Title :
Source Enumeration for High-Resolution Array Processing Using Improved Gerschgorin Radii Without Eigendecomposition
Author :
Huang, Lei ; Long, Teng ; Wu, Shunjun
Author_Institution :
Dept. of Electron. Eng., Beijing Inst. of Technol., Beijing
Abstract :
Accurate detection of sources with low complexity is of considerable interest in practical applications of high-resolution array processing. This paper addresses a new computationally efficient method for source enumeration by using enhanced Gerschgorin radii without eigendecompositofion. The proposed method can calculate the Gerschgorin radii in a more efficient manner, in which the additive background noise can be efficiently suppressed and the computational complexity can be considerably reduced. Therefore, the method is more accurate and computationally attractive. Furthermore, the method does not rely on the eigenvalues of a covariance matrix or the signal/noise power, making it robust against deviations from the assumption of spatially white noise model. Numerical results are presented to demonstrate the performance of the method.
Keywords :
array signal processing; computational complexity; covariance matrices; eigenvalues and eigenfunctions; source separation; white noise; Gerschgorin radii; accurate source detection; additive background noise; computational complexity; covariance matrix; eigendecomposition; eigenvalues; high-resolution array processing; signal/noise power; source enumeration; white noise model; Direction finding; Eigenvalue decomposition (EVD); Gerschgorin Radii; Gerschgorin radii; High resolution; Minimum description length (MDL); Multistage Wiener fiber (MSWF); Sensor array signal processing; Signal enumeration; eigenvalue decomposition (EVD); high resolution; minimum description length (MDL); multistage Wiener filter (MSWF); sensor array signal processing; signal enumeration;
Journal_Title :
Signal Processing, IEEE Transactions on
DOI :
10.1109/TSP.2008.929331