Field-wise wind estimation (also known as model-based wind estimation) is a sophisticated technique to derive wind estimates from radar backscatter measurements. In contrast to the more traditional method known as point-wise wind retrieval, field-wise techniques estimate wind field model parameters. In this way, neighboring wind vectors are jointly estimated, ensuring consistency. This work presents and implementation for field-wise wind retrieval for the SeaWinds scatterometer on the QuikSCAT satellite. Due to its sophistication, field-wise wind retrieval adds computational complexity and intensity. The tradeoffs necessary for practical implementations are examined and quantified. The Levenberg-Marquardt algorithm for minimizing the field-wise objective function is presented. As the objective function has several near-global local minima, several wind fields represent ambiguous wind field estimates. A deterministic method is proposed to ensure sufficient ambiguities are obtained. An improved method for selecting between ambiguous wind field estimates is also proposed. With a large set of Sea-Winds measurements and estimates available, the σ° measurement statistics are examined. The traditional noise model is evaluated for accuracy. A data-driven parameterization is proposed and shown to effectively estimate measurement bias and variance. The parameterized measurement model is used to generate Cramer-Rao bounds on estimator performance. Using the Cramer-Rao bound, field-wise and point-wise performances are compared.

Spaceborne scatterometer instruments are important tools for the remote sensing of the Earth's environment. In addition to the primary goal of measuring ocean winds, data from scatterometers have proven useful in the study of a variety of land and cryopshere processes as well. Several satellites carrying scatterometers have flown in the last two decades. These previous systems have been "fan-beam" scatterometers, where multiple antennas placed in fixed positions are used. The fan-beam scatterometer approach, however, has disadvantages which limit its utility for future missions. An alternate approach, the conically-scanning "pencil-beam" scatterometer technique, alleviates many of the problems encountered with earlier systems and provides additional measurement capability. Due to these advantages, the pencil-beam approach has been selected by NASA as the basis for future scatterometer missions. Whereas the fan-beam approach is mature and well understood, there is need for a fundamental study of the unique aspects of the pencil-beam technique. In this dissertation, a comprehensive treatment of the design issues associated with pencil-beam scatterometers is presented. A new methodology is established for evaluating and optimizing the performance of conically-scanning radar systems. Employing this methodology, key results are developed and used in the design of the SeaWinds instrument - NASA's first pencil-beam scatterometer. Further, the theoretical framework presented in this study is used to propose new scatterometer techniques which will significantly improve the spatial resolution and measurement accuracy of future instruments.

The NASA Scatterometer (NSCAT) was launched August 20, 1996 aboard the National Space Development Agency of Japan's Advanced Earth Observing Spacecraft (ADEOS). NSCAT's primary mission was to measure radar backscatter over the world's oceans. These measurements are used to generate estimates of ocean wind speed and direction. Scatterometers must be calibrated before their measurements are scientifically useful. However, the calibration of NSCAT must be done in orbit. A new methodology for selecting land regions for use in extended target spaceborne scatterometer calibration is first developed. Next, a summary of the calibration technique used in this thesis is presented. While the foundation of this technique was previously developed theoretically, the work in this thesis is its first application for calibration/validation of an on-line spaceborne radar system. The technique is extended to estimate simultaneously NSCAT's calibration and the host spacecraft's attitude error. The attitude references reported by the attitude control system on-board ADEOS are deemed erroneous. Results of this expanded technique, applied under varying assumptions, are presented for consideration. A summary and suggestions for future research conclude this work.

An algorithm has been developed that enables improved the resolution wind estimates from SeaWinds data. This thesis presents the development of three key portions of the high resolution wind retrieval algorithm: Compositing individual σ-0 measurements and Kp, Retrieved wind bias correction, and ambiguity selection for high resolution winds. The high resolution winds produced by this algorithm are expected to become a useful resource for scientists and engineers studying the ocean winds. The high resolution wind retrieval algorithm allows wind to be retrieved much closer to land than is available from the low resolution winds estimated from the same scatterometer by the Jet Propulsion Laboratory. The high resolution winds allow features such as the eye of hurricanes to be seen with much greater detail than was previously possible.

