A system comprising an unmanned aerial vehicle (UAV) configured to transition from a terminal homing mode to a target search mode, responsive to an uplink signal and/or an autonomous determination of scene change.

The present invention is directed to methods and systems for requesting information from a mobile device with a fencing agent. The fencing agent determines a position with a DNS resolver, queries geofences with an IP address, receives an anchor point with an IP address from the DNS resolver. The device with the fencing agent is able to receive multiple anchor points within multiple geofences within an ROI and translate fence points into fence geometries. Geofence information is stored and registered in a database of geofences, and each geofence is associated with a plurality of geographic designators, wherein each of the plurality of geographic designators is associated with an IP address.

A method for determining a flight path of an unmanned aerial vehicle (UAV) includes: acquiring an initial flight path configured by a management platform; determining, based on the initial flight path, a first group of accessible base stations of the UAV on the initial flight path capable to be accessed when the UAV flies based on the initial flight path; if the first group cannot provide continuous cellular network services for the UAV, acquiring a second group of accessible base stations capable of providing continuous cellular network services for the UAV; and determining the flight path corresponding to the second group as a target flight path. As such, the initial flight path of the UAV can be reasonably adjusted upon that the core network device cannot provide satisfactory network services for the UAV flying according to the initial flight path, to enable the cellular network to provide satisfactory network services for the UAV.

A formation flight assistance system is placed on board a follower aircraft to benefit from an upwards air flow induced by a wake vortex generated by a leader aircraft. The system determines a wake vortex effect experienced by the follower aircraft as being a difference between measurements taken by sensors and modelling in a wake vortex free environment. Using a recursive Bayesian filter, the system determines an estimated position of the wake vortex on the basis of information relating to the leader aircraft and a wake vortex model, and determines an estimation uncertainty, according to which a potential discomfort window is computed for the passengers of the follower aircraft. The system keeps the follower aircraft outside the potential discomfort window. Thus, the comfort of the passengers of the follower aircraft is provided, while benefiting from an upwards air flow induced by the wake vortex.

Various embodiments of a system and method for a quantitative approach and departure risk assessment are described. In one example, the system includes program instructions executable in the computing device that, when executed by the computing device, cause the computing device to: obtain a nominal flight path of an aircraft, calculate a potential crash area for a section of the nominal flight path based on a failure mode, calculate risk values based on a population data of a geographical area traveled corresponding to the nominal flight path, and display the calculated risk values plotted on a map of at least a section of the geographical area traveled corresponding to the nominal flight path. Other examples include corresponding computer systems, apparatus, and computer programs recorded on one or more computer storage devices, each configured to perform the actions of the methods.

A system and method for high-confidence error overbounding of multiple optical pose solutions receives a set of candidate correspondences between 2D image features captured by an aircraft camera and 3D constellation features including at least one ambiguous correspondence. A candidate estimate of the optical pose of the camera is determined for each of a set of candidate correspondence maps (CMAP), each CMAP resolving the ambiguities differently. Each candidate pose estimate is evaluated for viability and any non-viable estimates eliminated. An individual error bound is determined for each viable candidate pose estimate and CMAP, and based on the set of individual error bounds a multiple-pose containment error bound is determined, bounding with high confidence the set of candidate CMAPs and multiple pose estimates where at least one is correct. The containment error bound may be evaluated for accuracy as required for flight operations performed by aircraft-based instruments and systems.

A weather depiction system for an aircraft is disclosed. A radar is configured to scan a surrounding environment of the aircraft and provide weather data. An aircraft computing device is configured to: detect weather patterns using the weather data, receive a flight trajectory of the aircraft from a flight management system (FMS), compare the flight trajectory to an altitude of each of the weather patterns, identify the weather pattern as relevant or non-relevant based on the comparison, and present symbols corresponding to the relevant weather patterns on the weather display and exclude symbols corresponding to the non-relevant weather patterns on the weather display.

An apparatus for preconditioning a power source of an electric aircraft is presented. The apparatus includes a power source of an electric aircraft, a computing device, and a user device. The computing device is configured to receive a flight plan, determine a predicted power usage model as a function of the flight plan, and initiate a power source modification on the electric aircraft as a function of the predicted power usage model. The user device is configured to display a flight performance infographic as a function of the predicted power usage model.

Methods and systems for airport noise management, which are based on integrating virtual noise monitoring with actual noise recordings via mobile application system, are disclosed. An example method of improving airport noise management includes receiving information associated with a flight segment, generating a virtual noise map for the flight segment that includes a virtual noise metric generated for each of a multiple user-defined locations that span a projection of the flight path on the Earth. The method includes receiving, from a mobile application at a user location, an audio recording that was recorded in a recording interval, generating, based on the virtual noise map for the flight segment, a virtual noise metric associated with the user location, and determining a validity of the audio recording by comparing the virtual noise metric associated with the user location to a recorded noise metric that is calculated based on the audio recording.

Described are systems and methods that utilize nodes distributed at different geographic locations to detect and track the approximate position, trajectory, and/or predicted path of aerial vehicles operating below a defined altitude (e.g., 500 feet). As nodes detect an aerial vehicle, the node determines a bearing toward the aerial vehicle and provides the bearing to an air-traffic system. The air-traffic system processes bearings received from each node and determines one or more of an approximate position, trajectory, and/or predicted path of the detected aerial vehicle. The approximate position, trajectory, and/or predicted path may be provided to one or more subscribing clients and/or used to alter paths of one or more aerial vehicles.