A novel method of human presence detection using passive millimeter-wave sensors is presented. The method focuses on detecting a standing human from a moving platform in a cluttered outdoor environment using millimeter-wave radiometry, which has not been attempted before. Ka-band radiometers are used in total power mode as well as correlation mode, which ideally responds well to self-luminous objects such as humans. The intrinsic radiative power from a human is derived as well as the responses of the total power and correlation mode. The application of correlation radiometer theory to the detection of self-luminous objects at close range is presented in the context of human presence detection. Modifications and additions to techniques developed in radio astronomy and remote sensing for close range terrestrial situations are developed and discussed. The correlation radiometer fringe frequency is analyzed in the context of the scanning beam detection system and is estimated using MUSIC and ESPRIT. Detection and classification of humans is accomplished using a Naïve Bayesian classifier. The performance of the classifier is measured using the F1-measure and the receiver operating characteristic. / text

ITC/USA 2013 Conference Proceedings / The Forty-Ninth Annual International Telemetering Conference and Technical Exhibition / October 21-24, 2013 / Bally's Hotel & Convention Center, Las Vegas, NV / The University Rover Challenge is a competition to build a scaled down version of a next-generation Mars rover. This paper describes the comprehensive systems engineering based approached used by the Missouri S&T Mars Rover Design Team. This student run, interdisciplinary team of approximately 50 students followed a comprehensive systems-engineering based approach to the conceptualization, design, implementation, test and evaluation of the project. This has allowed students to leverage their discipline specific expertise, while simultaneously facilitating the cross-disciplinary communication which is essential to the successful completion of the project. The team's performance in the competition will provide metrics to analyze the efficacy of this organization and approach.

Specular reflection off the ocean surface has been used to derive ocean wave heights and surface wind speeds, but the effect that waves have on ocean surface reflection of incident solar radiation is not fully understood. This study focussed on measuring how sun glint affects the Earth's radiation budget, by including the previously ignored specularly reflecting region. Measurements collected by the GOES-10 geostationary satellite were used to produce an effective sun glint albedo to characterize the accuracy of omitting the glint region from the radiation budget. Estimations were made using the Cox/Munk statistical distribution model. These results varied slightly as a function of wind speed where a 6 m/s surface wind speed produced an effective clear sky sun glint albedo of 1.9%. This value was less than the satellite measured value of 2.2 ± 0.1% for measurements in the cloud free region. Estimates including clouds show a smaller glitter effect of 1.7 ± 0.1%. These values were then extrapolated to the full Earth value by including ocean fraction resulting in global values of 1.6 ± 0.1% and 1.2 ± 0.1% for clear sky and cloudy respectively.

The large extension and diversity of the Cerrado vegetative cover, the second largest biome in South America, has a strong impact on regional, and possibly global, energy, water, and carbon balances. Nevertheless, as a major farming frontier in Brazil, it is estimated that about 40% of the Cerrado land cover has already been converted into cultivated pastures, field crops, urban development, and degraded areas. Despite this aggressive pace of land conversion, there have been few investigations on the operational utilization of remote sensing data to effectively monitor and understand this biome. Within this context, and within the goals and framework of the Large Scale Biosphere-Atmosphere Experiment in Amazonia (LBA), we evaluated the usefulness of spectral vegetation indices (VIs), to effectively monitor the Cerrado, detect land conversions, and discriminate and assess the conditions of the major structural types of Cerrado vegetation. Using a full hydrologic year (1995) of AVHRR, local-area-coverage (LAC), data over the Cerrado, converted to normalized difference vegetation index (NDVI) and soil adjusted vegetation index (SAVI), we were able to spatially discriminate three major communities based on their phenologic patterns. These included savanna formations and pasture sites, forested areas, and agricultural crops. We also analyzed wet and dry season, aircraft-based radiometric data and a ground-based set of biophysical measurements, collected over the Brasilia National Park (BNP), the largest LBA core site in the Cerrado biome. Overall, we found the MODIS vegetation indices, which include a continuity NDVI and the new enhanced vegetation index (EVI), to provide better performance capabilities with improved dynamic ranges and contrasts in seasonal dynamics. Land cover discrimination was favored by the NDVI, while the EVI more strongly responded to the seasonal contrast of the vegetative cover. Thus, the synergistic use of the MODIS VI products will very likely result in an improved monitoring capability and understanding of the Cerrado biome.

