Low Complexity Adaptive Algorithms for Airborne ECCM

Award Information
Agency: Department of Defense
Branch: Air Force
Contract: N/A
Agency Tracking Number: 25901
Amount: $58,348.00
Phase: Phase I
Program: SBIR
Solicitation Topic Code: N/A
Solicitation Number: N/A
Timeline
Solicitation Year: N/A
Award Year: 1994
Award Start Date (Proposal Award Date): N/A
Award End Date (Contract End Date): N/A
Small Business Information
2243 Chimney Swift Circle, Marietta, GA, 30062
DUNS: N/A
HUBZone Owned: N
Woman Owned: N
Socially and Economically Disadvantaged: N
Principal Investigator
 Mr. Jay Scott Goldstein
 (404) 874-9856
Business Contact
Phone: () -
Research Institution
N/A
Abstract
Recent research has shown that effective jammer and clutter suppression is best performed with fully space-time adaptive processing. However, allowing adaptive weights on every tap on every element is computationally prohibitive and requires too many samples to converge. Eigenvalue analysis shows that the required number of degrees of freedom (DOF) is significantly less than the dimensionality of the space-time data (i.e. the total # of DOF's). Therefore it should not be necessary to use adaptive weights on every tap of every element. The objective then becomes to reduce the number of DOF's (=adaptive weights) used for interference suppression. We propose a general and fundamental two-dimensional subband decomposition approach which optimally (in terms of canceller mean squared error) chooses the desired number of DOF's using an easily computed criterion. Each adaptive weight operates on a linear combination of sensor and tap data, rather than a subset of sensors and taps. M degrees of freedom corresponds to M linear combinations. Furthermore, these linear combinations are formed in a data-dependent but easily computed way, so that the DOF's can change as the interference changes.

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