The QuikSCAT scatterometer provides global daily coverage of oceanic near-surface vector winds. Recently, algorithms have been developed to enhance the spatial resolution of QuikSCAT winds from 25~km to 2.5~km posting. These ultra-high resolution winds are used, in comparison with standard L2B data product winds, to observe and track tropical cyclones. Resolution enhanced winds are found to provide additional storm structure such as inner core size and structure and the presence of multiple eyewalls compared with standard resolution winds. The 2.5~km winds are also able to observe storms nearer to the shore than 25~km winds. An analysis of circulation center locatability with each resolution wind field is performed. Center fixes with enhanced resolution winds are nearer the National Hurricane Center best-track positions than are standard resolution center fixes. A data and image set of every tropical cyclone worldwide observed by Seawinds on QuikSCAT or SeaWinds on ADEOS II from 1999 through 2005 is generated and made available to the scientific community at http://scp.byu.edu.

The SeaWinds scatterometers aboard the QuikSCAT and ADEOS II satellites were originally designed to measure wind vectors over the ocean by exploiting the relationship between wind-induced surface roughening and the normalized radar backscatter cross-section. Recently, an algorithm for simultaneously retrieving wind and rain (SWR) from scatterometer measurements was developed that enables SeaWinds to correct rain-corrupted wind measurements and retrieve rain rate data. This algorithm is based on co-locating Tropical Rainfall Measuring Mission Precipitation Radar (TRMM PR) and SeaWinds on QuikSCAT data. In this thesis, a new wind and rain radar backscatter model is developed for the SWR algorithm using a global co-located data set with rain data from the Advanced Microwave Scanning Radiometer (AMSR) and backscatter data from the SeaWinds scatterometer aboard the Advanced Earth Observing Satellite 2 (ADEOS II). The model includes the effects of phenomena such as backscatter due to wind stress, atmospheric rain attenuation, and effective rain backscatter. Rain effect parameters of the model vary with integrated rain rate, which is defined as the product of rain height and rain rate. This study accounts for rain height in the model in order to calculate surface rain rate from the integrated rain rate. A simple model for the mean rain height versus latitude and longitude is proposed based on AMSR data and methods of incorporating this model into the SWR retrieval process are developed. The performance of the new SWR algorithm is measured by comparison of wind vectors and rain rates to the previous SWR algorithm, AMSR rain rates, and NCEP numerical weather prediction winds. The new SWR algorithm produces accurate rain estimates and detects rain with a low false alarm rate. The wind correction capabilities of the SWR algorithm are effective at correcting rain-induced inaccuracies. A qualitative comparison of the wind and rain retrieval for Hurricane Isabel demonstrates these capabilities.

While the standard wind product (L2B) available operationally in near-real time from SeaWinds on QuikSCAT is only 25 km in resolution, QuikSCAT data can be enhanced to yield a 2.5 km ultra-high resolution (UHR) product. The latter can be used to help estimate Tropical Cyclone (TC) characteristics such as TC eye center and wind radii. Two studies are conducted in this thesis, in which QuikSCAT UHR wind product's effectiveness in estimating these TC characteristics is evaluated. First, a comparison is made between the analyst's choice of eye location based on UHR images and interpolated best-track position. In this analysis, the UHR images are divided into two categories, based on the analyst's confidence level of finding the eye center location. In each category, statistical error quantities are computed. UHR images within the high confidence category can provide, for a given year and basin, mean error distance as small as 19 km with a 10 km standard deviation. Second, a visual comparison of QuikSCAT's performance in estimating wind radii is made. QuikSCAT's performance is gauged against H*wind dataset and the Extended Best-Track (EBT) dataset. Results show that QuikSCAT UHR data yields a correct 34-kt wind radius most of the time regardless of the TC category when compared to both H*wind and EBT, whereas the 50- and 64-kt wind radii visual estimates do not always agree with H*wind and EBT. A more sophisticated method is also implemented to automatically estimate wind radii based on a model fit to QuikSCAT data. Results from this method are compared with EBT wind radii. Wind radii obtained from QuikSCAT model fit are generally highly correlated with EBT estimated wind radii. These two studies show that QuikSCAT UHR wind products are helpful in estimating TC eye location and wind radii, thus improving TC forecasting and analysis.

