DocumentCode :
2287828
Title :
Multiple covariance matrix spectral model for direction of arrival
Author :
Alnajjar, Hisham ; Wilkes, D.M.
Author_Institution :
Dept. of Eng. Technol., Austin Peay State Univ., Clarksville, TN, USA
fYear :
1995
fDate :
26-29 Mar 1995
Firstpage :
402
Lastpage :
405
Abstract :
Presents a novel algorithm for modeling the behavior of the measured eigenvalues in order to find the direction of arrivals (DOAs) of sources. The authors use only the eigenvalues and not the eigenvectors to find the DOAs; no other algorithm works this way. The modeling process is based on the critical distance formula developed previously by the authors, which describes the best location to add a sensor to an existing subarray in order to improve the resolution performance of an array, also it is based on the concept of a structurally adaptive array, which promotes the idea of adapting the size and geometry of a subarray (of a much larger array) in order to optimize the detection for different scenarios
Keywords :
adaptive signal processing; covariance matrices; direction-of-arrival estimation; eigenvalues and eigenfunctions; optimisation; signal resolution; spectral analysis; critical distance formula; direction of arrival; eigenvalues; multiple covariance matrix spectral model; optimization; resolution performance; structurally adaptive array; Adaptive arrays; Covariance matrix; Current measurement; Eigenvalues and eigenfunctions; Electric variables measurement; Geometry; Sensor arrays; Sensor phenomena and characterization; Signal resolution; Solid modeling;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Southeastcon '95. Visualize the Future., Proceedings., IEEE
Conference_Location :
Raleigh, NC
Print_ISBN :
0-7803-2642-3
Type :
conf
DOI :
10.1109/SECON.1995.513126
Filename :
513126
Link To Document :
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