A user terminal generates a virtual drone camera image, as an estimated captured image where it is assumed that a virtual drone camera mounted on a drone has captured an image of a planned landing position on the basis of a captured image obtained by capturing the planned landing position of the drone with the user terminal, and transmits the generated virtual drone camera image to the drone. The drone collates the virtual drone camera image with the image captured by the drone camera and lands at the planned landing position in the image captured by the drone camera. The user terminal generates a corresponding pixel positional relationship formula indicating a correspondence relationship between a pixel position on the captured image of the user terminal and a pixel position on the captured image of the virtual drone camera, and generates the virtual drone camera image using the generated relationship formula.

Systems and corresponding methods are provided for moving object predictive locating, reporting, and alerting. This method includes receiving moving object data corresponding to a moving object; receiving sensor data from a sensor and merging the received moving object data and the received sensor data into a set of merged data. The example method further includes based on the set of merged data, automatically determining one or more of a predicted location or range of locations for the moving object, a potential path of travel for the moving object, an alert concerning the moving object, and providing the alert. The automatically determining may be further based on one or more historical traits concerning the object, and the geographic medium the object is moving through. The geographic medium may include one or more of terrain, air, water, and space. The object may be a soldier, vehicle, drone, or ballistic.

A population density map of a region is generated by dividing the region into cells and allocating a population of the region only to the cells that are accessible to people, or are believed to be populated. Each of the cells is classified based on one or more ground features of the cells, and an adjustment factor for each of the cells is determined based at least in part on the classifications. Equal shares of the population of the region are allocated to each of the cells that is accessible or populated, and the equal shares are multiplied by the adjustment factors determined for the respective ones of the cells to calculate a population for each of such cells.

Navigation beacons may be trained to receive signals of opportunity from one or more vehicles, to recognize their own position based on such signals, and to transmit information regarding their own position to one or more other vehicles accordingly. The navigation beacons may be of small size and feature a basic construction including one or more transceivers, power sources and the like, and may communicate via a Bluetooth® Low Energy, Ultra Wideband or long-range low-power wireless standard, or any other standard. The navigation beacons may be installed in any location, preferably being mounted to one or more existing fixed structures or facilities (e.g., transportation structures or facilities), and may operate in active and/or passive modes when learning their positions or servicing position information to one or more remote devices.

An aircraft includes a short-range radar that is configured to detect a trajectory, which is specified based on a position detection of the aircraft by a ground station.

An information processing apparatus includes an accumulation unit that accumulates history information regarding a flight history of an aircraft. A specification unit, based on the history information accumulated by the accumulation unit, specifies a candidate to be an operation assistant who assists an operation planned by an assisted operator. An output unit outputs information regarding the candidate to be the operation assistant specified by the specification unit.

A flight plan generation device for generating a flight plan of a flight device that transmits a captured image captured by an imaging unit through wireless communication during flight includes a first acquisition unit configured to acquire target information for specifying an imaging target to be imaged by the imaging unit during flight of the flight device and image quality information for specifying required image quality of a captured image of the imaging target, a second acquisition unit configured to acquire communication quality information on wireless communication quality in a predetermined area including at least a flight airspace of the flight device, and a flight plan generation unit configured to generate a flight plan including a flight path of the flight device and an imaging parameter of the imaging unit based on the acquired target information, image quality information, and communication quality information.

Systems, methods, and apparatus for identifying, tracking, and disrupting UAVs are described herein. A tracking system can receive sensor data associated with an object in a particular airspace from one or more radio frequency sensors. The tracking system can analyze the sensor data relating to the object to identify a type of RF signal being used by the object. A portable countermeasure device can generate one or more disruption signals on one or more targeted bands of spectrum based on the type of RF signal being used by the object.

A method, apparatus, and computer program product provide for crowdsourcing data from a plurality of aircraft systems to determine cloud ceiling information. In the context of a method, the method receives a set of sensor data from a first aircraft system captured during a first event. The method determines, based on the set of sensor data, a cloud ceiling value for a location and a time at which the first set of sensor data was captured. The method also stores the cloud ceiling value in association with a landing region and causes transmission of the cloud ceiling value to one or more additional aircraft systems.

Systems and methods for providing surveillance services for an unmanned vehicle are described herein. One embodiment of a method includes receiving surveilled data from a surveillance monitor regarding the unmanned aerial vehicle and at least one other aircraft, receiving trajectory data from at least one trajectory data source, and comparing the surveilled data with the trajectory data to determine whether the unmanned aerial vehicle is on path to collide with a third party aerial vehicle. In some embodiments, in response to determining that the unmanned aerial vehicle is on path to collide with the third party aerial vehicle, the method includes determining an alternate route for the unmanned aerial vehicle; and communicating at least a portion of the alternate route to the unmanned aerial vehicle.