DocumentCode :
3061756
Title :
Maximum entropy power spectrum estimation with uncertainty in correlation measurements
Author :
Schott, Jean-Pierre ; McClellan, James H.
Author_Institution :
Massachusetts Institute of Technology, Cambridge, MA
Volume :
8
fYear :
1983
fDate :
30407
Firstpage :
1068
Lastpage :
1071
Abstract :
The purpose of this paper is Co present a multidimensional MEM algorithm, valid for non-uniformly sampled arrays, which satisfies a "corrrelation-approximatily" constraint. To this end, the correlation matching.equality constraints of the usual MEM are replaced by a single inequality constraint whose form is based on a measure of the noise in the given acf. In this way, one can incorporate into the model knowledge of the noisy nature of the "given" acf, since the "given" acf is usually estimated from samples of the wavefield. The algorithm has been tested with 1-D synthetic data representing multiple sinusoids buried in additive white noise. The performance of this modified MEM algorithm is compared to a traditional MEM algorithm for extendible acfs and for different SNRs.
Keywords :
Covariance matrix; Entropy; Measurement uncertainty; Multidimensional systems; Noise measurement; Pollution measurement; Power measurement; Sea measurements; Spectral analysis; Testing;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Acoustics, Speech, and Signal Processing, IEEE International Conference on ICASSP '83.
Type :
conf
DOI :
10.1109/ICASSP.1983.1171967
Filename :
1171967
Link To Document :
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