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

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Since the late 1990s our group has been working with groups in chemistry department at the University of Texas at Austin on a project referred as "Electronic Taste Chip," a MicroElectroMechanical System (MEMS) based miniaturized microfluidic chemical sensor with multianalyte detection capabilities. By integrating optical detection mechanism directly onto the silicon chip a cost effective, compact, and portable sensor can be realized enabling use of these chips out of conventional laboratory environment. Addition to the integration a noble approach of accessing a photodiode with non-contact powerless RFID type readout is presented. By doing so a packaged photodiode can be interrogated without direct electrical contact, enhancing the portability even further for a sensor operated in aqueous medium. First background information regarding the project as well as design and integration criteria is presented followed by demonstration of non-contact RFID-type readout of a photodiode. Detailed discussion on the development of process integration scheme is discussed along with the measurements verifying the performance of the fabricated photodiode. During this investigation normally overlooked design criteria of collection efficiency, the effect of how a target element is to be delivered to a detection mechanism on the overall performance of the sensor, is addressed and discussed.

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published_or_final_version / Mechanical Engineering / Master / Master of Philosophy

The development of new technologies and the advancement of existing technical expertise can allow for dramatic improvements to be realized in analytical instrumentation. The development of an integrating solid-state ion detector, designed to have a high sensitivity as well as maintaining a high-level of stability, is described and evaluated. Several versions of the charge-transimpedance amplifier (CTIA) technology were constructed with different operating features. The CTIA-1 is a 32-pixel array detector designed for mass spectrometry. It has the capability to simultaneously detect multiple ion channels with a detection limit less than 100 ions. The CTIA-2 detector features an independent selectable gain for each detection channel. The CTIA-2 is a 4-channel device designed for ion mobility. Further design features were built into the CTIA-5 such as differential noise reduction capabilities.The CTIA-1 technology was evaluated for use in isotope ratio mass spectrometry on a custom-built Mattauch-Herzog mass spectrometer. An evaluation was conducted in terms of the detector sensitivity, stability, accuracy, precision, resolution, and mass bias. The CTIA-2 was tested on a sector mass spectrometer for its response to low ion currents of both positive and negative ions. The detector stability, its accuracy, and its precision were studied.The technique of ion mobility spectrometry is rapidly growing, as it is the main technology used for the detection of explosives at security checkpoints. The need to improve the sensitivity of existing ion mobility instruments has led to the exploration of using the CTIA detector in ion mobility instruments. Improvements in sensitivity of two to three orders of magnitude have been demonstrated using the described CTIA detectors. Additional applications that use ion mobility instruments for the detection of analytes have been presented, the chemical mapping of a halogen-contaminated sand bed, the detection of pesticides, as well as the detection of TNT in drinking water.Results indicate that the CTIA detector technology is well suited for use in both mass spectrometry and ion mobility. The sensitive and stable multi-array CTIA detectors perform well in isotope ratio mass spectrometry. Ion mobility instruments of all types can benefit from the added sensitivity supplied by this technology.

This thesis describes design, fabrication, and characterizations of high-Tc transition edge sensor (TES) detectors aiming at cryogen-free infrared application. TES is a superconducting thermometer based bolometric detector, whose operating resistance is strongly dependent on temperature, and therefore shows much higher sensitivity than standard non-superconducting bolometers. This thesis starts from the overview of major infrared detectors, then discusses in detail the theoretical background of a TES detector and some important figures of merit in evaluating its performance. Some TES arrays that are currently in use or under development for astronomical, ground or space-based missions are reviewed. The core of this thesis is the design and fabrication process of a TES detector, which is presented as a live report in Chapter 3 and provides useful guide for future detector fabrication. In order to evaluate performance of our devices, a cryogen-free cryostat is used for testing and its operational mechanics is introduced. In the final part, the experimental configurations for different tests are delivered, and the figures of merit mentioned above are measured and used to characterize fabrication results. / xv, 152 leaves : col. ill. ; 29 cm