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Linearly Constrained Minimum-Variance Algorithm for Radar Jammer and Clutter…

Award Information

Department of Defense
Missile Defense Agency
Award ID:
Program Year/Program:
2003 / SBIR
Agency Tracking Number:
Solicitation Year:
Solicitation Topic Code:
Solicitation Number:
Small Business Information
Information Systems Laboratories, Inc.
10070 Barnes Canyon Road San Diego, CA 92121
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Woman-Owned: No
Minority-Owned: No
HUBZone-Owned: No
Phase 1
Fiscal Year: 2003
Title: Linearly Constrained Minimum-Variance Algorithm for Radar Jammer and Clutter Suppression
Agency / Branch: DOD / MDA
Contract: F3060203C0238
Award Amount: $69,696.00


We propose an augmented linearly constrained minimum-variance algorithm for radar jammer and clutter suppression. The basic LCMV algorithm is augmented to extend the simple target detection capability to target classification. In general, received radarreturns are comprised of a linear superposition of the target return signal and mainbeam and sidelobe jammer signals and clutter returns, which corrupt or obscure the desired signal. One of the objectives of signal processing algorithms is to extract andamplify the target returns and reject or suppress the jammer signals and clutter. We propose to develop and apply a real-time algorithm for isolating target signals from jammer and clutter interference, while minimizing the output variance of the receiverresponse to the latter. The signal-to-noise ratio (SNR)is expressed as a Raleigh quotient and its optimization leads to a generalized eigenvalue problem. The solution yields a linear transformation which, when applied to the receiver response, maximizesthe SNR. The result is the strongest (in the SNR sense) signal as far removed from jammer signals and clutter as possible, for maximum detectability. The results are expanded to enable target classification. The algorithm we propose has potentialapplications in remote sensing tasks in government and private industry, planetary surveying and mapping, and in private and commercial civilian aviation, as well as in military scenarios.

Principal Investigator:

James D. Brasher
Executive Scientist

Business Contact:

James H. Boschma
Vice President and Divisi
Small Business Information at Submission:

10070 Barnes Canyon Road San Diego, CA 92121

EIN/Tax ID: 541198316
Number of Employees:
Woman-Owned: No
Minority-Owned: No
HUBZone-Owned: No