Abstract—Accurate detection of sources with low complexity is of considerable interest in practical applications of high-resolu-tion array processing. This paper addresses a new computationally efficient method for source enumeration by using enhanced Ger-schgorin radii without eigendecomposition. 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 at-tractive. Furthermore, the method does not rely on the eigenvalues of a covariance matrix or the signal/noise power, making it ro-bust against deviations from the assumption ...
Source localization and spectral estimation are among the most fundamental problems in statistical a...
Source number estimation methods for single channel signal have been investigated and the improvemen...
In array signal processing, the detection of the number of sources is an important step. Most approa...
Estimating the number of sources impinging on an array of sensors, termed as source enumeration, is ...
Abstract—This paper proposes a reduced-rank minimum de-scription length (MDL) method to enumerate th...
In this PhD thesis, one of the most fundamental problems in sensor array processing is investigated,...
It is interesting to determine the number of signals impinging upon a large array with small samples...
In this paper, we propose an algorithm for detecting the number $M$ of Gaussian sources received by ...
Caption title.Includes bibliographical references (p. 13).Research supported by the National Science...
Abstract—In this paper, we propose an algorithm for detecting the number of Gaussian sources receive...
© 2020 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for a...
This thesis deals with detection and estimation problems in sensor array signal processing. We treat...
Most of the number of sources estimation techniques use the well-known signal-subspace approach in w...
We address the problem of source detection in array signal processing when the noise over the sensor...
Source localization and spectral estimation are among the most fundamental problems in statistical a...
Source number estimation methods for single channel signal have been investigated and the improvemen...
In array signal processing, the detection of the number of sources is an important step. Most approa...
Estimating the number of sources impinging on an array of sensors, termed as source enumeration, is ...
Abstract—This paper proposes a reduced-rank minimum de-scription length (MDL) method to enumerate th...
In this PhD thesis, one of the most fundamental problems in sensor array processing is investigated,...
It is interesting to determine the number of signals impinging upon a large array with small samples...
In this paper, we propose an algorithm for detecting the number $M$ of Gaussian sources received by ...
Caption title.Includes bibliographical references (p. 13).Research supported by the National Science...
Abstract—In this paper, we propose an algorithm for detecting the number of Gaussian sources receive...
© 2020 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for a...
This thesis deals with detection and estimation problems in sensor array signal processing. We treat...
Most of the number of sources estimation techniques use the well-known signal-subspace approach in w...
We address the problem of source detection in array signal processing when the noise over the sensor...
Source localization and spectral estimation are among the most fundamental problems in statistical a...
Source number estimation methods for single channel signal have been investigated and the improvemen...
In array signal processing, the detection of the number of sources is an important step. Most approa...