Estimation of pulse parameters by autoconvolution and least squares

15Citations
Citations of this article
9Readers
Mendeley users who have this article in their library.
Get full text

Abstract

Let the parameter vector of a baseband pulse be μ=[D,A,W]T, where D=arrival time, A=amplitude, and W=width. A method for estimating μ for a pulse present in a noisy data segment is given. We start by performing an autoconvolution (AC) of the data segment, and then recording the shift where the AC peaks. By taking half of that shift, from the end of the segment, a point is placed near the middle of the pulse. Next, we partition the pulse at that point and perform two more ACs, (one on the left half of the pulse and another on the right half), and find two more shifts where the ACs peak. These two shifts provide coarse measurements on D and W. A further refinement by least squares (LS) then produces a final estimate for μ. Simulation results have corroborated the theoretical development and shown that the new estimator performs close to the Cramer-Rao lower bound (CRLB). © 2006 IEEE.

Cite

CITATION STYLE

APA

Chan, Y. T., Lee, B. H., Inkol, R., & Chan, F. (2010). Estimation of pulse parameters by autoconvolution and least squares. IEEE Transactions on Aerospace and Electronic Systems, 46(1), 363–374. https://doi.org/10.1109/TAES.2010.5417168

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free