No description available.

Passive microwave remote sensing has shown potential for monitoring near surface soil moisture. This dissertation presents a new approach to representing the effect of vegetation on microwave emission by extending an existing model (Wilheit, 1978) of the coherent propagation of electromagnetic radiation through a stratified medium. The resulting multi-layer microwave emission model is plausibly realistic in that it captures the behavior of the vegetation canopy by considering the dielectric permittivity of the mixture of air and vegetation matter in the canopy and recognizing the vertical distribution of dielectric permittivity through the canopy. The model parameters required to specify the dielectric profile within the canopy are not usually available from data taken in typical field experiments, particularly the parameters that quantify the way the dielectric permittivity of the vegetation and air mix together to give the dielectric permittivity of the canopy. Thus, the feasibility of specifying these parameters using an advanced single-criterion, multiple-parameter optimization technique was investigated. The resulting model was also applied to investigate the sensitivity of microwave emission to specific vegetation parameters. The study continued with an investigation of how the presence and nature of vegetation cover influences the values of geophysical variables retrieved from multi-angle microwave radiometer spectrometer observations, using the upcoming Soil Moisture Ocean Salinity (SMOS) mission as a case study. The extended version of the Wilheit (1978) model was used to calculate synthetic observations of microwave brightness temperature at the look-angles proposed for the SMOS mission for three different soil moisture states (wet, medium, and dry) and four different vegetation covers (grass, crop, shrub, and forest). It was shown that retrieved values are only accurate when the effective values of the opacity coefficient used in the Fresnel model are made to vary in a prescribed way with look-angle, soil moisture status, and vegetation. The errors in retrieved values that may be induced by poor specification of vegetation cover were investigated by imposing random errors in the values of vegetation-related parameters in the forward calculations of synthetic observations made with the extended Wilheit model. The results show that poorly specified vegetation can result in both random and systematic errors in the retrieved values of the geophysical variables. (Abstract shortened by UMI.)

The Modulation Transfer Function (MTF) is a standard measure of imaging systems performance. This work addresses determination of the MTF for the Moderate Resolution Imaging Spectroradiometer (MODIS) Earth remote sensing system on NASA's TERRA satellite. Reliable characterization of the MODIS MTF requires using as many sources of information as possible for evaluation. In this research a model, pre-launch and on-orbit measurements are used to develop a consistent characterization of the MTF. The on-orbit characterization is implemented using two approaches. The first is cross-track temporal monitoring using data derived from the SpectroRadiometric Calibration Assembly (SRCA). The second is using a two-image approach in which the reference is Landsat-7 Enhanced Thematic Mapper (ETM+) and Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER). This characterization of the MTF is used to evaluate the effect on science products, the Normalized Difference Vegetation Index (NDVI) and the Enhanced Vegetation Index (EVI), and includes partial MTF correction (MTFc) as a way to improve the accuracy. This work has produced the following significant results: (1) A model for the pre-launch MODIS MTF. (2) Automatic image registration using the geolocation data. (3) Cross-track on-orbit MTF are comparable to the pre-launch MTF for bands 1, 2, 6 and 29. (4) In-track on-orbit MTF indicate that it is lower for bands 1 and 2 (in most cases), and comparable for bands 6 and 29, in reference to the pre-launch MTF.

