The Experts below are selected from a list of 106599 Experts worldwide ranked by ideXlab platform

O Ritzau Eigaard - One of the best experts on this subject based on the ideXlab platform.

Petre Stoica - One of the best experts on this subject based on the ideXlab platform.

  • Source Resolvability of Spatial-Smoothing-Based Subspace Methods: A Hadamard Product Perspective
    IEEE Transactions on Signal Processing, 2019
    Co-Authors: Zai Yang, Petre Stoica, Jinhui Tang
    Abstract:

    A major drawback of subspace methods for direction-of-arrival estimation is their poor performance in the presence of coherent sources. Spatial smoothing is a common solution that can be used to restore the performance of these methods in such a case at the cost of increased array size requirement. In this paper, a Hadamard Product Perspective of the source resolvability problem of spatial-smoothing-based subspace methods is presented. The array size that ensures resolvability is derived as a function of the source number, the rank of the source covariance matrix, and the source coherency structure. This new result improves upon previous ones and recovers them in special cases. It is obtained by answering a long-standing question first asked explicitly in 1973 as to when the Hadamard Product of two singular positive-semidefinite matrices is strictly positive definite. The problem of source identifiability is discussed as an extension. Numerical results are provided that corroborate our theoretical findings.

  • hadamard Product Perspective on source resolvability of spatial smoothing based subspace methods
    International Conference on Acoustics Speech and Signal Processing, 2019
    Co-Authors: Zai Yang, Petre Stoica
    Abstract:

    Spatial smoothing is a common preprocessing scheme for subspace methods that resolves their sensitivity to coherent sources. The source resolvability problem of spatial-smoothing-based subspace methods has been extensively investigated using different analysis techniques. In this paper, a unified Hadamard Product technique is provided to recover these results. This is done by answering a long-standing question in linear algebra as to under what conditions the Hadamard Product of two singular positive-semidefinite matrices is positive definite.

  • ICASSP - Hadamard Product Perspective on Source Resolvability of Spatial-smoothing-based Subspace Methods
    ICASSP 2019 - 2019 IEEE International Conference on Acoustics Speech and Signal Processing (ICASSP), 2019
    Co-Authors: Zai Yang, Petre Stoica
    Abstract:

    Spatial smoothing is a common preprocessing scheme for subspace methods that resolves their sensitivity to coherent sources. The source resolvability problem of spatial-smoothing-based subspace methods has been extensively investigated using different analysis techniques. In this paper, a unified Hadamard Product technique is provided to recover these results. This is done by answering a long-standing question in linear algebra as to under what conditions the Hadamard Product of two singular positive-semidefinite matrices is positive definite.

Friederike Ziegler - One of the best experts on this subject based on the ideXlab platform.

Zai Yang - One of the best experts on this subject based on the ideXlab platform.

  • Source Resolvability of Spatial-Smoothing-Based Subspace Methods: A Hadamard Product Perspective
    IEEE Transactions on Signal Processing, 2019
    Co-Authors: Zai Yang, Petre Stoica, Jinhui Tang
    Abstract:

    A major drawback of subspace methods for direction-of-arrival estimation is their poor performance in the presence of coherent sources. Spatial smoothing is a common solution that can be used to restore the performance of these methods in such a case at the cost of increased array size requirement. In this paper, a Hadamard Product Perspective of the source resolvability problem of spatial-smoothing-based subspace methods is presented. The array size that ensures resolvability is derived as a function of the source number, the rank of the source covariance matrix, and the source coherency structure. This new result improves upon previous ones and recovers them in special cases. It is obtained by answering a long-standing question first asked explicitly in 1973 as to when the Hadamard Product of two singular positive-semidefinite matrices is strictly positive definite. The problem of source identifiability is discussed as an extension. Numerical results are provided that corroborate our theoretical findings.

  • hadamard Product Perspective on source resolvability of spatial smoothing based subspace methods
    International Conference on Acoustics Speech and Signal Processing, 2019
    Co-Authors: Zai Yang, Petre Stoica
    Abstract:

    Spatial smoothing is a common preprocessing scheme for subspace methods that resolves their sensitivity to coherent sources. The source resolvability problem of spatial-smoothing-based subspace methods has been extensively investigated using different analysis techniques. In this paper, a unified Hadamard Product technique is provided to recover these results. This is done by answering a long-standing question in linear algebra as to under what conditions the Hadamard Product of two singular positive-semidefinite matrices is positive definite.

  • ICASSP - Hadamard Product Perspective on Source Resolvability of Spatial-smoothing-based Subspace Methods
    ICASSP 2019 - 2019 IEEE International Conference on Acoustics Speech and Signal Processing (ICASSP), 2019
    Co-Authors: Zai Yang, Petre Stoica
    Abstract:

    Spatial smoothing is a common preprocessing scheme for subspace methods that resolves their sensitivity to coherent sources. The source resolvability problem of spatial-smoothing-based subspace methods has been extensively investigated using different analysis techniques. In this paper, a unified Hadamard Product technique is provided to recover these results. This is done by answering a long-standing question in linear algebra as to under what conditions the Hadamard Product of two singular positive-semidefinite matrices is positive definite.

Guldborg Søvik - One of the best experts on this subject based on the ideXlab platform.