Notification:
We are currently experiencing intermittent issues impacting performance. We apologize for the inconvenience.
By Topic

Threshold detection in correlated non-Gaussian noise fields

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

1 Author(s)
Middleton, D. ; 127 E. 91 Street, New York, NY, USA

Classical threshold detection theory for arbitrary noise and signals, based on independent noise samples, i.e., using only the first-order probability density of the noise, is generalized to include the critical additional statistical information contained in the (first-order) covariances of the noise. This is accomplished by replacing the actual, generalized noise by a “quasi-equivalent” (QE-)model employing both the first-order PDF and covariance. The result is a “near-optimum” approach, which is the best available to date incorporating these fundamental statistical data. Space-time noise and signal fields are specifically considered throughout. Even with additive white Gaussian noise (AWGN) worthwhile processing gains per sample (Γ(c)) are attainable, often O(10-20 dB), over the usual independent sampling procedures, with corresponding reductions in the minimum detectable signal. The earlier moving average (MA) noise model, while not realistic, is included because it reduces in the Gaussian noise cases to the threshold optimum results of previous analyses, while the QE-model remains suboptimum here because of the necessary constraints imposed in combining the PDF and covariance information into the detector structure. Full space-time formulation is provided in general, with the important special cases of adaptive and preformed beams in reception. The needed (first-order) PDF here is given by the canonical Class A and Class B noise models. The general analysis, including the canonical threshold algorithms, correlation gain factors Γ(c), detection parameters for the QE-model, along with some representative numerical results for both coherent and incoherent detection, based on four representative Toeplitz covariance models is presented

Published in:

Information Theory, IEEE Transactions on  (Volume:41 ,  Issue: 4 )