Exploiting Agile Waveforms and Sampling for Compressive Sensing Radar Navy SBIR FY2011.2 Sol No.: Navy SBIR FY2011.2 Topic No.: N112-161 Topic Title: Exploiting Agile Waveforms and Sampling for Compressive Sensing Radar Proposal No.: N112-161-1029 Firm: Scientific Systems Company, Inc 500 West Cummings Park - Ste 3000 Woburn, Massachusetts 01801-6562 Contact: Les Novak Phone: (781) 933-5355 Web Site: www.ssci.com Abstract: Compressive Sensing (CS) has provided the radar community with a new mathematical framework for efficient and robust data collection and image formation. According to the theory of compressive sensing, a signal that is sparse in some domain can be recovered using far fewer samples than required by the Nyquist Sampling Theorem. Applications to radar were quick to emerge; the availability of high-resolution (traditional and synthetic aperture) radars that gather enormous amounts of data require faster, more efficient data processing algorithms to process the data. CS concepts have been applied to the radar imaging function; high range/velocity resolutions have been achieved using sufficiently smaller bandwidth than traditional radars. MIMO (multi-input, multi-output) radar has also provided the radar community with radar designs that achieve superior resolution compared to traditional systems having the same number of transmit and receive antennas. It is reasonable, therefore, to apply CS concepts to the design of MIMO radar systems. Since the direction of arrival (DOA) of targets approaching a radar system form a sparse vector in range-Doppler-angle space, compressive sensing concepts can be applied to the MIMO radar image formation and DOA estimation problems. SSCI is developing optimum radar transmit waveforms for CS/MIMO systems. Benefits: Radar systems using Compressive Sensing (CS) and Multi-input, Multi-output (MIMO) antenna configurations that exploit optimized random transmit waveforms are more robust to interference and jamming and would minimally interfere with other (military or civilian) EM operations. Such a system would be stealthier and more difficult to counter due to its randomized transmit waveforms. And the optimized transmit waveforms would provide robust and complete coverage of the signal spaces. Compressive radar sensing systems may designed to detect isolated sparse scatterers while reducing the returns from high sea-state clutter by better fitting sea-clutter signals in appropriate over-determined bases, thereby providing better detection performance against periscopes and small craft. Downlink requirements are of course minimized due to the reduced sampling afforded by CS systems - and down-linking of transmitted waveform information to ensure accurate CS-image reconstructions is also minimized. Return