DocumentCode
1701224
Title
Eigenvalue shift supperresolution algorithm
Author
Yongjun, Zhang ; Zongzhi, Chen ; Wei, Ye
Author_Institution
Inst. of Command & Technol., COSTIND, Beijing, China
Volume
1
fYear
1996
Firstpage
185
Abstract
This paper provides a new approach to spatial spectral estimation, called eigenvalue shift superresolution algorithm (ESSA). This method avoids the inverse covariance matrix. It can be applied to the processing of data received by spatially distributed arrays of sensors
Keywords
adaptive signal processing; array signal processing; covariance matrices; direction-of-arrival estimation; eigenvalues and eigenfunctions; signal resolution; spectral analysis; array signal processing; covariance matrix; data processing; eigenvalue shift supperresolution algorithm; high resolution adaptive methods; spatial spectral estimation; spatially distributed sensor arrays; Adaptive arrays; Covariance matrix; Eigenvalues and eigenfunctions; Phased arrays; Sensor arrays; Sensor phenomena and characterization; Signal processing; Signal resolution; Spatial resolution; Vectors;
fLanguage
English
Publisher
ieee
Conference_Titel
Signal Processing, 1996., 3rd International Conference on
Conference_Location
Beijing
Print_ISBN
0-7803-2912-0
Type
conf
DOI
10.1109/ICSIGP.1996.567094
Filename
567094
Link To Document