En microélectronique, l'augmentation de la densité des composants est la solution principale pour améliorer la performance des circuits. Ainsi, la taille des structures définies par la lithographie diminue à chaque changement de nœud technologique. A partir du nœud 14 nm, la lithographie optique est confrontée à la limite de résolution pour les niveaux métalliques. Pour surmonter cet obstacle, les niveaux métalliques sont conçus en deux étapes successives de patterning regroupant chacune une étape de lithographie et une étape de gravure. Cette technique, nommée double patterning, requiert une métrologie adaptée car l'alignement entre les deux étapes et les dimensions critiques sont alors directement liées. La méthode de mesure développée dans cette thèse repose sur la scattérométrie et la mesure de l'alignement par diffraction. Un code de simulation a permis d'optimiser la conception des mires de mesure. De plus, la méthode de mesure adoptée a pu être validée expérimentalement. / In microelectronics, the increase of component density is the main solution to improve circuit performance. The size of the patterns defined by lithography is reduced at each change of technology node. From the 14 nm node, optical lithography is facing the resolution limit for metal levels. In order to overcome this hurdle, metal levels are designed in two successive steps of patterning, which is composed of lithography followed by etching. This double patterning technique requires an appropriate metrology since overlay between the two steps and critical dimensions are directly linked. The developed method is based on scatterometry and overlay measurement by diffraction. Using a simulation code, the measurement targets have been designed optimally. Then the adopted method has been validated experimentally.

The Imaging Wind and RAin Profiler (IWRAP) is an airborne scatterometer system built and operated by University of Massachusetts Amherst's Microwave Remote Sensing Laboratory (MIRSL). The radar is seasonally deployed aboard one of the two National Oceanic and Atmospheric Administration (NOAA) WP-3D Orion ``Hurricane Hunter'' aircraft based out of MacDill AFB in Tampa, Florida. IWRAP is a dual-frequency, Ku- and C-band, scatterometer that uses two conically scanning antennas to estimate the ocean surface wind vectors as well as intervening rain profiles. Data that is gathered with IWRAP is used to improve current Geophysical Model Functions (GMF) or to help derive new GMFs for other undocumented incidence angles. This thesis outlines the improvements and changes made to the IWRAP system from 2009-2011. Chapter Two describes the IWRAP instrument including a description of the instrument status as of Fall 2009, and a summary of instrument operations in 2010 and 2011. Chapter Three describes hardware and software modifications to support dual-polarization. It also describes hardware-based and flight-based attempts to observe at large incidence angles. Chapter Four is an analysis of the stability of the internal calibration both during flights and over a season. System documentation is consolidated into a single technical manual in Appendix A.

This dissertation approaches high resolution scatterometry from a new perspective. Three related general topics are addressed: high resolution σ^0 imaging, wind estimation from high resolution σ^0 images over the ocean, and high resolution wind estimation directly from the scatterometer measurements. Theories of each topic are developed, and previous approaches are generalized and formalized. Improved processing algorithms for these theories are developed, implemented for particular scatterometers, and analyzed. Specific results and contributions are noted below. The σ^0 imaging problem is approached as the inversion of a noisy aperture-filtered sampling operation-extending the current theory to deal explicitly with noise. A maximum aposteriori (MAP) reconstruction estimator is developed to regularize the problem and deal appropriately with noise. The method is applied to the SeaWinds scatterometer and the Advanced Scatterometer (ASCAT). The MAP approach produces high resolution σ^0 images without introducing the ad-hoc processing steps employed in previous methods. An ultra high resolution (UHR) wind product has been previously developed and shown to produce valuable high resolution information, but the theory has not been formalized. This dissertation develops the UHR sampling model and noise model, and explicitly states the implicit assumptions involved. Improved UHR wind retrieval methods are also developed. The developments in the σ^0 imaging problem are extended to deal with the nonlinearities involved in wind field estimation. A MAP wind field reconstruction estimator is developed and implemented for the SeaWinds scatterometer. MAP wind reconstruction produces a wind field estimate that is consistent with the conventional product, but with higher resolution. The MAP reconstruction estimates have a resolution similar to the UHR estimates, but with less noise. A hurricane wind model is applied to obtain an informative prior used in MAP estimation, which reduces noise and ameliorates ambiguity selection and rain contamination.