Smart robocopters use MWIR sensors and 3D LADAR to identify pirate boats
Arlington, VA--A U.S. Office of Naval Research (ONR)-funded sensor starts airborne tests this summer so that Navy unmanned aerial vehicles (UAVs) will be able to distinguish small pirate boats from other vessels. The sensor, called the Multi-Mode Sensor Seeker (MMSS), is a combination of high-definition cameras, mid-wavelength infrared (MWIR) sensors and laser-radar or laser detection and ranging (LADAR) technology. Carrying advanced automatic target recognition software, the sensor prototype will be placed on a robotic helicopter (robocopter) called Fire Scout to autonomously identify small boats on the water, reducing the workload of Sailors operating it from control stations aboard Navy ships.
"Sailors who control robotic systems can become overloaded with data, often sifting through hours of streaming video searching for a single ship," said Ken Heeke, program officer in ONR's Naval Air Warfare and Weapons Department. "The automatic target recognition software gives Fire Scout the ability to distinguish target boats in congested coastal waters using LADAR, and it sends that information to human operators, who can then analyze those vessels in a 3-D picture."
Navy-developed target recognition algorithms aboard Fire Scout will exploit the 3D data collected by the LADAR using a long-range, high-resolution, eye-safe laser. The software compares the 3D imagery to vessel templates or schematics stored in the system's memory.
"The 3-D data gives you a leg up on target identification," said Dean Cook, principal investigator for the MMSS program at Naval Air Warfare Center Weapons Division (NAWCWD). "Infrared and visible cameras produce 2-D pictures, and objects in them can be difficult to automatically identify. With LADAR data, each pixel corresponds to a 3-D point in space, so the automatic target recognition algorithm can calculate the dimensions of an object and compare them to those in a database."
The algorithms have been successfully tested in shore-based systems against vessels at sea. The software is being integrated into a BRITE Star II turret by a team from NAWCWD, Raytheon, FLIR Systems, BAE Systems and Utah State University for airborne testing aboard a manned test helicopter. The flight assessment will be conducted against groups of approximately seven small boats in a military sea range off the California coast later this summer.
The U.S. Department of the Navy's Office of Naval Research (ONR) provides the science and technology necessary to maintain the Navy and Marine Corps' technological advantage. Through its affiliates, ONR is a leader in science and technology with engagement in 50 states, 70 countries, 1035 academic institutions and 914 industry partners. ONR employs approximately 1400 people, comprising uniformed, civilian, and contract personnel, with additional employees at the Naval Research Lab in Washington, DC.
SOURCE: U.S.Office of Naval Research; www.onr.navy.mil/Media-Center/Press-Releases/2012/Unmanned-Sensor-Automatic-Target-Recognition.aspx
Gail Overton | Senior Editor (2004-2020)
Gail has more than 30 years of engineering, marketing, product management, and editorial experience in the photonics and optical communications industry. Before joining the staff at Laser Focus World in 2004, she held many product management and product marketing roles in the fiber-optics industry, most notably at Hughes (El Segundo, CA), GTE Labs (Waltham, MA), Corning (Corning, NY), Photon Kinetics (Beaverton, OR), and Newport Corporation (Irvine, CA). During her marketing career, Gail published articles in WDM Solutions and Sensors magazine and traveled internationally to conduct product and sales training. Gail received her BS degree in physics, with an emphasis in optics, from San Diego State University in San Diego, CA in May 1986.