The ever-increasing resolution of CMOS imagers has steadily driven the requirements of readout circuitry. As the number of sensors on a chip increases, the bandwidth of the readout circuit must be increased correspondingly to maintain a constant frame rate. Column parallel A/D converters are commonly used to divide the conversions among many converters. However, implementing high-speed, high-resolution A/D converters at the column level is challenging because the entire circuit needs to be as narrow as the sensor. This thesis presents the design of a 10-bit, one million conversions per second column-parallel A/D converter. A factor of four increase in speed over conventional converters was achieved by combining techniques of successive approximation and two-step subranging in a distributed column-parallel architecture. The speed of the converter makes it suitable to be integrated with a 1-megapixel sensor array providing a frame rate at 1000fps with 11µm pixels in a 0.35µm CMOS technology.

Synthetic Aperture Radar interferometry (InSAR) is a powerful and established technique, which is based on exploiting the phase difference between pairs of SAR images, and which aims to measure changes in the Earth’s surface. The quality of the interferometric phase is therefore the most crucial factor for deriving reliable products by means of this technique. Unfortunately, the quality of the phase is often degraded due to multiple decorrelation factors, such as the geometrical or temporal decorrelation. Accordingly, central to this PhD thesis is the development of advanced processing techniques and algorithms to extensively reduce such disturbing effects caused by decorrelation. These new techniques include an improved range spectral filter which fully utilizes an external Digital Elevation Model (DEM) to reduce geometrical decorrelation between pairs of SAR images, especially in areas strongly influenced by topography where conventional methods are limited; an improved filter for the final interferometric phase the goal of which is to remove any remaining noise (for instance, noise caused by temporal decorrelation) while, simultaneously, phase details are appropriately preserved; and polarimetric optimization algorithms which also try to enhance the quality of the phase by exploring all the polarization diversity. Moreover, the exploitation of InSAR data for crop type mapping has also been evaluated in this thesis. Specifically, we have tested if the multitemporal interferometric coherence is a valuable feature which can be used as input to a machine learning algorithm to generate thematic maps of crop types. We have shown that InSAR data are sensitive to the temporal evolution of crops, and, hence, they constitute an alternative or a complement to conventional radiometric, SAR-based, classifications.

Plants have evolved an efficient mechanism to defend themselves against pathogens. Many biotic and abiotic agents have been shown to induce defense mechanism in plants. Acibenzolar-S-Methyl (ASM) is a commercially available chemical inducer of local and systemic resistance (SAR) response in plants. ASM functioning at molecular level is mostly unclear. This research was designed to investigate the mechanism of ASM action in plants. It was hypothesized that SABP2, a plant protein, plays an important role in ASM-mediated defense signaling. Biochemical studies were performed to test the interaction between SABP2 and ASM. Transgenic SABP2-silenced tobacco plants were used to determine the role of SABP2 in SAR induced by ASM. The expression of PR-1 proteins was used as a marker for SAR induction. Results showed that SABP2 converts ASM into acibenzolar that induces the expression of PR-1 proteins and develops the SAR response in ASM-treated plants.

Conventional Synthetic Aperture Radar (SAR) offers high-resolution imaging of a target region in the range and cross-range dimensions along the ground plane. Little or no data is available in the range-altitude dimension, however, and target functions and models are limited to two-dimensional images. This thesis first investigates some existing methods for the computation of target reflectivity data in the deficient elevation domain, and a new method is then proposed for three-dimensional (3-D) SAR target feature extraction. Simulations are implemented to test the decoupled least-squares technique for high-resolution spectral estimation of target reflectivity, and the accuracy of the technique is assessed. The technique is shown to be sufficiently accurate at resolving targets in the third axis, but is limited in practicality due to restrictive requirements on the input data. An attempt is then made to overcome some of the practical limitations inherent in the current 3-D SAR methods by proposing a new technique based on the direct extraction of 3-D target features from arbitrary SAR image inputs. The radar shadow present in SAR images of MSTAR vehicle targets is extracted and used in conjunction with the radar beam depression angle to compute physical target heights along the range axis. Multiple inputs of elevation data are then merged to forge rough 3-D target models. The project is a continuation of prior SAR research at Cal Poly under Dr. John Saghri with the sponsorship of Raytheon Space & Airborne Systems.

