Optimum array detector for a weak signal in unknown noise

We study the design of constant false-alarm rate (CFAR) tests for detecting a rank-one signal in the presence of background Gaussian noise with unknown spatial covariance. We look at invariant tests, i.e., those tests whose performance is independent of the nuisance parameters, like the background n...

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Bibliographic Details
Published in:IEEE transactions on aerospace and electronic systems 1996-07, Vol.32 (3), p.911-922
Main Authors: Bose, S., Steinhardt, A.O.
Format: Article
Language:English
Subjects:
Applied sciences
Background noise
Detection, estimation, filtering, equalization, prediction
Detectors
Exact sciences and technology
Gaussian noise
Information, signal and communications theory
Matched filters
Sensor arrays
Signal and communications theory
Signal design
Signal detection
Signal to noise ratio
Signal, noise
Statistical analysis
Telecommunications and information theory
Testing
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Summary:We study the design of constant false-alarm rate (CFAR) tests for detecting a rank-one signal in the presence of background Gaussian noise with unknown spatial covariance. We look at invariant tests, i.e., those tests whose performance is independent of the nuisance parameters, like the background noise covariance. Such tests are shown to have the desirable CFAR property. We characterize the class of all such tests by showing that any invariant decision statistic can be written as a function of two basic statistics which are in fact the adaptive matched filter (AMF) statistic and Kelly's generalized likelihood ratio statistic. Further, we establish an optimum test in the limit of low signal-to-noise ratio (SNR), the locally most powerful invariant (LMPI) test. We also derive the bound for the probability of detection of any invariant detector, at a fixed false-alarm rate, and compare the LMPI and the published detectors (Kelly and AMF) to it.
ISSN:0018-9251
1557-9603
DOI:10.1109/7.532252