DocumentCode :
1781220
Title :
CoFAR: Cognitive fully adaptive radar
Author :
Guerci, Joseph R. ; Guerci, R.M. ; Ranagaswamy, M. ; Bergin, J.S. ; Wicks, Michael
Author_Institution :
Cognitive Syst. Div., Guerci Consulting LLC, Arlington, VA, USA
fYear :
2014
fDate :
19-23 May 2014
Abstract :
A new and fully adaptive environmentally aware (cognitive) radar and signal processing architecture is introduced to meet the challenges of increasingly complex operating environments. The system features fully adaptive transmit, receive, and controller/scheduler functions. “Cognition”, i.e., learning/understanding the complete multidimensional radar channel (targets, clutter, interference, etc.) and operating environment is achieved via a sense-learn-adapt (SLA) approach, which is a radar centric application of the OOPDA (observe, orient, predict, decide, act) loop concept. Learning in turn is achieved via expert system, knowledge-aided (KA) supervised training. Lastly, a MIMO probing approach is introduced as a learning aid for signal dependent channel effects and illustrated with a MTI radar example where it is shown that a full rank estimate of the clutter covariance matrix is possible from the returns in a single range bin, thereby alleviating the so-called “sample starved” covariance estimation problem that arises in highly nonstationary environments.
Keywords :
MIMO radar; adaptive radar; covariance matrices; learning (artificial intelligence); radar signal processing; CoFAR; MIMO probing approach; MTI radar; OOPDA loop concept; SLA approach; clutter covariance matrix; cognitive fully adaptive radar; complete multidimensional radar channel; complex operating environments; knowledge-aided supervised training; radar centric application; sample starved covariance estimation problem; sense-learn-adapt approach; signal processing architecture; Channel estimation; Clutter; Cognition; Computer architecture; MIMO; Radar; Receivers; MIMO; MTI; OOPDA loop; STAP; channel estimation; cognitive radar;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Radar Conference, 2014 IEEE
Conference_Location :
Cincinnati, OH
Print_ISBN :
978-1-4799-2034-1
Type :
conf
DOI :
10.1109/RADAR.2014.6875736
Filename :
6875736
Link To Document :
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