The eigenstructure based estimator designed to be used with the aid of the Gerschgorin's disk theorem is proposed for source number detection. By introducing the unitary transformation of the covariance matrix, the Gerschgorin radii of the eigenstructure are exploited to determine the number of sources while overcoming a lack of data samples, noise model and data independency information. Unlike conventional methods such as Akaike information criterion (AIC) and minimum descriptive length criterion (MDL), which are based on the cluster analysis of the eigenvalues used in conjunction with statistical formulations, the proposed method called the Gerschgorin disk estimator (GDE), provide more accurate detection of the source number in situations of both simulated and measured experimental data. >
['Hsien-Tsai Wu', 'Jar-Ferr Yang', 'Fwu-Kuen Chen']
Source number estimator using Gerschgorin disks