Two University of Texas at Arlington researchers are working with Lockheed Martin to “optimize how unmanned vehicles use sensors to gather information.”

Frank Lewis, the Moncrief-O’Donnell Chair and professor of electrical engineering, and Yan Wan, an associate professor of electrical engineering, are helping Lockheed figure out how to use sensors on vehicles underwater, on the ground and in the air, to measure and predict the activities of a target.

The entities note that moving targets and environmental factors such as water, air clarity or visibility can interfere with sensor signals, so the team is using a Kalman filter to collect information from several sensors, then fuse it together from different angles to estimate a location, velocity, physical properties and other information of a target. 

According to the entities, when uncertainty exists in a dynamic system, a Kalman filter is an “algorithm that can be used to combine information to make an educated guess about what a system will do next.” Using the algorithm, operators can adapt to changing missions and environmental conditions to produce an “increased effective field of view, improved sensor coverage and more accurate target estimation.”

Lewis and Wan will use a $50,000 contract with Lockheed to make sure that the algorithm will work with the company’s software.

“In distributed control systems, where multiple unmanned vehicles work together and receive commands based on their relative position to each other and the desired outcome or goal of the task, the ability to quickly and accurately predict behaviors is a vital component of a satisfactory outcome for the mission,” Wan explains.

“We are happy to apply our knowledge of distributed controls in collaboration with Lockheed Martin because it will help them develop better platforms for the technology and it will help us better understand the potential applications of our research.”