The autocorrelation function is a commonly used tool in statistical time series analysis. Under the assumption of Gaussianity, the sample autocorrelation function is the standard method used to estimate this function given a finite number of observations. Non-Gaussian, impulsive observation noise following probability density functions with thick tails, which often occurs in practice, can bias this estimator, rendering classical time series analysis methods ineffective. This work examines the robustness of two estimators of correlation based on memoryless nonlinear functions of observations, the Phase-Phase Correlator (PPC) and the Median- of-Ratios Estimator (MRE), which are applicable to complex-valued Gaussian random pro- cesses. These estimators are very fast and easy to implement in current processors. We show that these estimators are robust from a bias perspective when complex-valued Gaussian pro- cesses are contaminated with impulsive noise at the expense of statistical efficiency at the assumed Gaussian distribution. Additionally, iterative versions of these estimators named the IMRE and IPPC are developed, realizing an improved bias performance over their non- iterative counterparts and the well-known robust Schweppe-type Generalized M-estimator utilizing a Huber cost function (SHGM). An impulsive noise suppression technique is developed using basis pursuit and a priori atom weighting derived from the newly developed iterative estimators. This new technique is proposed as an alternative to the robust filter cleaner, a Kalman filter-like approach that relies on linear prediction residuals to identity and replace corrupted observations. It does not have the same initialization issues as the robust filter cleaner. Robust spectral estimation methods are developed using these new estimators and impulsive noise suppression techniques. Results are obtained for synthetic complex-valued Guassian processes and real-world digital television signals collected using a software defined radio. / Ph. D.

This thesis introduces a novel spectral response (SR) measurement technique using polychromatic filters (filters with very broad spectral transmittances) to determine SR of large area PV devices. Conventionally, SR of a photovoltaic (PV) device is determined by illuminating the device under test (DUT) with a series of monochromatic beams at different wavelengths as described in the international standard IEC 60904-8, or beams of limited spectral content using narrow band pass filters or monochromator. One significant problem associated with the application of the narrow band pass filters for a large-area SR measurement is that low light intensity produced on the measurement plane particularly in certain wavelength ranges: the ultraviolet and infrared. This can produce weak signal responses from a tested PV device. In addition, the imperfection of the filter s mounting position can shift the peak wavelength of the filter s transmittance at angle of incidence greater than 10°. This can cause stray light on the measurement plane. The proposed SR measurement method is called the 'polychromatic SR fitting method' or, in short, it is known as the 'polychromatic method'. The advantage of this method is that higher beam intensity can be produced on the measurement plane as a result of large spectral transmittance of the polychromatic filters. This can improve the signal strength of a tested PV device. This new SR measurement method works by comparing the variations in the currents which are measured at different spectra to the currents which are calculated at the same spectral conditions using the SR model. Validations of this method for a large- and small-area SR determinations show that it is potentially feasible as a new technique for determining SR of a PV device with deviations within ±2% across the wavelength bands.

Many techniques have been developed to analyze time series. Spectral analysis and cycle regression analysis represent two such techniques. This study combines these two powerful tools to produce two new algorithms; the spectral algorithm and the one-pass algorithm. This research encompasses four objectives. The first objective is to link spectral analysis with cycle regression analysis to determine an initial estimate of the sinusoidal period. The second objective is to determine the best spectral window and truncation point combination to use with cycle regression for the initial estimate of the sinusoidal period. The third is to determine whether the new spectral algorithm performs better than the old T-value algorithm in estimating sinusoidal parameters. The fourth objective is to determine whether the one-pass algorithm can be used to estimate all significant harmonics simultaneously.

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Master of Science / Department of Horticulture, Forestry, and Recreation Resources / Dale J. Bremer / Radiometric methods may provide more objective and quantitative assessments of turf quality and density than visual ratings and may be useful in measuring green leaf area index (LAI), aboveground biomass, and chlorophyll concentration. This three-year study was conducted near Manhattan, KS to examine: 1) relationships between canopy reflectance and visual quality and density ratings in four cool-season grasses tall fescue (Festuca arundinacea Schreb.), Kentucky bluegrass (Poa pratensis L.) and two hybrid bluegrasses (HBG); 2) effects of species, mowing height, and irrigation deficit on relationships between visual quality and reflectance; 3) comparisons of visual quality with reflectance and digital images of individual plots; and 4) relationships of LAI, aboveground biomass, and chlorophyll concentration with canopy reflectance in the same four grasses and in perennial ryegrass (Lolium perenne), zoysiagrass (Zoysia japonica Stued.), and bermudagrass [Cynodon dactylon (L.) Pers.]. Reflectance was strongly correlated with visual ratings in the normalized difference vegetation index (NDVI, [935-661]/[935+661] nm, r = 0.88), the near infrared to red (NIR/R [935/661] nm, r = 0.83), Stress1 (706/760 nm, r= 0.84), and Stress2 (706/813 nm, r= 0.70) ratios and at wavelengths 613 (r= 0.74) and 661 nm (r = 0.80), but correlations varied among years at each wavelength and vegetation index. For density, highest correlations were in NDVI (r=0.86), R661 (r=-0.84), and Stress2 (r=-0.82). Regressions between reflectance and quality and density ratings indicated cultivar- and mowing height-specific models. Irrigation-deficit strongly affected reflectance in KBG and both HBG but not in TF, indicating greater sensitivity to drought of bluegrasses than TF. Digital images indicated strong correlations between percentage green cover and visual quality (r=0.89). However, wide ranges in visual quality were observed in plots with similar green cover or NDVI for reasons that are not apparent. Correlations of LAI, aboveground biomass, and chlorophyll concentration with reflectance were strong in some species at different wavelengths and ratios. Results indicated both potential and limitations in using spectral reflectance to estimate turfgrass canopy characteristics.

