
Advances in radio frequency (RF) solid state transmitters and high performance embedded computing (HPEC) have afforded a new opportunity to “re-write” the textbooks on active sensing systems such as radar. Previously, radars were constrained to pre-determined set of transmit waveforms such as linear frequency modulation (LFM), and pseudo-random binary modulation with constant modulus. It is now possible to utilize advanced arbitrary waveform generators (AWGs) that are also adaptive. In this talk we will develop from first principles the theory of optimal and adaptive waveform design. We will see that to achieve optimality, knowledge of the entire multidimensional radar channel is required. Performance bounds for optimal detection and target ID are presented along with illustrative applications. The talk concludes with areas of ongoing and future research [1-5].
[1] J. R. Guerci, J. S. Bergin, R. J. Guerci, M. Khanin, and M. Rangaswamy, "A new MIMO clutter model for cognitive radar," IEEE (RadarConf), 2016.
[2] J. R. Guerci, R. M. Guerci, M. Ranagaswamy, J. S. Bergin, and M. C. Wicks, "CoFAR: Cognitive fully adaptive radar," IEEE (RadarConf), 2014.
[3] J. R. Guerci, Space-Time Adaptive Processing for Radar, 2nd Edition. Norwood, MA: Artech House, 2014.
[4] J. R. Guerci, "Cognitive Radar: The Next Radar Wave?," Microwave Journal, vol. 54, pp. 22-36, January 2011.
[5] J. R. Guerci, Cognitive Radar: The Knowledge-Aided Fully Adaptive Approach. Norwood, MA: Artech House, 2010.