The Experts below are selected from a list of 16365 Experts worldwide ranked by ideXlab platform

N J S Stacy - One of the best experts on this subject based on the ideXlab platform.

  • a change Detection Statistic for repeat pass interferometric sar
    International Conference on Acoustics Speech and Signal Processing, 2003
    Co-Authors: M Preiss, D A Gray, N J S Stacy
    Abstract:

    In repeat pass synthetic aperture radar interferometry (In-SAR) the scene coherency can be used to detect subtle scene changes that may not be evident in the image magnitude data alone. The sensitivity of the coherency estimate for identifying man-made disturbances is dependent on the size and nature of these disturbances compared to the other sources of disturbance such as wind, system noise and processing aberrations that affect the scene images. In this paper the Detection problem is formulated in a hypothesis testing framework and a new change Statistic is proposed. Analytic expressions for the probability of Detection and false alarm are derived which show a significant improvement over the commonly used coherence based change Detection. Application of the new change Statistic to experimental data obtained using the DSTO Ingara SAR demonstrates the improved Detection performance.

  • ICASSP (5) - A change Detection Statistic for repeat pass interferometric SAR
    2003 IEEE International Conference on Acoustics Speech and Signal Processing 2003. Proceedings. (ICASSP '03)., 1
    Co-Authors: M Preiss, D A Gray, N J S Stacy
    Abstract:

    In repeat pass synthetic aperture radar interferometry (In-SAR) the scene coherency can be used to detect subtle scene changes that may not be evident in the image magnitude data alone. The sensitivity of the coherency estimate for identifying man-made disturbances is dependent on the size and nature of these disturbances compared to the other sources of disturbance such as wind, system noise and processing aberrations that affect the scene images. In this paper the Detection problem is formulated in a hypothesis testing framework and a new change Statistic is proposed. Analytic expressions for the probability of Detection and false alarm are derived which show a significant improvement over the commonly used coherence based change Detection. Application of the new change Statistic to experimental data obtained using the DSTO Ingara SAR demonstrates the improved Detection performance.

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

  • a change Detection Statistic for repeat pass interferometric sar
    International Conference on Acoustics Speech and Signal Processing, 2003
    Co-Authors: M Preiss, D A Gray, N J S Stacy
    Abstract:

    In repeat pass synthetic aperture radar interferometry (In-SAR) the scene coherency can be used to detect subtle scene changes that may not be evident in the image magnitude data alone. The sensitivity of the coherency estimate for identifying man-made disturbances is dependent on the size and nature of these disturbances compared to the other sources of disturbance such as wind, system noise and processing aberrations that affect the scene images. In this paper the Detection problem is formulated in a hypothesis testing framework and a new change Statistic is proposed. Analytic expressions for the probability of Detection and false alarm are derived which show a significant improvement over the commonly used coherence based change Detection. Application of the new change Statistic to experimental data obtained using the DSTO Ingara SAR demonstrates the improved Detection performance.

  • ICASSP (5) - A change Detection Statistic for repeat pass interferometric SAR
    2003 IEEE International Conference on Acoustics Speech and Signal Processing 2003. Proceedings. (ICASSP '03)., 1
    Co-Authors: M Preiss, D A Gray, N J S Stacy
    Abstract:

    In repeat pass synthetic aperture radar interferometry (In-SAR) the scene coherency can be used to detect subtle scene changes that may not be evident in the image magnitude data alone. The sensitivity of the coherency estimate for identifying man-made disturbances is dependent on the size and nature of these disturbances compared to the other sources of disturbance such as wind, system noise and processing aberrations that affect the scene images. In this paper the Detection problem is formulated in a hypothesis testing framework and a new change Statistic is proposed. Analytic expressions for the probability of Detection and false alarm are derived which show a significant improvement over the commonly used coherence based change Detection. Application of the new change Statistic to experimental data obtained using the DSTO Ingara SAR demonstrates the improved Detection performance.

Christopher J Burke - One of the best experts on this subject based on the ideXlab platform.

  • χ 2 discriminators for transiting planet Detection in kepler data
    Astrophysical Journal Supplement Series, 2013
    Co-Authors: Shawn Seader, Peter Tenenbaum, Jon M Jenkins, Christopher J Burke
    Abstract:

    The Kepler spacecraft observes a host of target stars to detect transiting planets. Requiring a 7.1{sigma} Detection in three years of data yields over 100,000 Detections, many of which are false alarms. After a second cut is made on a robust Detection Statistic, some 50,000 or more targets still remain. These false alarms waste resources as they propagate through the remainder of the software pipeline and so a method to discriminate against them is crucial in maintaining the desired sensitivity to true events. This paper describes a {chi}{sup 2} test which represents a novel application of an existing formalism developed for false alarm mitigation in searches for gravitational waves. Using this technique, the false alarm rate can be lowered to {approx}5%.

