Journal ArticleDOI
A useful form of the Barankin lower bound and its application to PPM threshold analysis
R. McAulay,L. Seidman +1 more
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A form of Barankin's greatest lower bound on estimation error is obtained, which is easy to compute and easy to interpret, and is applied to a set of pulse-position modulation waveforms designed to reduce threshold effects.Abstract:
A form of Barankin's greatest lower bound on estimation error [7] is obtained, which is easy to compute and easy to interpret. This gives a lower bound on estimation error for non-linear modulation systems in an additive Gaussian noise back-ground. Threshold effects are included. This bound is applied to a set of pulse-position modulation waveforms designed to reduce threshold effects. It is shown that these signals do, in fact, offer reduced threshold levels (e.g., \approx 3.5 dB) with very small ( \approx \frac{1}{2} dB) degradation in large signal performance.read more
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Journal ArticleDOI
Some lower bounds on signal parameter estimation
Jacob Ziv,Moshe Zakai +1 more
TL;DR: New bounds are presented for the maximum accuracy with which parameters of signals imbedded in white noise can be estimated, which are independent of the bias and include explicitly the dependence on the a priori interval.
Journal ArticleDOI
Barankin Bounds on Parameter Estimation
R. McAulay,E. Hofstetter +1 more
TL;DR: It is shown that the Barankin bound reduces to the Cramer-Rao bound when the signal-to-noise ratio (SNR) is large, but as the SNR is reduced beyond a critical value, the Baranksin bound deviates radically from the C Kramer-R Rao bound, exhibiting the so-called threshold effect.
Journal ArticleDOI
A Barankin-type lower bound on the estimation error of a hybrid parameter vector
I. Reuven,Hagit Messer +1 more
TL;DR: A Barankin-type bound is presented which is useful in problems where there is a prior knowledge on some of the parameters to be estimated and which provides bounds on the covariance of any unbiased estimators of the nonrandom parameters and an estimator of the random parameters, simultaneously.
Journal ArticleDOI
Delay estimation using narrow-band processes
Siu-Kay Chow,P.M. Schultheiss +1 more
TL;DR: The Barankin bound is used to examine the effect of ambiguity on mean-square measurement error and the relative magnitude of the bounds in that region depends critically on the ratio of signal center frequency to signal bandwidth.
Journal ArticleDOI
Performance limitations and error calculations for parameter estimation
TL;DR: This paper summarizes the available approaches to studying performance and compares the resulting answers for a specific case and shows that the familiar Cramer-Rao lower bound on rms error yields an accurate answer only for large signal-to-noise ratios (SNR).
References
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