CoFAR: Cognitive fully adaptive radar

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.

[1]  S. Haykin,et al.  Cognitive radar: a way of the future , 2006, IEEE Signal Processing Magazine.

[2]  Joseph R. Guerci,et al.  On Periodic Autoregressive Processes Estimation , 2000 .

[3]  Joseph R. Guerci,et al.  ISAT - innovative space-based-radar antenna technology , 2003, IEEE International Symposium on Phased Array Systems and Technology, 2003..

[4]  William L. Melvin Space-time adaptive processing and adaptive arrays: special collection of papers , 2000, IEEE Trans. Aerosp. Electron. Syst..

[5]  Daniel W. Bliss Coherent MIMO radar , 2010, 2010 International Waveform Diversity and Design Conference.

[6]  Charles R. Johnson,et al.  Topics in Matrix Analysis , 1991 .

[7]  J.R. Guerci,et al.  Knowledge-aided adaptive radar at DARPA: an overview , 2006, IEEE Signal Processing Magazine.

[8]  D.W. Bliss,et al.  Multiple-input multiple-output (MIMO) radar: performance issues , 2004, Conference Record of the Thirty-Eighth Asilomar Conference on Signals, Systems and Computers, 2004..

[9]  Daniel W. Bliss,et al.  Multiple-input multiple-output (MIMO) radar and imaging: degrees of freedom and resolution , 2003, The Thrity-Seventh Asilomar Conference on Signals, Systems & Computers, 2003.

[10]  V. C. Vannicola Expert system for sensor resource allocation (radar application) , 1990, Proceedings of the 33rd Midwest Symposium on Circuits and Systems.

[11]  Joseph R. Guerci,et al.  Space-Time Adaptive Processing for Radar , 2003 .

[12]  J. R. Guerci,et al.  Cognitive radar: A knowledge-aided fully adaptive approach , 2010, 2010 IEEE Radar Conference.

[13]  M. Melamed Detection , 2021, SETI: Astronomy as a Contact Sport.

[14]  W.L. Melvin,et al.  An approach to knowledge-aided covariance estimation , 2006, IEEE Transactions on Aerospace and Electronic Systems.

[15]  A. Farina,et al.  Knowledge-based radar signal and data processing: a tutorial review , 2006, IEEE Signal Processing Magazine.

[16]  Harry L. Van Trees,et al.  Detection, Estimation, and Modulation Theory, Part I , 1968 .

[17]  D. W. Bliss,et al.  GMTI MIMO radar , 2009, 2009 International Waveform Diversity and Design Conference.