A COMPARISON OF THE BURG AND THE KNOWN-AUTOCORRELATION AUTOREGRESSIVE SPECTRAL ANALYSIS OF COMPLEX SINUSOIDAL SIGNALS IN ADDITIVE WHITE NOISE

Authors
  1. Herring, R.W.
Corporate Authors
Communications Research Centre, Ottawa ONT (CAN)
Abstract
Burg's algorithm for Maximum Entropy autoregressive spectral estimation is analyzed for the cases of one and two complex sinusoidal signals in additive white noise. For the latter case are found two biases which can account for the line splitting and line shifting that occur in simulation studies when the SNR is very high. These biases vanish completely if the two complex sinusoids are in phase quadrature at the middle of the data record; if there is an integral number of half-cycles of difference frequency contained in the data record, then the power level of the spectral estimate will be biased although the effects believed to cause splitting and shifting will be eliminated. Results of simulation studies to support these conjectures are presented.
Report Number
1326 —
Date of publication
15 Sep 1979
Number of Pages
35
DSTKIM No
80-00272
CANDIS No
124966
Format(s):
Hardcopy;Originator's fiche received by DSIS

Permanent link

Document 1 of 1

Date modified: