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
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;
Conference_Titel :
Southeastcon '95. Visualize the Future., Proceedings., IEEE
Conference_Location :
Raleigh, NC
Print_ISBN :
0-7803-2642-3
DOI :
10.1109/SECON.1995.513126