Browsing by Subject "Ambiguity resolution"
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Item Advanced techniques for centimeter-accurate GNSS positioning on low-cost mobile platforms(2015-12) Pesyna, Kenneth Mark Jr.; Humphreys, Todd Edwin; Heath, Robert W., Jr, 1973-; Vikalo, Haris; York, Johnathan; Sanghavi, SujayOver the past decade, GPS and other Global Navigation Satellite System (GNSS) chipsets have become smaller, cheaper, and more energy efficient, so much so that they now come standard in most smartphones and tablets. Under good multipath conditions, one can expect 2-to-3-meter-accurate positioning with these chipsets, under adverse multipath, accuracy degrades to 10 meters or worse. Outside the mainstream of consumer GNSS receivers, however, centimeter---even millimeter---accurate GNSS receivers are used routinely in geodesy, agriculture, and surveying. The key to their accuracy is a radically different approach to positioning in which the standard code-phase (or pseudorange) positioning technique is replaced by differential carrier-phase positioning. Adopting this high-precision carrier-phase-based technique for consumer-grade mobile devices is possible, but comes with significant challenges. This dissertation identifies and addresses the challenges to performing centimeter accurate carrier-phase differential GNSS (CDGNSS) positioning on low-cost mobile devices. To this end, this dissertation makes three primary contributions. First, this dissertation develops a carrier phase reconstruction technique to address the high power consumption of current CDGNSS algorithms. The reconstruction technique enables a continuous and unambiguous phase time history to be reconstructed from intermittent phase measurements, permitting aggressive duty cycling of the mobile device's internal GNSS chip, decreasing energy consumption. Second, this dissertation demonstrates that a centimeter-accurate positioning solution is possible based on GNSS data collected using a smartphone, a first in the open literature. It is identified that the primary impediment to performing CDGNSS on smartphones lies not in the commodity GNSS chipset within the phone, but instead in the antenna, whose chief failing is its poor multipath suppression, resulting in long initialization times. It is demonstrated that wavelength-scale random antenna motion can be used to decorrelate multipath errors and reduce the initialization period---the so-called time-to-ambiguity-resolution (TAR)---of smartphones employing CDGNSS to obtain centimeter-level positioning fix. Finally, this dissertation develops a framework that tightly fuses smartphone camera image measurements with GNSS carrier phase measurements to reduce CDGNSS initialization times beyond what is achievable using antenna motion alone. The framework augments the traditional bundle-adjustment- (BA-)-based structure from motion (SFM) algorithm with the carrier phase differential GNSS (CDGNSS) algorithm in a way that preserves the key features of both algorithms, namely the sparseness of the matrices in BA and the integer structure of the ambiguities in CDGNSS. The framework is shown to produce a faster, more robust, and more accurate positioning solution than achievable with existing techniques.Item Advanced techniques for safety-of-life carrier phase differential GNSS positioning with applications to triplex architectures(2018-01-24) Green, Gary Nathan; Humphreys, Todd Edwin; Andrews, Jeffrey; de Veciana, Gustavo; Vikalo, Haris; York, JohnathanSafety-of-life Carrier phase Differential Global Navigation Satellite System (CDGNSS) positioning systems must provide guarantees that their position estimates have errors that are smaller than specified levels, called alert limits (AL). These guarantees are specified as an allowable probability, called integrity risk (IR), that the error exceeds its AL. Typical values of IR are between 10⁻⁹ and 10⁻⁷, per hour of operation. CDGNSS positioning has been demonstrated to provide centimeter-accurate estimates of a vehicle's location when the so-called integer ambiguities are resolved; however, in safety-of-life applications, the probability of incorrectly resolving the integer ambiguities frequently exceeds the allowable IR. To address this limitation, existing algorithms bound the positioning error caused by incorrectly resolved ambiguities. If such bounds satisfy the AL, then the integer-resolved, or fixed, solution can be used. Unfortunately, the positioning error from incorrect fixing can exceed several meters, which fails to satisfy the most demanding ALs for autonomous vehicles. This dissertation offers three contributions to the science of CDGNSS positioning for safety-of-life applications. First, a novel algorithm is developed that validates the correctness of integer ambiguity estimates. This algorithm, called Generalized Integer Aperture Bootstrapping (GIAB), establishes a rigorous, fixed-missed-detection-rate test that provides a guarantee that the integer ambiguities have been fixed correctly. GIAB also allows for partial fixing, where a subset of the ambiguities are resolved. Partial fixing allows for graceful degradation of positioning when measurement quality is poor. GIAB is derived analytically and validated via Monte Carlo simulation. Its performance is compared with existing ambiguity validation techniques. Second, the probability density function of the positioning estimate resulting from GIAB is derived. This distribution leads to a provable bound on the IR that the estimate has errors exceeding the specified ALs. This bound allows