Thesis (M.S.)--Montana State University--Bozeman, 2006. / Typescript. Chairperson, Graduate Committee: James P. Becker. Includes bibliographical references (leaves 120-121).

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

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

Thesis (M.S.)--University of Wisconsin--Madison, 1982. / Typescript. eContent provider-neutral record in process. Description based on print version record. Includes bibliographical references (leaves 50-51).

Thesis (M.S.)--Baylor University, 2006. / Includes bibliographical references (p. 65-67).

The Cold-Electron Bolometer (CEB) is a sensitive detector of millimeter-wave radiation, in which tunnel junctions are used as temperature sensors of a nanoscale normal metal strip absorber. The absorber is fed by an antenna via two Superconductor-Insulator-Normal metal (SIN) tunnel junctions, fabricated at both ends of the absorber. Incoming photons excite electrons, heating the whole electron system. The incoming RF power is determined by measuring the tunneling current through the SIN junctions. Since electrons at highest energy levels escape the absorber through the tunnel junctions, it causes cooling of the absorber. This electron cooling provides electro-thermal feedback that makes the saturation power of a CEB well above that of other types of millimeter-wave receivers. The key features of CEB detectors are high sensitivity, large dynamic range, fast response, easy integration in arrays on planar substrates, and simple readout. The high dynamic range allows the detector to operate under relatively high background levels. In this thesis, we present the development and successful operation of CEB, focusing on the fabrication technology and different implementations of the CEB for efficient detection of electromagnetic signals. We present the CEB detector integrated across a unilateral finline deposited on a planar substrate. We have measured the finline-integrated CEB performance at 280-315 mK using a calibrated black-body source mounted inside the cryostat. The results have demonstrated strong response to the incoming RF power and reasonable sensitivity. We also present CEB devices fabricated with advanced technologies and integrated in log-periodic, double-dipole and cross-slot antennas. The measured CEB performance satisfied the requirements of the balloon-borne experiment BOOMERANG and could be considered for future balloon-borne and ground-based instruments. In this thesis we also investigated a planar phase switch integrated in a back-to-back finline for modulating the polarization of weak electromagnetic signals. We examine the switching characteristics and demonstrate that the switching speed of the device is well above the speed required for phase modulation in astronomical instruments. We also investigated the combination of a detector and a superconducting phase switch for modulating the polarization of electromagnetic radiation.