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Patent Number: |
h2222 |
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Case ID: |
0 |
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Patent Title:
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Normalized matched filter--a low rank approach
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Status: |
ACTIVE |
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Status Date: |
6/17/2009 4:21:22 PM |
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Issue Date:
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8/5/2008 |
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Filed Date:
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10/13/2005 |
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Serial #:
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1/251,007 |
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Assignee Name:
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The United States of America as represented by the Secretary of the Air Force
(Washington,
DC)
N/A
(
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Inventor(s):
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Rangaswamy, Muralidhar , Lin, Freeman |
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Lab Name: |
Human Effectiveness Directorate |
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Location: |
2610 Seventh Street, Building 441
Wright-Patterson AFB, OH 45433-7901 |
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Contact: |
Contact Lab About This Patent |
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BACKGROUND OF THE INVENTION
The invention relates generally to radar receivers, and more specifically, it relates to a low rank approximation to interference covariance for target detection in non-Gaussian clutter.
This invention addresses the problem of signal detection in interference composed of clutter (and possibly jamming), having a covariance matrix with known structure but unknown level and background white noise. The technique developed in this
paper ensures invariance with respect to the unknown level and the background noise power. The research is motivated by the problem of space-time adaptive processing (STAP) for airborne phased-array radar applications. Typically, a radar receiver front
end consists of an array of J antenna elements processing N pulses in a coherent processing interval. We are interested in the problem of target detection given the JN.times.1 spatio-temporal data vector.
Patented art of interest includes the following U.S. Pa . . . . More |
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This invention addresses the problem of radar target detection in severely
heterogeneous clutter environments. Specifically, we present the
performance of the normalized matched filter test in a background of
disturbance consisting of clutter having a covariance matrix with known
structure and unknown scaling plus background white Gaussian noise. It is
shown that when the clutter covariance matrix is low rank, the (LRNMF)
test retains invariance with respect to the unknown scaling as well as
the background noise level and has an approximately constant false alarm
rate (CFAR). Therefore, a technique known as self-censoring reiterative
fast maximum likelihood/adaptive power residue (SCRFML/APR) is developed
to treat this problem and its performance is discussed. The SCRFML/AP
method is used to estimate the unknown covariance matrix in the presence
of outliers. This covariance matrix estimate can then be used in the
LRNAMF o . . . . More |
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What is claimed is:
1. A radar target detection process for producing a target detection signal from a radar data stream received from a heterogeneous clutter environment with clutter and
interference using a signal vector with radar target detection process producing a detection signal for hypothesis H.sub.0, when the signal of interest is not present in the observed data signal and H.sub.1 when the signal of interest is present in the
observed data signal, said radar target detection process comprising the steps of: forming an estimate of a covariance matrix of the clutter and interference in the heterogeneous clutter environment; a first subtracting step that comprises subtracting
the signal vector from the observed data signal from the host system to produce thereby a first subtraction signal; estimating the signal of interest from the observed data signal to produce an estimate signal; a first step which uses a first linear
prediction error filter which processes the f . . . . More |
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