This dissertation investigated the estimation of global cloud water amounts. The study was prompted by the large discrepancy in published global mean values of cloud liquid water path. Microwave and optical satellite measurements of this quantity range from 25 g/m² to 80 g/m². Theoretical estimates are significantly larger with a current best guess value of 380 g/m². The major limitations of microwave measurements were found to be the inadequate separation of the cloud- and rainwater components, and the lack of retrievals over land. Optical observations were found to be constrained by the truncation of retrieved optical thickness due to saturation effects, the limited knowledge of drop effective radius as a function of optical thickness and rain rate, and plane-parallel retrieval errors due to 3D effects. An analysis of the potential uncertainties concluded that the current theoretical estimate of the global mean cloud liquid water path of 380 g/m² was reasonable with an uncertainty of ±80 g/m². Errors in the optical retrievals due to 3D effects were estimated using a multiangle data set. A microwave-optical comparison revealed that a drop effective radius significantly larger than the common assumption of 8-10 μm was required to remove the low bias of optical retrievals of cloud liquid water in precipitating systems. The low bias due to saturation effects was accounted for by sigmoidal extrapolation of the cumulative distribution of cloud optical thickness. Overall it was found that the optical measurement of the global mean cloud liquid water path could be increased to a maximum of 150 g/m² over the oceans. The failure to close the gap between satellite measurements and theoretical estimates can partly be attributed to, but cannot be completely explained by, the lack of the most intense continental clouds in the ocean-only data set used in this study. It is unlikely that optical measurements can be corrected to accurately retrieve the largest liquid water amounts. New techniques are required to handle the wettest precipitating clouds.

Images acquired by ground-based telescopes are severely degraded by atmospheric turbulence effects. New algorithms are presented for restoration with super-resolution of satellite object images from sequences of turbulence-degraded observations. Super-resolution refers to recovery of Fourier spectral components outside the optical system passband. Modern wave front sensor (WFS) can measure the optical distortions caused by the atmosphere. Such measurement can be used for (1) control of an adaptive optics (AO) system; (2) for post-processing of the uncompensated image; and (3) for a hybrid approach involving partially compensated images. This study focuses on the second of these approaches. Quantitative simulation of imaging through turbulence and WFS are used to demonstrate the performance of new super-resolving multiframe algorithms based on Bayes maximum a posteriori (MAP) criterion. The original and object images are assumed to have Poisson statistics. The resulting Poisson MAP algorithms extend the single frame version to the multiframe case. Super-resolution is demonstrated for realistic conditions. In the blind deconvolution problem, both the original image and the degradations must be derived simultaneously from the recorded images without the aid of WFS. We investigate this problem and propose a new multiframe algorithm based on Bayes maximum likelihood. Strict constraints such as positivity and finite bandwidth are incorporated using nonlinear reparameterizations. Nonlinear conjugate gradient techniques are employed along with implementation on the massively parallel IBM SP2, in order to meet the computational demands of these algorithms. Super-resolution is demonstrated for realistic circumstances. On a related subject, nonlinear interpolative vector quantization (NLIVQ) is presented as a tool for the novel application of vector quantization (VQ) to super-resolution of diffraction-limited images. The algorithm is trained on a large set of image pairs, consisting of an original and its diffraction-limited counterpart, and exploits the statistical dependence between blocks of pixels in the two images. The discrete cosine transform (DCT) is used to manage the codebook complexity and simplify training. Simulation results are presented which demonstrate improvements in the visual quality and peak signal-to-noise ratio. A study of restored image spectra reveals modest super-resolution. The prospects for this technique are promising.

Measurements of the refractive bending of solar radiation passing through the limb of the Earth's atmosphere can be utilized to recover vertical profiles of density and temperature. These parameters obtained using the technique of solar refractive sounding could be used to improve satellite solar occultation trace species retrievals and to monitor potential trends in upper atmospheric temperatures. The solar refractive sounding method is described in detail and applied to data available from the Stratospheric Aerosol and Gas Experiment (SAGE II). The meteorological profiles derived from the SAGE II data are not consistently accurate enough for general use due to poor vertical sampling and measurement uncertainties. However, the qualitatively decent results provide optimism for future development and implementation of solar occultation refractive sounders. Better techniques for measuring solar refraction and the potential improvements in the retrievals are also discussed.