DocumentCode :
3510873
Title :
On DOA estimation based on higher order statistics
Author :
Scarano, G. ; Mattioli, A. Guidarelli ; Jacovitti, G.
Author_Institution :
Dip. Infocom, Roma Univ., Italy
fYear :
1993
fDate :
1993
Firstpage :
285
Lastpage :
289
Abstract :
The authors present a DOA estimation procedure which is based on the assumption of highly correlated Gaussian noise contaminating nonGaussian sources, and which jointly employs second order statistics and higher order cumulants statistics. From second order statistics, they identify a set of candidate angles in which both true signal DOA´s and spourious noise induced DOA´s are present. Then, the signal DOA´s are extracted by resorting to higher order statistics and to the nonGaussianity of the sources. Even though the estimates are biased when the noise is not fully correlated, simulation results show that, for SNR values below a certain threshold, this bias does not (significantly) affect the estimation accuracy and that the proposed approach outperforms the straight-forward application of Root-MUSIC to the matrix of fourth order cumulants.
Keywords :
array signal processing; random noise; statistical analysis; DOA estimation; SNR; biased estimates; correlated Gaussian noise; estimation accuracy; higher order cumulants; higher order statistics; nonGaussian sources; second order statistics; simulation results; spourious noise; Covariance matrix; Direction of arrival estimation; Equations; Gaussian noise; Higher order statistics; Matrix decomposition; Multiple signal classification; Sensor arrays; Signal processing; Signal to noise ratio;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Higher-Order Statistics, 1993., IEEE Signal Processing Workshop on
Conference_Location :
South Lake Tahoe, CA, USA
Print_ISBN :
0-7803-1238-4
Type :
conf
DOI :
10.1109/HOST.1993.264550
Filename :
264550
Link To Document :
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