Approved for public release; distribution is unlimited / The use of the HF radar to measure and map surface currents has proliferated along the coastlines of many countries for purposes of Search and Rescue, Oil Spill Management, Oceanographic and Fishery Science studies. In the US Navy, these surface current maps are being evaluated for operational use in real-time data assimilating coastal circulation models, and direct monitoring tools in environmentally sensitive operating areas. The SeaSonde HF radar, a DF system, was considered in this study. It uses the MUSIC algorithm to recover bearings from the Doppler backscatter spectrum of the sea surface. By varying the radial and antenna patterns, the simulated backscatter spectra were passed through the SeaSonde software suite for radial pattern recovery. This unprecedented approach directly evaluated SeaSondeâ s MUSIC, and the associated uncertainties were examined against the simulated inputs of (1) fixed amplitude and phase deviations from the ideal antenna pattern, (2) measured antenna patterns and (3) decreasing SNR. It was found that using the measured antenna pattern to recover radials yielded least uncertainty, but a definitive prediction of MUSICâ s radial-recovery capability in relation to the patternâ s complex amplitude and phase structure remained illusive. The results highlighted the need to calibrate the militaryâ s DF-systems for accurate azimuth recovery. / Outstanding Thesis

Thesis (M.S.)--Naval Postgraduate School, 2002. / Thesis advisor(s): Kenneth L. Davidson, John McCarthy. Includes bibliographical references (p. 61-62). Also available online.

Thesis (Ph. D.)--University of Oklahoma, 1998. / Includes bibliographical references (leaves 247-257).

Through-wall human monitoring within a highly cluttered environment is a problem of current interest. Example applications include law enforcement, disaster search-and-rescue, and urban military operations. The purpose is to clearly monitor humans through building walls using a radar system. Doppler-based sensors offer an inexpensive way to detect moving targets in the presence of stationary clutters. It also provides information regarding motions of the human by micro-Doppler returns. In this dissertation, the applications of data-driven model (DDM) are investigated for locating human subjects and classifying their activity using Doppler sensors. DDM is a mathematical model trained by a set of data that describe the input-output relationship. It is suitable for real-time applications. As DDM, an artificial neural network (ANN) and a support vector machine (SVM) are considered. A collection of Doppler sensors is studied to localize humans in two ways: the use of spatially distributed Doppler sensors and the use of a single-sensor array. Furthermore, the feasibility of classifying human activities is studied with the obtained Doppler information. First, an ANN is proposed to track humans using the Doppler information measured by a set of spatially distributed sensors. The ANN estimates the target position and velocity given the observed Doppler data from multiple sensors. A point-scatterer model is used for the training data generation. For the verification of the proposed method, a toy car and a human moving in a circular track are measured in line-of-sight and through-wall environments. Second, an array-processing algorithm is proposed to estimate the number of targets and their Direction-of-Arrival (DOA) based on ANN when the available number of sensor elements is small. Using software beamforming, a number of overlapping beams are simultaneously formed. The received signal strengths from all the beams produce a unique signature in accordance with the target locations, as well as the number of targets. The identification of the number of targets and their locations is carried out sequentially via ANNs. For the verification of the algorithm, both line-of-sight and through-wall measurements are performed using loudspeakers driven by audio tones and moving humans. Third, an SVM is proposed to classify activities of a human subject using the measured Doppler information. MicroDopplers from moving limbs of human subjects contain significant information regarding their activities. Seven different human activities of twelve human subjects are measured in the laboratory using a Doppler radar. Six microDoppler features are extracted from the resulting spectrograms. A decision-tree based SVM is used for the classification of seven activities based on the features. Diverse situations such as combination of different activities, oblique angle case, and throughwall case are also discussed. / text

Copy of author's previously published article inserted. / Bibliography: p. 221-228. / xii, 228 p. : ill. ; 30 cm. / Title page, contents and abstract only. The complete thesis in print form is available from the University Library. / Discusses the work done by the author to upgrade the Buckland Park VHF stratosphere-troposphere radar, verify the data from the new system, plan and run new experiments, and analyse the resultant data in order to study the scattering and aspect sensitivity of the troposphere. / Thesis (Ph.D.)--University of Adelaide, Dept. of Physics and Mathematical Physics, 1998

Zugl.: München, Techn. Univ., Diss., 2006

Thesis (M.S.)--Ohio University, November, 1980. / Title from PDF t.p.

Thesis (Ph. D.)--University of Wyoming, 2006. / Title from PDF title page (viewed on Jan. 2, 2008). Includes bibliographical references.

Thesis (Ph.D.)--University of Adelaide, School of Chemistry and Physics, 2003? / "July 2003." Includes bibliographical references (leaves 459-484). Also available in a print form.

Thesis (Ph. D.)--University of Texas at Austin, 2008. / Vita. Includes bibliographical references.