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  1. Towards navigation based on 120 satellites : analyzing the signals

    Gao, Grace X. (Grace Xingxin)
    2008, c2009.

    Online Search ProQuest Dissertations & Theses. Not all titles available.

  2. Statistical theory for the detection of persistent scatterers in insar imagery

    Huang, Stacey Amy
    [Stanford, California] : [Stanford University], 2021

    Interferometric Synthetic Aperture Radar (InSAR) is a powerful remote sensing technique for observing subtle deformation of the Earth's surface over time through multiple observations of the same ground area. Because radar backscatter depends on wavelength-scale properties of surfaces, traditional InSAR methods can fail over naturally changing terrain. The persistent scatterer InSAR (PS-InSAR) technique is one important extension for time-series analysis which identifies and utilizes only the most reliable points in InSAR images for analysis. PS-InSAR has been successfully applied to detect mm-level deformation associated with natural hazards such as earthquakes, volcanoes, and landslides. To date, however, the implementation of PS-InSAR has not been fully optimized, which can limit its utility in challenging mixed-terrain regions. In this thesis, we show that these techniques can be further optimized by characterizing the statistics of PS and developing a statistical framework for applying PS-InSAR techniques. There are three major parts to this work. First, we analyze PS density for different terrain types and image resolution and present a model for predicting the change in PS density, which adheres to empirical results within 50% error and closer for points that form the desired network for PS. Second, we characterize the probability distribution functions (PDFs) of the backscatter from PS and non-PS (clutter) and find that both are highly non-Gaussian over a variety of bandwidths and wavelengths. Finally, we demonstrate a novel maximum likelihood PS detector based on these non-Gaussian models. We show results from the improved detector over Hawaii's Kilauea Volcano and California's Central Valley. In both areas, the non-Gaussian detector finds many more PS than in the existing detector, which leads to a more complete map of deformation. Further, we find that the retrieved deformation time-series is consistent with that measured with three other methods: the existing maximum likelihood Gaussian detector, the small baseline subset (SBAS) InSAR method, and GPS

  3. Precision navigation of miniaturized distributed space systems using GNSS

    Giralo, Vincent Paul
    [Stanford, California] : [Stanford University], 2021

    The way humans conduct spaceflight is being revolutionized by two key trends. The first trend is the distribution of payload tasks among multiple coordinated units, referred to as Distributed Space Systems (DSS), which allow for advances in planetary science, astronomy and astrophysics, and space infrastructure and development. The second is spacecraft miniaturization, where micro- and nanosatellites are transitioning from being merely educational tools to a viable scientific platform. Together, these pushes call for strict Guidance, Navigation, and Control (GNC) requirements while adhering to on-board constraints. In particular, advanced DSS require precise real-time knowledge of the relative orbits of each spacecraft in the system. Centimeter-level relative positioning precision can be obtained from Global Navigation Satellite Systems (GNSS), but this has only been demonstrated on ground through post-processing and only between two spacecraft. This research presents a methodology for nanosatellite swarms to provide on-board navigation solutions in real time using differential GNSS, combining the precision from ground-operated navigation systems with the timeliness of on-board payloads. To accomplish this task, a large swarm is divided into smaller subsets, within which differential GNSS provides centimeter-level relative positioning through successful carrier-phase integer ambiguity resolution. These precise subset estimates are then fused together to form a full swarm orbit estimate on each spacecraft. This system is validated in a new GNSS testbed at Stanford, designed to characterize and profile both hardware and software for GNC payloads. A hardware-in-the-loop experiment demonstrates that the new navigation system can provide precise navigation solutions to a swarm of six spacecraft, including the first demonstration of integer ambiguity resolution on CubeSat avionics. The payload is then applied to two upcoming science missions for which it is considered a mission-enabling technology: the Virtual Super-resolution Optics with Reconfigurable Swarms (VISORS) and the Miniaturized Distributed Occulter/Telescope (mDOT). These missions both present unique challenges, showing that the navigation system can meet strict mission requirements in the presence of frequent control maneuvers and large inter-spacecraft separations. In the latter case, a novel hybrid extended/unscented Kalman filter (KF) estimates the differential ionospheric path delay between GNSS receivers in the swarm, using an unscented KF measurement update to better handle nonlinearities while reducing computational load through an extended KF time update


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