International Telemetering Conference Proceedings / October 20-23, 2003 / Riviera Hotel and Convention Center, Las Vegas, Nevada / Calculating the power spectral density (PSD) at the transducer or data acquisition system offers advantages in a network-based telemetry system. The PSD is provided in real time to the users. The conversion to PSD can either be lossless (allowing a complete reconstruction of the transducer signal) or lossy (providing data compression). Post-processing can convert the PSD back to time histories if desired. A complete reconstruction of the signal is possible, including knowledge of the signal level between the sample periods. Properly implemented, this method of data collection provides a sharp anti-aliasing filter with minimal added cost. Currently no standards exist for generating PSDs on the vehicle. New standards could help telemetry system designers understand the benefits and limitations calculating the power spectral density in a network-based telemetry system.

International Telemetering Conference Proceedings / October 30-November 02, 1995 / Riviera Hotel, Las Vegas, Nevada / This paper will present and compare several definitions of telemetry radio frequency (RF) signal bandwidth. Measured spectra for different signals will be presented. The bandwidths of these signals will then be determined and measurement methods will be discussed. This discussion will include the effects of spectrum analyzer resolution bandwidth, video bandwidth and detector type. Finally, a proposed spectral mask will be discussed. This spectral mask can be used to calculate the required attenuation for a given frequency offset from the center frequency. The required attenuation is a function of the the bit rate or maximum frequency of interest and the transmitter power. This spectral mask is proposed to be part of the next edition of the Telemetry Standards, Inter-Range Instrumentation Group (IRIG) Standard 106.

International Telemetering Conference Proceedings / October 22-25, 2001 / Riviera Hotel and Convention Center, Las Vegas, Nevada / Shaped Offset QPSK (SOQPSK), as proposed and analyzed by Terrance Hill, is a family of constant envelope waveforms that is non-proprietary and exhibits excellent spectral containment and detection efficiency. Results using a conventional coherent OQPSK demodulator without any special pulse shaping to recover the SOQPSK signal have been previously presented. This paper describes a trellis detector for SOQPSK-A and SOQPSK-B that provides superior detection performance, as compared to a traditional OQPSK detector, by accounting for the pulse shaping. Analytical error performance bounds, implementation of the trellis demodulator, and computer simulation results are presented.

We consider a model of N particles interacting through a Kac-style collision process, with m particles among them interacting, in addition, with a thermostat. When m = N, we show exponential approach to the equilibrium canonical distribution in terms of the L2 norm, in relative entropy, and in the Gabetta-Toscani-Wennberg (GTW) metric, at a rate independent of N. When m < N , the exponential rate of approach to equilibrium in L2 is shown to behave as m/N for N large, while the relative entropy and the GTW distance from equilibrium exhibit (at least) an "eventually exponential” decay, with a rate scaling as m/N^2 for large N. As an allied project, we obtain a rigorous microscopic description of the thermostat used, based on a model of a tagged particle colliding with an infinite gas in equilibrium at the thermostat temperature. These results are based on joint work with Federico Bonetto, Michael Loss and Hagop Tossounian.

International Telemetering Conference Proceedings / October 23-26, 2000 / Town & Country Hotel and Conference Center, San Diego, California / The Advanced Range Telemetry (ARTM) program is a tri-service telemetry modernization project whose goal is to assure that all Department of Defense (DoD) test and training ranges are able to use telemetry as necessary to carry out their respective missions. Multi-h Continuous Phase Modulation (CPM) has been selected by the ARTM JPO as the Tier II ARTM waveform, because it offers significant improvements over both legacy telemetry waveforms (PCM/FM) and the newly-introduced Tier I waveform (Feher-patented FQPSK) in terms of spectral containment and detection efficiency, while retaining a constant envelope characteristic. The paper describes the theoretical and measured performance of the ARTM Tier II multi-h CPM waveform, and the implementation of the trellis demodulator being developed for it.