By Topic

Optimum weighting functions for the detection of sampled signals in noise

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)

The problem of designing a linear predetection filter for the detection of a sampled random signal in additive noise is considered. The design of the filter is based on an optimality criterion which maximizes the signal-to-noise ratio enhancement. The optimum weighting function obtained in this manner has the advantage that it is independent of signal characteristics and depends only on the covariance function of the noise. The optimum filter, for general covariance functions, is obtained forN = 2, 3and4samples. The asymptotic solution for largeNis also presented by employing results from the theory of Teeplitz forms. In addition, the complete solution for allNis given for several particular covariance matrices. An application of the results is made to the problem of designing a linear predetection filter in a moving target indication (MTI) radar system. The optimum weighting function forN = 2is a single-cancellation unit, while that forN = 3is similar but not quite the same as a double-cancellation unit. It is shown that the signal-to-noise ratio enhancement provided by the double-cancellation scheme is1.76db worse than that of the optimum filter when the noise has a Gaussian covariance function.

Published in:

Information Theory, IEEE Transactions on  (Volume:10 ,  Issue: 2 )