  • chi sup 2 discriminators for transiting planet Detection in kepler data
    Astrophysical Journal Supplement Series, 2013
    Co-Authors: Shawn Seader, Peter Tenenbaum, Jon M Jenkins, Christopher J Burke
    Abstract:

    The Kepler spacecraft observes a host of target stars to detect transiting planets. Requiring a 7.1{sigma} Detection in three years of data yields over 100,000 Detections, many of which are false alarms. After a second cut is made on a robust Detection Statistic, some 50,000 or more targets still remain. These false alarms waste resources as they propagate through the remainder of the software pipeline and so a method to discriminate against them is crucial in maintaining the desired sensitivity to true events. This paper describes a {chi}{sup 2} test which represents a novel application of an existing formalism developed for false alarm mitigation in searches for gravitational waves. Using this technique, the false alarm rate can be lowered to {approx}5%.

D A Gray - One of the best experts on this subject based on the ideXlab platform.

  • a change Detection Statistic for repeat pass interferometric sar
    International Conference on Acoustics Speech and Signal Processing, 2003
    Co-Authors: M Preiss, D A Gray, N J S Stacy
    Abstract:

    In repeat pass synthetic aperture radar interferometry (In-SAR) the scene coherency can be used to detect subtle scene changes that may not be evident in the image magnitude data alone. The sensitivity of the coherency estimate for identifying man-made disturbances is dependent on the size and nature of these disturbances compared to the other sources of disturbance such as wind, system noise and processing aberrations that affect the scene images. In this paper the Detection problem is formulated in a hypothesis testing framework and a new change Statistic is proposed. Analytic expressions for the probability of Detection and false alarm are derived which show a significant improvement over the commonly used coherence based change Detection. Application of the new change Statistic to experimental data obtained using the DSTO Ingara SAR demonstrates the improved Detection performance.

  • ICASSP (5) - A change Detection Statistic for repeat pass interferometric SAR
    2003 IEEE International Conference on Acoustics Speech and Signal Processing 2003. Proceedings. (ICASSP '03)., 1
    Co-Authors: M Preiss, D A Gray, N J S Stacy
    Abstract:

    In repeat pass synthetic aperture radar interferometry (In-SAR) the scene coherency can be used to detect subtle scene changes that may not be evident in the image magnitude data alone. The sensitivity of the coherency estimate for identifying man-made disturbances is dependent on the size and nature of these disturbances compared to the other sources of disturbance such as wind, system noise and processing aberrations that affect the scene images. In this paper the Detection problem is formulated in a hypothesis testing framework and a new change Statistic is proposed. Analytic expressions for the probability of Detection and false alarm are derived which show a significant improvement over the commonly used coherence based change Detection. Application of the new change Statistic to experimental data obtained using the DSTO Ingara SAR demonstrates the improved Detection performance.

Steven L Grant - One of the best experts on this subject based on the ideXlab platform.

  • normalized double talk Detection based on microphone and aec error cross correlation
    International Conference on Multimedia and Expo, 2007
    Co-Authors: M A Lqbal, Jack W Stokes, Steven L Grant
    Abstract:

    In this paper, we present two different double-talk Detection schemes for Acoustic Echo Cancellation (AEC). First, we present a novel normalized Detection Statistic based on the cross-correlation coefficient between the microphone signal and the cancellation error. The decision Statistic is designed in such a way that it meets the needs of an optimal double-talk detector. We also show that the proposed Detection Statistic converges to the recently proposed normalized cross-correlation based double-talk detector, the best known cross-correlation based detector. Next, we present a new hybrid double-talk Detection scheme based on a cross-correlation coefficient and two signal detectors. The hybrid algorithm not only detects double-talk but also detects and tracks any echo-path variations efficiently. We compare our results with other cross-correlation based double-talk detectors to show their effectiveness.

  • ICME - Normalized Double-Talk Detection Based on Microphone and AEC Error Cross-Correlation
    2007 IEEE International Conference on Multimedia and Expo, 2007
    Co-Authors: M A Lqbal, Jack W Stokes, Steven L Grant
    Abstract:

    In this paper, we present two different double-talk Detection schemes for Acoustic Echo Cancellation (AEC). First, we present a novel normalized Detection Statistic based on the cross-correlation coefficient between the microphone signal and the cancellation error. The decision Statistic is designed in such a way that it meets the needs of an optimal double-talk detector. We also show that the proposed Detection Statistic converges to the recently proposed normalized cross-correlation based double-talk detector, the best known cross-correlation based detector. Next, we present a new hybrid double-talk Detection scheme based on a cross-correlation coefficient and two signal detectors. The hybrid algorithm not only detects double-talk but also detects and tracks any echo-path variations efficiently. We compare our results with other cross-correlation based double-talk detectors to show their effectiveness.