for detecting and avoiding a conflict along a current route of a vehicle is described. In some implementations, the system accesses or determines trajectories of the vehicle and a plurality of nearby moving objects, the trajectories being determined forward in time. Next, the system performs a comparison of the trajectories, and, predicts one or more conflicts between the vehicle and corresponding ones of the nearby moving objects. The system then determines the most-imminent conflict and selects a maneuver to avoid the most-imminent conflict. The system includes a user interface, where a specific resolution to the conflict is displayed. The specific resolution includes a direction in which to turn the vehicle and the magnitude of heading change. In some alternative implementations, the specific resolution is transmitted to a guidance system of the vehicle where the resolution is automatically executed by the guidance system.

Systems, methods, and devices for automatic signal detection in an RF environment are disclosed. A sensor device in a nodal network comprises at least one RF receiver, a generator engine, and an analyzer engine. The at least one RF receiver measures power levels in the RF environment and generates FFT data based on power level data. The generator engine calculates a power distribution by frequency of the RF environment in real time or near real time, including a first derivative and a second derivative of the FFT data. The analyzer engine creates a baseline based on statistical calculations of the power levels measured in the RF environment for a predetermined period of time, and identifies at least one signal based on the first derivative and the second derivative of the FFT data in at least one conflict situation from comparing live power distribution to the baseline of the RF environment.

Various embodiments of a vision-guided unmanned aerial vehicle (UAV) system to identify and collect foreign objects from the surface of a body of water are disclosed herein. A vision system and methodology has been developed to reduce reflections and glare from a water surface to better identify an object for removal. A linearized polarization filter and a specularity-removal algorithm is used to eliminate excessive reflection and glare. A contour-based detection algorithm is implemented for detecting the targeted objects on water surface. Further, the system includes a boundary layer sliding mode control (BLSMC) methodology to reduce and minimize position and velocity errors between the UAV and object in the presence of modeling and parameter uncertainties due to variation in a moving water surface.