The Experts below are selected from a list of 291 Experts worldwide ranked by ideXlab platform

K. Kiasaleh - One of the best experts on this subject based on the ideXlab platform.

M. Cole - One of the best experts on this subject based on the ideXlab platform.

Jean-pierre Delmas - One of the best experts on this subject based on the ideXlab platform.

  • Optimizing V antenna arrays using a Bayesian DOA Estimation Criterion
    2013 1st International Conference on Communications Signal Processing and their Applications (ICCSPA), 2013
    Co-Authors: Houcem Gazzah, Jean-pierre Delmas
    Abstract:

    Experimentations have shown V-shaped uniform antenna arrays to be near-optimum for estimating the direction of arrival of a far-field source, whether the source position is fixed or random. We consider, as performance measure, the expected Cramer-Rao bound, normalized (for comparison purposes) to that of the commonly used uniform circular arrays. We study in details the behavior of V arrays in this context. For large-sized V arrays, the performance measure shows a simple expression, enabling analytical solution of the subsequent array-geometry optimization problem. We obtain closed-form expressions of the orientation, shape and performance of optimal V arrays and learn about their ability to benefit from the available prior about the source direction.

  • Optimization of the antenna array geometry based on a Bayesian DOA Estimation Criterion
    2011 IEEE International Conference on Acoustics Speech and Signal Processing (ICASSP), 2011
    Co-Authors: Houcem Gazzah, Jean-pierre Delmas
    Abstract:

    In this paper, we address the problem of the sensor placement for estimating the direction of a narrow-band source, randomly located in the far-field of a planar antenna array. Estimation performance is evaluated by means of the expectation of the conditional Cramer Rao bound (ECRB), which depends on the prior probabilistic distribution of the DOA angles. We study the particular, but practical, case where the azimuth angle is uniformly distributed. Surprisingly, it turns out that the optimal arrays are not isotropic, i.e. they do not have the same accuracy in all possible look directions. In fact, optimal arrays computed here increase performance by about 10% compared to optimal isotropic arrays computed in a previous work.

  • ICASSP - Optimization of the antenna array geometry based on a Bayesian DOA Estimation Criterion
    2011 IEEE International Conference on Acoustics Speech and Signal Processing (ICASSP), 2011
    Co-Authors: Houcem Gazzah, Jean-pierre Delmas
    Abstract:

    In this paper, we address the problem of the sensor placement for estimating the direction of a narrow-band source, randomly located in the far-field of a planar antenna array. Estimation performance is evaluated by means of the expectation of the conditional Cramer Rao bound (ECRB), which depends on the prior probabilistic distribution of the DOA angles. We study the particular, but practical, case where the azimuth angle is uniformly distributed. Surprisingly, it turns out that the optimal arrays are not isotropic, i.e. they do not have the same accuracy in all possible look directions. In fact, optimal arrays computed here increase performance by about 10% compared to optimal isotropic arrays computed in a previous work.

Houcem Gazzah - One of the best experts on this subject based on the ideXlab platform.

  • Optimizing V antenna arrays using a Bayesian DOA Estimation Criterion
    2013 1st International Conference on Communications Signal Processing and their Applications (ICCSPA), 2013
    Co-Authors: Houcem Gazzah, Jean-pierre Delmas
    Abstract:

    Experimentations have shown V-shaped uniform antenna arrays to be near-optimum for estimating the direction of arrival of a far-field source, whether the source position is fixed or random. We consider, as performance measure, the expected Cramer-Rao bound, normalized (for comparison purposes) to that of the commonly used uniform circular arrays. We study in details the behavior of V arrays in this context. For large-sized V arrays, the performance measure shows a simple expression, enabling analytical solution of the subsequent array-geometry optimization problem. We obtain closed-form expressions of the orientation, shape and performance of optimal V arrays and learn about their ability to benefit from the available prior about the source direction.

  • Optimization of the antenna array geometry based on a Bayesian DOA Estimation Criterion
    2011 IEEE International Conference on Acoustics Speech and Signal Processing (ICASSP), 2011
    Co-Authors: Houcem Gazzah, Jean-pierre Delmas
    Abstract:

    In this paper, we address the problem of the sensor placement for estimating the direction of a narrow-band source, randomly located in the far-field of a planar antenna array. Estimation performance is evaluated by means of the expectation of the conditional Cramer Rao bound (ECRB), which depends on the prior probabilistic distribution of the DOA angles. We study the particular, but practical, case where the azimuth angle is uniformly distributed. Surprisingly, it turns out that the optimal arrays are not isotropic, i.e. they do not have the same accuracy in all possible look directions. In fact, optimal arrays computed here increase performance by about 10% compared to optimal isotropic arrays computed in a previous work.

  • ICASSP - Optimization of the antenna array geometry based on a Bayesian DOA Estimation Criterion
    2011 IEEE International Conference on Acoustics Speech and Signal Processing (ICASSP), 2011
    Co-Authors: Houcem Gazzah, Jean-pierre Delmas
    Abstract:

    In this paper, we address the problem of the sensor placement for estimating the direction of a narrow-band source, randomly located in the far-field of a planar antenna array. Estimation performance is evaluated by means of the expectation of the conditional Cramer Rao bound (ECRB), which depends on the prior probabilistic distribution of the DOA angles. We study the particular, but practical, case where the azimuth angle is uniformly distributed. Surprisingly, it turns out that the optimal arrays are not isotropic, i.e. they do not have the same accuracy in all possible look directions. In fact, optimal arrays computed here increase performance by about 10% compared to optimal isotropic arrays computed in a previous work.

John Lafferty - One of the best experts on this subject based on the ideXlab platform.

  • Mismatched Estimation and relative entropy in vector Gaussian channels
    2013 IEEE International Symposium on Information Theory, 2013
    Co-Authors: Minhua Chen, John Lafferty
    Abstract:

    We derive a novel relation between mismatched Estimation and relative entropy (KL divergence) in vector Gaussian channels under the mean squared Estimation Criterion. This relation includes as special cases several previous results connecting Estimation theory and information theory. A direct proof is provided, together with a verification using Gaussian inputs. An interesting relationship between the KL divergence and Fisher divergence is derived as a direct consequence of our work. The relations established here are potentially useful for inference in graphical models and the design of information systems.

  • ISIT - Mismatched Estimation and relative entropy in vector Gaussian channels
    2013 IEEE International Symposium on Information Theory, 2013
    Co-Authors: Minhua Chen, John Lafferty
    Abstract:

    We derive a novel relation between mismatched Estimation and relative entropy (KL divergence) in vector Gaussian channels under the mean squared Estimation Criterion. This relation includes as special cases several previous results connecting Estimation theory and information theory. A direct proof is provided, together with a verification using Gaussian inputs. An interesting relationship between the KL divergence and Fisher divergence is derived as a direct consequence of our work. The relations established here are potentially useful for inference in graphical models and the design of information systems.