Statement of Work (SOW)

We propose a synergistic, multi-disciplinary, multi-university research program that will substantially increase both radar resolution, detection and accuracy, as well as communication systems capacity.

This will be done by integrated transmit waveform optimization involving the development of waveform parameterizations and libraries, methods for optimal waveform selection in real-time, and application-matched objective/cost functions. Recent developments in flexible digital waveform modulator hardware have hastened the day when it will be practical to adjust the transmit waveform on a periodic basis, as often as pulse-by-pulse if required, for the best overall system performance in a dynamically changing scenario. However, research on adaptive waveform selection has been sporadic to date, therebylimiting what could and should be dramatic technological advances in systems involving the transmission of probing or information-carrying signals.

We propose a broad plan of enabling research and technology that will be carried out by a team of eleven leading scientists and divided into the four following tasks:

• Task 1: unified approach to waveform design. Advanced research will be conducted towards incorporating current and new signal diversities in an integrated manner. Waveform diversity will be explored along numerous multiple dimensions including time, space, frequency, phase, power, and polarization; the research will draw upon concepts underlying ultrawideband signals, orthogonal frequency division multiplexing, code division multiple access, Prometheus orthonormal sets, and recent advances in time-varying signals.
• Task 2: environment and channel modeling. A new, general framework will be developed to obtain channel models used for optimal waveform design. Drawing on this, models will be developed for MIMO radars, time-varying and dispersive channels, polarimetric targets and multipath channel, propagation in layered media, stochastic clutter, and communication systems under different scenarios. Techniques will be developed to select the appropriate model.
• Task 3: optimization. We will introduce cost functions and sensor management schemes to optimally design the waveforms in diverse operational environments for both sensing and communications applications. Activities include enhancement of the classical ambiguity function for the optimization of the cost function for communication, multitask, and sensor systems.
• Task 4: applications and validations. Applications of our waveform design techniques will be pursued for systems of interest including multistatic radars, distributed platforms, countermeasures, and polarimetric radars.Experimental validations will be conducted inside an anechoic chamber and a radar test tower. Other issues include detection, STAP, hot clutter, and robust design.

Block diagram of adaptive waveform design

This investigation will be led by the University of Illinois at Chicago in collaboration with 5 other funded institutions: Arizona State University, Harvard University, University of Maryland, Princeton University, and Purdue University. Two independently-funded collaborations are with Raytheon Missile Systems and the University of Melbourne, Australia.