A COMPARISON OF THE BURG AND THE KNOWN-AUTOCORRELATION AUTOREGRESSIVE SPECTRAL ANALYSIS OF COMPLEX SINUSOIDAL SIGNALS IN ADDITIVE WHITE NOISE
- Authors
- 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
Document 1 of 1
- Date modified: