Rockwell Collins, Inc.

Nicholas Liberko

Boe A Svatek

Kevin McElroy

Brian R Wolford

Daniel K Snodgrass

Kevin Michael Kronfeld

David Fogerty

George F Elmasry

George Tyler Barney

Paul A Lenhardt

Jason Thompson

Carrie Block

Corrie E Block

Abhishek Dharmesh Rane

Daniel Snodgrass

A system may include a radio and a processor. The processor may be configured to: obtain information of a flight plan; obtain a command and control (C2) communication plan; and output instructions to operate the radio to connect with at least one given antenna of at least one given radio tower at a given time according to the C2 communication plan. The radio may be configured to connect with the at least one given antenna of the at least one given radio tower at the given time according to the C2 communication plan.

System and method to operate radio of aircraft to connect to radio towers according to command and control communication plan

An unmanned aircraft system (UAS) control apparatus is disclosed. In embodiments, the UAS control apparatus is embodied in a control station to manage command and control (C2) functions for UAS operations in a designated coverage volume including a geofenced interference region proximate to the control station, controlling each UAS via connections on a spectrum of C2 channels. The UAS control apparatus generates flight plans for UAS operations, providing separation and keeping UAS operations away from the control station to minimize RF interference with other UAS C2 connections. Should a UAS be required to operate proximate to the control station, the UAS control apparatus employs dynamic spectrum management with respect to other concurrently operating UAS to eliminate, reduce, or mitigate RF interference resulting from the encroaching UAS.

System and method for optimized unmanned aircraft system (UAS) spectrum planning via dynamic airspace and spectrum allocation

A system and method for optimizing mission fulfillment via unmanned aircraft systems (UAS) within a mission space generates or receives atmospheric models forecasting weather and wind through the mission space, the atmospheric models having an uncertainty factor. Until the projected flight time, the controller may iterate through one or more simulations of a projected flight plan through the mission space, determining the probability of successful fulfillment of mission objectives based on the most current atmospheric models (including the ability of the UAS to navigate the flight plan within authorized airspace constraints). Based on conditions and behaviors observed during a simulated flight plan, the controller may revise flight plans, flight times, or atmospheric models for subsequent simulations. Based on multiple probabilities of fulfillment across multiple simulations, the controller selects an optimal flight plan and/or flight time for fulfillment of the assigned set of mission objectives.

System and method for optimizing mission fulfillment by unmanned aircraft systems (UAS) via dynamic atmospheric modeling

A system and method for adaptive extension of a command and control (C2) backhaul network for unmanned aircraft systems (UAS) is disclosed. In embodiments, the adaptive extension includes front-end and back-end cognitive engines on either side of an extension of the C2 backhaul network to a remote control station otherwise without a point of presence (PoP). Both cognitive engines transmit test packets to the other to refine coding schemes for transmission of C2 packets across the extension based on received feedback about the transmission. When C2 packets are received from the backhaul network or remote control station, the cognitive engines select an optimal coding scheme based on packet size. The cognitive engine encodes the C2 packets based on the optimal coding scheme. When C2 packets are received from the other cognitive engine, the applicable coding schemes are identified and the C2 packets decoded accordingly.

System and method for adaptive extension of command and control (C2) backhaul network for unmanned aircraft systems (UAS)

An unmanned aerial system (UAS) is disclosed. In embodiments, the UAS includes an unmanned aerial vehicle (UAV), and a controller communicatively coupled to the UAV. In embodiments, the UAS controller may be configured to: acquire a command and control (C2) link quality model for a planned route; generate one or more control signals configured to cause the UAV to perform a monitored flight along a planned route; acquire actual C2 link quality data during the monitored flight along the planned route; compare the actual C2 link quality data to the C2 link quality model; identify a C2 link quality deviation between the actual C2 link quality and the C2 link quality model; and generate one or more control signals configured to cause the UAV to perform one or more prescribed flight plan maneuvers if the identified C2 link quality deviation (&#x394;C2) exceeds a threshold deviation value (C2).

System and method for preventing inadvertent loss of command and control link to an unmanned aerial system

An unmanned aerial system (UAS) is disclosed. In embodiments, the UAS includes an unmanned aerial vehicle (UAV) and a controller communicatively coupled to the UAV. In embodiments, the UAS controller may be configured to: acquire a surveillance quality model for a prescribed flight path; generate one or more control signals configured to cause the UAV to perform a monitored flight along the prescribed flight path; acquire actual surveillance quality data during the monitored flight along the prescribed flight path; compare the actual surveillance quality data to the surveillance quality model; identify a surveillance quality deviation between the actual surveillance quality and the surveillance quality model; and generate one or more control signals configured to cause the UAV to perform one or more corrective actions or maneuvers if the identified surveillance quality deviation exceeds a threshold deviation value.

System and method for preventing inadvertent loss of surveillance coverage for an unmanned aerial system (UAS)

A communication link analysis system is for analyzing communication link performance for an unmanned aviation system traveling over a route using a radio network comprising a plurality of radio nodes. The communication link analysis system includes a memory for storing quality parameters associated with communication links between the unmanned aviation system and the radio nodes. The communication link analysis system also includes a processor configured to map the quality parameters by location along the route or provide a bin chart of the quality parameter by radio node. The quality parameter is derived from radio link parameters provided by the unmanned aviation system.

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Marion, IA, United States of America

Nicholas Liberko