Tutorial: Cognitive Radar: The Knowledge-Aided Fully Adaptive Approach
Presented by:
Dr. Joseph R. Guerci
Consultant, USA
Course Description:
Recent advances in radar front-end hardware affording unprecedented flexibility, adaptivity and waveform diversity, coupled with continued advances in high performance embedded computing (HPEC) and knowledge-aided (KA) methods, has afforded the opportunity to “re-invent” radar with a new and powerful set of tools/assumptions that include:
- Arbitrary waveform selection
- Transmit adaptivity (waveform, spatial, polarimetric, etc.)
- Environmental awareness via a dynamic database and the availability of both endogenous and exogenous sensors
- Real-time KA methods adapted from the DARPA/AFRL KASSPER project and extended to the transmitter as well as the receiver
When effectively integrated, the result is an advanced radar architecture that exhibits the key rudimentary properties of a “cognitive” system, i.e., the ability to adapt “on-the-fly” both transmit and receive functions based on both its own sensing, as well as on information from a multitude of other sources (e.g., digital terrain maps, SAR imagery, etc.) via an environmental database (EDDB) and a real-time KASSPER HPEC architecture to exploit it.
Topics covered in this tutorial include:
- Derivation of optimal and adaptive multi-input, multi-output (MIMO) transmitter equations with numerous examples of potential benefits
- Application of optimal and adaptive MIMO techniques to optimizing detection, interference cancellation, and target identification
- Introduction to knowledge-aided (KA) methods and the DARPA/AFRL KASSPER real-time HPEC architecture
- Integration of full adaptivity (transmit and receive) and KA methods
Instructor Biography:
Dr. Joe Guerci has over 24 years of experience in advanced technology research and development in government, industrial, and academic settings. His government service included a recent 7 year term with the Defense Advanced Research Projects Agency (DARPA) in which he held the positions of Program Manager, Deputy Office Director, and finally Office Director of the Special Projects Office (SPO). In these capacities, Dr. Guerci was involved in the inception, research, development, execution, and ultimately transition of next generation multidisciplinary defense technologies.
Dr. Guerci is a recognized leader in the research and development of next generation sensor systems and adaptive signal processing. In particular, he has pioneered several major radar technologies including robust and knowledge-aided space-time adaptive processing (STAP), and optimal and adaptive MIMO radar and waveform design. In addition to authoring over 80 peer reviewed articles, he has two book chapters and is the author of Space-Time Adaptive Processing for Radar (Artech House, 2003). Dr. Guerci also recently received the 2007 IEEE Warren D. White Award for “Excellence in Radar Adaptive Processing and Waveform Diversity”.
A graduate of Polytechnic University with a PhDEE (System Engineering), Dr. Guerci has also held adjunct professorships in engineering and applied mathematics at The City University of New York, Polytechnic University, The Cooper Union for Advancement of Art and Science, and Virginia Tech. Additionally, he has held senior engineer and scientist positions in industry and was recently Chief Technology Officer (CTO) for SAIC’s Research, Development, Test & Evaluation (RDT&E) Group. A member of the IEEE Radar Systems panel, he is also a Fellow of the IEEE for “Contributions to Advanced Radar Theory and its Embodiment in Real-World Systems”, holds eight US Patents and is a member of several industrial, academic and government advisory boards.