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Robust Wideband Waveforms for Synthetic Aperture Radar (SAR) and Ground Moving Target Indication (GMTI) Applications

Award Information
Agency: Department of Defense
Branch: Defense Advanced Research Projects Agency
Contract: W31P4Q-09-C-0449
Agency Tracking Number: 08SB2-0382
Amount: $98,930.00
Phase: Phase I
Program: SBIR
Solicitation Topic Code: SB082-020
Solicitation Number: 2008.2
Solicitation Year: 2008
Award Year: 2009
Award Start Date (Proposal Award Date): 2009-08-19
Award End Date (Contract End Date): 2010-04-20
Small Business Information
317 Harrington Avenue Suites 9 & 10
Closter, NJ 07624
United States
DUNS: 001562821
HUBZone Owned: No
Woman Owned: No
Socially and Economically Disadvantaged: No
Principal Investigator
 KeYong Li
 Senior Engineer
 (201) 768-4448
Business Contact
 Mary Kritikos
Title: Office Manager and Accountant
Phone: (201) 768-4448
Research Institution

High resolution SAR imaging and Ground moving target indicator (GMTI) radar are of critical value to modern intelligence surveillance and reconnaissance missions. High resolution SAR can be realized at the expense of wide bandwidth waveform. However, to achieve long dwells over a wideband width, often the operating frequency band can overlap with other co-band radars, and it becomes necessary to notch out those interference bands both in the transmit mode and the receive mode. Thus it becomes necessary to design wideband transmit waveforms with spectral notches to null out the co-channel interference while maintaining excellent pulse compression with good sidelobe properties. A solution to this problem is presented in this proposal. The new solution leads to poor range resolution and to compensate that, two new receiver design strategies to suppress the sidelobes are also presented here. For azimuth compression, the carrier frequency plays a crucial role in narrowband SAR. However, the use of wide bandwidth leads to a less well defined role for the carrier frequency resulting in poorer azimuth resolution. This fundamental problem is addressed here using a new approach that draws on recent results on non-linear sparsity based image processing methods.

* Information listed above is at the time of submission. *

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