Theses and Dissertations at Montana State University (MSU)
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Item Compressive laser ranging with embedded systems(Montana State University - Bozeman, College of Engineering, 2015) Pandit, Pushkar Pradeep; Chairperson, Graduate Committee: Joseph A. ShawCompressive sensing is a signal processing technique that has recently come to the forefront due to its ability to work around the well-known Shannon-Nyquist-Whittaker sampling theorem by exploiting certain properties in real world signals. This thesis will explore the theory behind compressive sensing and demonstrate its implementation toward laser ranging, cumulatively known as compressive laser ranging. Experiments were set up using electronic and photonic devices combining the theory behind compressive sensing and laser ranging and successful results measuring distances to multiple targets were obtained. The experimental setup was also implemented on an FPGA in an effort to create a compact laser ranging system.Item Design and application of a microwave moisture meter(Montana State University - Bozeman, College of Engineering, 1974) Kowalski, Joseph LacyItem An intrusive slotted cylinder antenna array for subsurface moisture profiling(Montana State University - Bozeman, College of Engineering, 1979) Herrick, David LeoItem A computer controlled time domain reflectometry multiplexer(Montana State University - Bozeman, College of Engineering, 1995) Carlson, Rodney DavidItem Comparison of the Kirchhoff and Rayleigh-Rice diffractions for sinusoidal surfaces(Montana State University - Bozeman, College of Engineering, 1990) Schiff, Tod Forrest; Chairperson, Graduate Committee: Frederick M. Cady; John C. Stover (co-chair)Item Ultra wideband radar antenna design for snow measurement applications(Montana State University - Bozeman, College of Engineering, 2009) Mosy, John Samy; Chairperson, Graduate Committee: Richard WolffCreating a high-precision, compact and low cost snow structure and depth sensor has always been the dream of many industries, and yet hard to achieve all together. Snow depth sensors are used in avalanche search and rescue and widely in recreational snow industry, as well as in environmental monitoring systems for snow water equivalence measurements. The use of radar for snow depth measurement is not new and many techniques -such as Frequency Modulated Continuous Wave (FMCW) - have been used but they prove to be costly, bulky, and have relatively low precision. Today with the availability of chip-scale Ultra Wide-Band (UWB) technology, it is possible to create Snow Depth Sensor (SDS) and Snow Water Equivalent (SWE) measuring systems in low cost, small size and possibly mobile devices, with very high precision. One problem that remains at the RF (Radio Frequency) end of the UWB technique in measuring snow parameters is the antenna used in transmitting and receiving UWB pulses. UWB pulses are characterized by an instantaneous fractional energy bandwidth greater than about 0.20-0.25. The FCC has allocated spectrum for UWB use in the 3.1-10.6 GHz band and available chipsets generate pulses in the lower 3-6 GHz band. For creating applications that use UWB in measuring snow parameters such as SWE and snow depth, a UWB antenna is required. A successful UWB radar antenna needs to have high gain, linear phase, low dispersion and low Voltage Standing Wave Ratio (VSWR), and high directivity throughout the entire band. The antennas are to have physically compact design with high gain, linear phase, low VSWR and high directivity for UWB radar applications in the snow measurements industry. This thesis presents several antenna designs for the 3.1-10.6 GHz UWB band and the 3-6 GHz UWB lower band that have the potential to meet these requirements, and show, through laboratory measurements, modeling and simulations, that the required attributes can be achieved.Item Remote sensing applications of uncooled long-wave infrared thermal imagers(Montana State University - Bozeman, College of Engineering, 2012) Johnson, Jennifer Erin; Chairperson, Graduate Committee: Joseph A. ShawThe commercial development of microbolometer uncooled long-wave thermal infrared imagers in conjuncture with advanced radiometric calibration methods developed at Montana State University has led to new uses of thermal imagery in remote sensing applications. As a result of being uncooled, microbolometer imagers are notably lighter and cheaper than typical cooled imagers, making them ideal for remote sensing. Two novel uses are discussed in the work presented here. The first is the imaging of beehives in order to remotely determine the hive vitality. Bees thermally regulate their hives to a narrow range of temperatures that creates a thermal signature seen in thermal infrared images. For each of the hives imaged, frame counts (or the number of full frames of bees in each hive) were found by manual inspection. Linear regressions of the normalized frame counts of the hives were performed versus the measured hive thermal radiance values. The resulting plots showed a strong relationship between the normalized frame count and the mean radiance of each hive, particularly in images taken just prior to dawn. The second novel use was imaging vegetation exposed to large ground concentrations of CO ₂ over a four-week period in summer for use in leak detection. A CO ₂ leak was simulated in a test field run by the Zero Emissions Research and Technology Center. Thermal infrared images were acquired along with visible and near-infrared reflectance images of the exposed vegetation and healthy control vegetation. Thermal radiance statistics were measured and a regression was performed versus the day of the experiment. The infrared data were found to have a strong R ² value and clearly show the effect of the CO ₂ on the vegetation. An additional regression was run on the infrared data combined with the reflectance data, and this was found to not add any unique information to the vegetation reflectance data. Both methods were found to independently indicate the potential of a CO ₂ leak before it was detected visually.Item Thermal infrared imaging of the atmosphere : the infrared cloud imager(Montana State University - Bozeman, College of Engineering, 2004) Thurairajah, Brentha; Chairperson, Graduate Committee: Joseph A. ShawClouds play an important role in regulating the radiation budget of the atmosphere and are responsible for altering or maintaining the global climate. Understanding the interaction between clouds and radiation is necessary for accurate models that predict future climate and weather changes. The present cloud instruments are either zenithviewing, single-pixel instruments that calculate cloud amount using Taylor's hypothesis (spatial statistics are equal to temporal statistics), which do not work under certain atmospheric conditions, or are imagers that operate in the visible spectrum, thereby operating only in the daytime. Other imaging instruments use completely different techniques for daytime and nighttime detection of clouds and have problems detecting clouds at sunrise and sunset. The Infrared Cloud Imager (ICI), a ground based, thermal infrared imager was developed with funding from the Communications Research Laboratory (CRL), Japan, to provide continuous 24-hour cloud measurement without difference in daytime or nighttime sensitivity. The ICI is a spatially resolving instrument that measures the downwelling atmospheric radiance in the 8-14 aem region of the electromagnetic spectrum. The data collected are used to compute spatial and temporal cloud statistics. Although the ICI was initially developed to measure Arctic clouds, it has been successfully deployed in both Barrow, Alaska in the Spring of 2002 and in Lamont, Oklahoma (mid-latitude plains) in Spring 2003. I have developed algorithms for processing the ICI data based on Microwave Radiometer (MWR) water vapor data, for identifying and classifying clouds, and have demonstrated that ICI is capable of determining cloud statistics. From the radiative transfer analysis of the ICI data, weekly and monthly cloud statistics show a general trend of mostly clear and/or mostly cloudy skies with very small transition periods. Sky cover histograms from Oklahoma show predominantly thick clouds in March and thin clouds in April with a significant amount of variability in sky condition. The comparison of cloud statistics obtained from the entire ICI image and from a single pixel in the ICI image illustrates that zenith-viewing instruments generally tend to underestimate cloudiness. The correlation between ICI percent cloudiness (using different thresholds for Oklahoma data) with the Micro Pulse Lidar (MPL) cloudiness has also been analyzed.