Opportunities to use synthetic aperture radar (SAR) in scientific studies and military operations are expanding with the development of small SAR systems that can be operated on small unmanned air vehicles (UAV)s. While the nimble nature of small UAVs make them an attractive platform for many reasons, small UAVs are also more prone to deviate from a linear course due autopilot errors and external forces such as turbulence and wind. Thus, motion compensation and improved processing algorithms are required to properly focus the SAR images. The work of this dissertation overcomes some of the challenges and addresses some of the opportunities of operating SAR on small UAVs. Several contributions to SAR backprojection processing for UAV SARs are developed including: 1. The derivation of a novel SAR backprojection algorithm that accounts for motion during the pulse that is appropriate for narrow or ultra-wide-band SAR. 2. A compensation method for SAR backprojection to enable radiometrically accurate image processing. 3. The design and implementation of a real-time backprojection processor on a commercially available GPU that takes advantage of the GPU texture cache. 4. A new autofocus method that improves the image focus by estimating motion measurement errors in three dimensions, correcting for both amplitude and phase errors caused by inaccurate motion parameters. 5. A generalization of factorized backprojection, which we call the Dually Factorized Backprojection method, that factorizes the correlation integral in both slow-time and fast-time in order to efficiently account for general motion during the transmit of an LFM-CW pulse. Much of this work was conducted in support of the Characterization of Arctic Sea Ice Experiment (CASIE), and the appendices provide substantial contributions for this project as well, including: 1. My work in designing and implementing the digital receiver and controller board for the microASAR which was used for CASIE. 2. A description of how the GPU backprojection was used to improved the CASIE imagery. 3. A description of a sample SAR data set from CASIE provided to the public to promote further SAR research.

Deviations from a nominal, straight-line flight path of a synthetic aperture radar (SAR) lead to inaccurate and defocused radar images. This thesis is an investigation into the improvement of the motion compensation algorithm created for the BYU inteferometric synthetic aperture radar, YINSAR. The existing BYU SAR processing algorithm produces improved radar imagery but does not fully account for variations in attitude (roll, pitch, yaw) and does not function well with large position deviations. Results in this thesis demonstrate that a higher order motion compensation algorithm is not as effective as using a segmented reference track, coupled with the current lower-order motion compensation algorithm. Attitude variations cause a Doppler shift and are corrected by limiting the processed azimuth bandwidth or by reversing the frequency shift with a range-dependent filter. Another important area considered is the effects of motion compensation on interferometry. When performing interferometry with YINSAR, motion compensating both channels to a single track has two effects. First, the applied MOCO phase corrections remove the "flat-earth" differential phase from the interferogram. Second, range resampling coregisters the two images. All of these changes have helped to improve YINSAR imagery.

Brigham Young University has developed a low-cost, light-weight, and low power consumption SAR for flight on a small unmanned aerial vehicle (UAV) at low altitudes. This micro-SAR, or uSAR, consumes only 18 watts of power, ideal for application on a small UAV. To meet these constraints, a linear frequency modulation-continuous wave (LFM-CW) transmit signal is utilized. Use of an LFM-CW signal introduces some differences from the typical strip map SAR processing model that must be addressed in signal processing algorithms. This thesis presents a derivation of the LFM-CW signal model and the associated image processing algorithms used for the uSAR developed at BYU. A data simulator for the BYU LFM-CW SAR is detailed and results are provided for the case when the simulated data are processed using the uSAR algorithms. Data processing schemes are discussed, including compression, receive signal phase detection, interference filtering and auto-focusing. Finally, data collected from the instrument itself are processed and presented.

