The major problems associated with implementing synthetic apertures in sonar may be overcome by applying the technique to sub-bottom imaging. The use of a low frequency aids both penetration of the sediment and the attainment of long coherent apertures. The implementation of synthetic apertures realises a narrow fan beam. By directing this beam out sideways, a more rapid survey rate is possible than that achieved by the normal echo-sounding mode used in sub-bottom profiling. The synthetic aperture technique appears to offer significant advantages over that of parametric arrays, for high resolution sub-bottom imaging. Synthetic apertures have been implemented in a laboratory tank, under controlled conditions at a fresh water reservoir, and under realistic operational conditions at sea. Encouraging results have been obtained.

Thesis (M.E.)--University of Canterbury, 2006. / Typescript (photocopy). "December 2006." Includes bibliographical references (p. 99-103). Also available via the World Wide Web.

Thesis (Ph. D.)--University of Canterbury, 2007. / Typescript (photocopy). "January 2007." Includes bibliographical references (p. [209]-223). Also available via the World Wide Web.

Thesis (Ph. D.)--University of Canterbury, 2006. / Typescript (photocopy). "June 2006." Includes bibliographical references (p. [169]-182) and index. Also available via the World Wide Web.

Synthetic Aperture Sonar (SAS) provides the best opportunity for side-looking sonar mounted on underwater platforms to achieve high-resolution images. However, SAS processing requires strict constraints on resolvable platform motion. The most common approach to estimate this motion is to use the Redundant Phase Center (RPC) technique. Here the ping interval is set, such that a portion of the sonar array overlaps as the sensor moves forward. The time delay between the pings received on these overlapping elements is estimated using cross-correlation. These time delays are then used to infer the pingto-ping vehicle motion. Given the stochastic nature of the operational environment, some level of decorrelation between these two signals is likely. In this research, two iterative signal decomposition methods well suited for nonlinear and non-stationary signals, are investigated for their potential to improve the Time Delay Estimation (TDE). The first of this type, the Empirical Mode Decomposition (EMD) was introduced by Huang in the seminal paper, The empirical mode decomposition and the Hilbert spectrum for nonlinear and non-stationary time series analysis and is the foundation for the algorithms used in this research. This method decomposes a signal into a finite sequence of simple components termed Intrinsic Mode Functions (IMFs). The Iterative Filter (IF) approach, developed by Lin, Wang and Zhou, builds on the EMD framework. The sonar signals considered in this research are complex baseband signals. Both the IF and EMD algorithms were designed to decompose real signals. However, the IF variant, the Multivariate Fast Iterative Filtering (MFIF) Algorithm, developed by Cicone, and the EMD variant, the Fast and Adaptive Multivariate Empirical Mode Decomposition (FAMVEMD) algorithm, developed by Thirumalaisamy and Ansell, preserve both the magnitude and phase in the decomposition and hence were chosen for this analysis. / Includes bibliography. / Dissertation (Ph.D.)--Florida Atlantic University, 2021. / FAU Electronic Theses and Dissertations Collection

Thesis (Ph. D.)--University of Canterbury, 2006. / Typescript (photocopy). "August 2006." Includes bibliographical references (p. [167]-179) and index. Also available via the World Wide Web.

No description available.

Thesis (M.E.)--University of Canterbury, 2007. / Typescript (photocopy). "February 2007." Includes bibliographical references (p. [85]-88). Also available via the World Wide Web.

No description available.

This thesis covers the individual work of Michael Chin as part of the sponsored research project funded by the U.S. State Department in support of a computational design of a "Mobile Pit Verification System" (MPVS), a mobile “drive by” passive radiation detection system to be applied in special nuclear materials (SNM) storage facilities for validation and compliance purposes. The MPVS system is intended to enable a comprehensive, rapid verification and validation of stored nuclear weapon core physics packages containing SNM, or so-called “weapon pits,” in weapon materials and stockpile storage facilities. The MPVS platform is designed to move at a constant speed and accumulate a signal for each stored weapon pit container. The gamma detector was selected to be a 4 × 4 × 8 cubic inch CsI detector while the neutron detector array designed for the “Transport Simulation and Validation of a Synthetic Aperture SNM Detection System (“T-SADS”) project was used in conjunction with this work; T-SADS was a 3 year project funded by DOE-NNSA which was completed on May 2013. The computational design effort for this project was completed in April 2013, and leveraged novel computational radiation transport methods, algorithms, and SNM identification methods, including a synthetic aperture collection approach, and a new gamma ratio methodology for distinguishing between naturally occurring radiation materials and weapon class SNM materials. Both forward and adjoint transport methods were utilized to characterize the adjoint reaction rate as a function of inter-source spacing, collimation thickness, linear and angular field of view, source age, source type, source geometry, and mobile platform speed. The integrated count was then compared with background radiation and the associated probabilities of detection and false alarm were then computed. Publications resulting from this research were published in PHYSOR 2012, presented at the 53rd annual Proceedings of the INMM, and at the Mathematics & Computation 2013 Conference.