Tag: radar

Computational Intelligence Aids in Explosive Hazard Detection

To detect buried explosive hazards in places like Afghanistan, and to save the lives of civilians and US soldiers, Michigan Tech researcher Tim Havens realizes it requires a team—a team
of sensors.

This technology has the potential to not only save lives, but also to advance the basic science of how to combine sensors and information together to get a whole better than the sum of its parts.

A new $983,000 research project, “Heterogeneous Multisensor Buried Target Detection Using Spatiotemporal Feature Learning,” will look at how forward-looking ground-penetrating radar, LiDAR, and video sensors can be combined synergistically to see into the ground, capture high-quality images, and then automatically notify the operator of threats. With funding from the US Army Research Office, Havens and Tim Schulz, professor of electrical and computer engineering at Michigan Tech, will work with three PhD students to create a high probability-of-detection/low false-alarm rate solution.

“It’s a very difficult problem to solve because most of the radar energy bounces right off the surface of the earth,” says Havens, the William and Gloria Jackson Assistant Professor of Computer Systems at Michigan Tech. “This technology has the potential to not only save lives, but also to advance the basic science of how to combine sensors and information together to get a whole better than the sum of its parts.”

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This new project will advance additional sensor-related work Havens and collaborators completed between 2013–2015. The US Army-funded project studied signal processing and computer-aided detection and classification using forward-looking, ground-penetrating, vehicle-mounted radar.
The Army currently fields ground-penetrating radars in its fleet. The problem is they cannot detect hazards until they’re right above them, putting a multi-million dollar radar—and soldiers—directly in the path of danger.

“The big ideas here were to process data to obtain better images, see into the ground in a high-fidelity manner, and develop algorithms to automatically find buried threats—notifying operators of what the possible threats actually are,” Havens adds.

Havens has partnered with the Army since 2008 when he was a PhD student.

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