In this thesis, the Omega-k algorithm used for processing stripmap synthetic aperture radar (SAR) data is explored in detail. While the original Omega-k algorithm does not achieve the same SNR as a matched filter, a modification is presented which enables the algorithm to nearly achieve that SNR. It is shown that the focused point spread function obtained when the Omega-k algorithm is used differs in important ways from the output of a modified version of the matched filter. Spread out sidelobes and a stretched mainlobe are observed when the data is processed by the Omega-k algorithm. These differences may increase the potential interference between some nearby scatterers; however, the amplitude of the resulting sidelobes is lower than that observed for the matched filter, and the potential interference between other nearby scatterers is reduced. The details of a discrete implementation of the algorithm are also presented. Two methods for mixing the frequency domain signal to baseband are compared, and one is shown to potentially reduce the required accuracy of the interpolation kernel. Finally, the errors associated with the key approximation used by the algorithm are explored through simulation, and it is shown that the approximation is sufficiently accurate for a particularly demanding configuration.

Using co-located space-borne satellite (TRMM PR, ESCAT on ERS 1/2) measurements, and numerical predicted wind fields (ECMWF), the sensitivity of C-band backscatter measurement to rain is evaluated. It is demonstrated that C-band radar backscatter can be significantly altered by rain surface perturbation, an effect that has been previously neglected. A low-order wind/rain backscatter model is developed that has inputs of surface rain rate, incidence angle, wind speed, wind direction, and azimuth angle. The wind/rain backscatter model is accurate enough for describing the total backscatter in raining areas with relatively low variance. Rain has a more significant impact on measurements at high incidence angles than at low incidence angles. Using three distinct regimes, the conditions for which wind, rain, and both wind and rain can be retrieved from scatterometer backscatter measurements are determined. The effects of rain on ESCAT wind-only retrieval are evaluated. The additional scattering from rain causes estimated wind speeds to be biased high and estimated wind directions to be biased toward the along-track direction in heavy rains. To compensate for rain-induced backscatter, we develop a simultaneous wind/rain retrieval method (SWRR), which simultaneously estimates wind and rain from ESCAT backscatter measurements with an incidence angle of over 40 degrees. The performance of SWRR under typical wind/rain conditions is evaluated through simulation and validation with collocated TRMM PR and ECMWF data sets. SWRR is shown to significantly improve wind velocity estimates and the SWRR-estimated rain rate has relatively high accuracy in moderate to heavy rain cases. RADARSAT-1 ScanSAR SWA images of Hurricane Katrina are used to retrieve surface wind vectors over the ocean. Collocated H*wind wind directions are used as the wind direction estimate and the wind speed is derived from SAR backscatter measurements by inversion of a C-band HH-polarization Geophysical Model Function (GMF) that is derived from the VV-polarization GMF, CMOD5, using a polarization ratio model. Because existing polarization models do not fit the ScanSAR SWA data well, a recalibration model is proposed to recalibrate the ScanSAR SWA images. Validated with collocated H*wind wind speed estimates, the mean difference between SAR-retrieved and H*wind speed is small and the root mean square (RMS) error is below 4 m/s. Rain effects on the ScanSAR measurements are analyzed for three different incidence angle ranges using collocated ground-based Doppler weather radar (NEXRAD) rain measurements. Compared with the scatterometer-derived model, the rain-induced backscatter observed by the ScanSAR at incidence angles 44 to 45.7 degrees is consistent with the scatterometer-derived model when the polarization difference between HH and VV polarizations is considered.

Factorized backprojection is a processing algorithm for reconstructing images from data collected by synthetic aperture radar (SAR) systems. Factorized backprojection requires less computation than conventional time-domain backprojection with little loss in accuracy for straight-line motion. However, its implementation is not as straightforward as direct backprojection. Further, implementing an azimuth window has been difficult in previous versions of factorized backprojection. This thesis provides a new, easily parallelizable formulation of factorized backprojection designed for both pulsed and linearly frequency modulated continuous wave (LFM-CW) stripmap SAR data. A method of easily implementing an azimuth window as part of the factorized backprojection algorithm is introduced. The approximations made in factorized backprojection are investigated and a detailed analysis of the corresponding errors is provided. We compare the performance of windowed factorized backprojection to direct backprojection for simulated and actual SAR data.