Raytheon Company

David James Theodore

Torsten Staab

Jesse J Lee

Andres Rios

Alfonso Andres Lopez

Blake Cameron Sims

Hyperia Doe

In some embodiments, a method for determining a location of an unmanned system (UMS) can include: receiving data from a plurality of data sources, wherein the data sources include a geolocation sensor and at least one of an RF receiver, a RADAR system, a LIDAR system, a SONAR system, an infrared camera, a Simultaneous Location and Mapping Algorithm (SLAM) system, an inertial sensor, or an acoustic sensor; determining a reliability of one or more of the data sources based on the received data; assigning weights to the data sources based at least in part on the determination of the reliability of the one or more data sources; and determining the location of the UMS using the received data and the assigned weights.

Intelligent location awareness for unmanned systems

A plurality of authentication devices form and manage a self-organizing mobile peer-to-peer mesh network to provide robust authentication of mobile peers, humans and or mobile devices such as drones, cars, satellites, robots etc. The mesh network may supplement traditional fixed point of entry authentication to combat social engineering penetrations or be used in situations where fixed-point authentication is not viable. Network efficiency can be enhanced by using two-level encryption, a first level of encryption based on permissions to join a mesh network and a simpler second level of encryption based on knowledge shared with members of the network for communication. Making the permissions a function of location can make the network more robust. Re-authenticating member peers based on the occurrence of defined events can further enhance security.

Self-organizing mobile peer-to-peer mesh network authentication

Growing community of inventors

Austin, TX, United States of America

David James Theodore