J. Ward

Massachusetts Institute of Technology, Cambridge, Massachusetts, United States

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Publications (2)0 Total impact

  • Source
    L.M. Zurk, N. Lee, J. Ward
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    ABSTRACT: In this paper we demonstrate passive detection and localization in a noisy shallow water environment using matched field processing (MFP) with data obtained during the Santa Barbara Channel Experiment (SBCX). The use of an Adaptive MFP algorithm provides the ability to detect a submerged source in the presence of strong surface interference and also reduces ambiguity surface sidelobe clutter. We also consider the effects of source motion during the observation interval. Target motion can degrade signal gains by introducing, smearing across MFP range cells. For large arrays, such as those deployed during SBCX, motion can also introduce errors due to differential doppler across the array. Since long observation times are desirable for increased noise gain and to provide sample support for the adaptive algorithms, motion compensation is required. An approach is described that uses a velocity hypothesis to focus the snapshots prior to covariance estimation. Results show that with compensation, localization accuracy is improved and the full resolution of the array can be realized
    OCEANS '99 MTS/IEEE. Riding the Crest into the 21st Century; 02/1999
  • Source
    N. Lee, L.M. Zurk, J. Ward
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    ABSTRACT: This paper evaluates the performance of several reduced-rank, adaptive matched field processing (AMFP) algorithms for passive sonar detection in a shallow-water environment. Effective rank reduction improves the stability of adaptive beamformer weight calculation when the number of available snapshots is limited. Here, rank-reduction techniques with various criteria for subspace selection are evaluated within a common framework and compared to the full-rank conventional and minimum-variance (MVDR) beamformers. Results from real data demonstrate that rank reduction, properly applied can improve AMFP detection performance in practical system implementations.
    Signals, Systems, and Computers, 1999. Conference Record of the Thirty-Third Asilomar Conference on; 02/1999