Michael Wicks


Michael C. Wicks’ pioneering signal processing techniques changed the face of modern radar engineering, enabling advanced air and space radar systems for intelligence, surveillance, and reconnaissance important to national security. An innovator of many new radar signal-processing techniques, Dr. Wicks is best known for development of knowledge-based STAP. Space-time adaptive processing, or STAP, improves target detection in environments where interference such as clutter or jamming exists. To overcome the limitations of traditional STAP, Dr. Wicks developed algorithms that can incorporate “prior knowledge” such as digital terrain maps and real-time and archival data to improve radar performance. Successfully demonstrated with airborne radar data during the 1990s, this approach has been further developed by the U.S. government and is finding its way into numerous real‐world radars. Dr. Wicks has also been a driving force in waveform diversity, which has provided the foundation for fully adaptive radar. Waveform diversity extends adaptivity to the transmit signal, where it can be varied depending on the target and interference environment. He has also investigated problems in weak signal detection, distributed radar, and detection of targets that are covered or concealed.

An IEEE Fellow and U.S. Air Force Research Laboratory Fellow, Dr. Wicks’ many honors include the 2009 IEEE Warren D. White Award for Excellence in Radar Engineering as well as the 2013 IEEE Dennis J. Picard Medal, awarded to him for "leadership and developments in fully adaptive radar, advanced space-time adaptive processing (STAP), knowledge-based signal processing, and waveform diversity." He retired from the U.S. Air Force in 2011 as senior scientist for sensors signal processing at the Air Force Research Laboratory, Rome, NY, USA and is currently a professor at the Ohio Scholar for Sensor Exploitation and Fusion at the University of Dayton, OH, USA.