Systems and methods for predicting aircraft navigation performance are provided. In one embodiment, a method can include determining that one or more navigational aid measurements are not available to the aircraft. The method can include estimating a future actual navigation performance of the aircraft for a future point in the flight plan. The method can include determining a future required navigation performance associated with the future point in the flight plan. The method can include comparing the future actual navigation performance to the future required navigation performance to determine if the future actual navigation performance satisfies the future required navigation performance. The method can include providing, to an onboard system of the aircraft, information indicative of whether the future actual navigation performance satisfies the future required navigation performance.

A flight itinerary alerting system for monitoring a flight itinerary includes a monitoring system storing flight itinerary data like pilot contact data, first tier contact data, and second tier contact data. An alert routine executable on the monitoring system i) determines first or second tier alert conditions if no deactivation message is received upon expiry of a respective first or second duration following the expected arrival time, and ii) send an alert message through a communication network to a computer device of a corresponding first or second tier contact person upon determination of the respective alert condition. The multiple tiers of contact data with respective alerting criteria allows quick determination if search and rescue should be contacted with inherent redundancy, thus preventing overdue aircraft from being overlooked, while also minimizing false alarms in reporting overdue aircraft to search and rescue which might reasonably be accounted for by responsible persons.

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 and related methods for providing unusual attitude symbology for recovering from an unusual attitude condition. By the unusual attitude symbology, a pilot may visually determine corrective actions needed to recover from the unusual attitude condition with a minimal recovery time and similarly with a minimal cognitive workload. The pilot may thus establish stable flight, even under a high-stress situation. The unusual attitude symbology includes pitch direction indicators, roll direction indicators, a roll recovery arc, an unusual attitude warning indicator, and a roll entry chevron. Path based symbology may also be used to provide unusual attitude recovery while maintaining spatial orientation of the aircraft to the outside scene.

A method performed by a computing system configured to process distributed flight data is described. The computing systems obtains distributed flight data from a communication system operating externally from the computing system. The computing system creates a record identifying the distributed flight data in a queue of the computing system. The computing system processes the distributed flight data identified in the record of the queue using a plurality of virtualized environments (VEs) of the computing system, each VE of the plurality of VEs comprising a task scheduler and a containerized application that operates to process the distributed flight data. The computing system further provides processed flight data to a plurality of different client communication systems operating externally from the computing system.

A device includes a memory, a network interface, and a processor. The memory is configured to store an aircraft performance model. The aircraft performance model is based on historical flight data of one or more aircraft. The aircraft performance model includes a recurrent neural network layer. The network interface is configured to receive real-time time-series flight data from a data bus of a first aircraft. The processor is configured to receive, via the network interface, the real-time time-series flight data. The processor is also configured to generate, based on the real-time time-series flight data and the aircraft performance model, one or more aircraft performance parameters. The processor is further configured to provide the aircraft performance parameters to a display device.

The technology relates to health and lifetime estimation for a lighter-than-air (LTA) vehicle. An LTA vehicle health and lifetime estimation system may include a processor and a memory storing instructions executable by the processor to cause the processor to implement an estimation service for determining a remaining lifetime output and a simulator for simulating a terminal event based on the remaining lifetime output. The estimation service may include a thermal model configured to determine a gas temperature, a gas and air estimator configured to estimate a gas amount and an air amount remaining in a balloon of the LTA vehicle, a leak rate estimator configured to estimate a leak rate, and a zero pressure estimator configured to determine the remaining lifetime output based on the leak rate. The system also may include an air flow estimator configured to determine an air mass flow rate based on the air amount.

A system and method that system for provide visual decision support information. A disclosed system performs a process that includes: storing a set of layers of GIS data associated with a safety critical use case; in response to an active incident, integrating UAS incident data with the GIS data and generating a visual decision support interface that includes a flight plan overlaid onto the GIS data, wherein the flight plan includes a path with interactive points that link images taken by a UAS to geospatial locations in the GIS data; in further response to the active incident, integrating at least one of: weather, thermal image, social media, RFID, machine learning, animation, graphic, haptic sensor, holographic or virtual image, emoji, or video data, with the GIS data to provide additional visual information to the visual decision support interface; and displaying the visual decision support interface on at least one display.

A method for updating, for an aircraft, a first flight plan having a first set of flight parameters, includes receiving, via an avionics device, a change to the first flight plan, determining a second set of flight parameters based on the change to the first flight plan, receiving, by the avionics device, at least one of terrain data and special use airspace (SUA) data. The method includes performing, with the avionics device, a safety validation of the second set of flight parameters, wherein the safety validation comprises: comparing the second set of flight parameters with the received at least one of terrain data and SUA data, and determining, based on the comparison, whether the second set of flight parameters presents a risk to safe flight.