By Topic

Resolution capability of nonlinear spectral-estimation methods for short data lengths

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 $31
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

2 Author(s)
Prabhu, K.M.M. ; Dept. of Electr. Eng., Indian Inst. of Technol., Madras, India ; Bhoopathy Bagan, K.

The performance of nonlinear power spectral estimation methods is studied from the viewpoint of resolution. The methods considered are the maximum entropy method, the maximum likelihood method, the least-squares method, Prony's energy spectral-density method, the singular-value decomposition technique and the autoregressive moving-average power spectral-estimation method. The data model used comprises two sinusoidal signals of equal amplitudes immersed in white Gaussian noise. The minimum resolution that can be obtained for all the power spectral-estimation methods considered has been studied for different data lengths and signal-to-noise ratios and the results are tabulated.

Published in:

Radar and Signal Processing, IEE Proceedings F  (Volume:136 ,  Issue: 3 )