GIAB to be used for safety-of-life application while satisfying ALs of less than a meter. Third, triplex CDGNSS architectures, in which the vehicle position is estimated using three separate navigation systems with mid-level voting (MLV) logic, are analyzed. Such architectures are commonly used since they are robust to single equipment failures, but the integrity benefit of their fault-free performance has not previously been evaluated. It is shown that integer-fixed CDGNSS solutions improve in accuracy performance, but gain no integrity benefit. However, when the integer constraint is not enforced, the so called CDGNSS float solution benefits greatly from MLV in both accuracy and integrity performance.Item The "resolution" of verb meaning in context(2013-05) Gaylord, Nicholas L.; Erk, Katrin; Bannard, ColinIt is well-known that the meaning of a word often changes depending on the context in which the word is used. Determining the appropriate interpretation for a word occurrence requires a knowledge of the range of possible meanings for that word, and consideration of those possibilities given available contextual evidence. However, there is still much to be learned about the nature of our lexical knowledge, as well as how we make use of that knowledge in the course of language comprehension. I report on a series of three experiments that explore these issues. I begin with the question of how precise our perceptions of word meaning in context really are. In Experiment 1, I present a Magnitude Estimation study in which I obtain judgments of meaning-in-context similarity over pairs of intransitive verb occur- rences, such as The kid runs / The cat runs, or The cat runs / The lane runs. I find that participants supply a large range of very specific similarity judgments, that judgments are quite consistent across participants, and that these judgments can be at least partially predicted even by simple measures of contextual properties, such as subject noun animacy and human similarity ratings over pairs of subject nouns. However, I also find that while some participants supply a great variety of ratings, many participants supply only a few unique values during the task. This suggests that some individuals are making more fine-grained judgments than others. These differences in response granularity could stem from a variety of sources. However, the offline nature of Experiment 1 does not enable direct examination of the comprehension process, but rather focuses on its end result. In Experiment 2, I present a Speed-Accuracy Tradeoff study that explores the earliest stages of meaning-in-context resolution to better understand the dynamics of the comprehension process itself. In particular, I focus on the timecourse of meaning resolution and the question of whether verbs carry context-independent default interpretations that are activated prior to semantic integration. I find, consistent with what has previously been shown for nouns, that verbs do in fact carry such a default meaning, as can be seen in early false alarms to stimuli such as The dawn broke -- Something shattered. These default meanings appear to reflect the most frequent interpretation of the verb. While these default meanings are likely an emergent effect of repeated exposure to frequent interpretations of a verb, I hypothesize that they additionally support a shallow semantic processing strategy. Recently, a growing body of work has begun to demonstrate that our language comprehension is often less than exhaustive and less than maximally accurate -- people often vary the depth of their processing. In Experiment 3, I explore changes in depth of semantic processing by making an explicit connection to research on human decision making, particularly as regards questions of strategy selection and effort- accuracy tradeoffs. I present a semantic judgment task similar to that used in Experiment 2, but incorporating design principles common in studies on decision making, such as response-contingent financial payoffs and trial-by-trial feedback on response accuracy. I show that participants' preferences for deep and shallow semantic processing strategies are predictably influenced by factors known to affect decision making in other non-linguistic domains. In lower-risk situations, participants are more likely to accept default meanings even when they are not contextually supported, such as responding "True" to stimuli such as The dawn broke -- Something shattered, even without the presence of time pressure. In Experiment 3, I additionally show that participants can adjust not only their processing strategies but also their stimulus acceptance thresholds. Stimuli were normed for truthfulness, i.e. how strongly implied (or entailed) a probe sentence was given its context sentence. Some stimuli in the task posessed an intermediate degree of truthfulness, akin to implicature, as in The log burned -- Something was dangerous (truthfulness 4.55/7). Across 3 conditions, the threshold separating "true" from "false" stimuli was moved such that stimuli such as the example just given would be evaluated differently in different conditions. Participants rapidly learned these threshold placements via feedback, indicating that their perceptions of meaning-in-context, as expressed via the range of possible conclusions that could be drawn from the verb, could vary dynamically in response to situational constraints. This learning was additionally found to occur both faster and more accurately under increased levels of risk. This thesis makes two primary contributions to the literature. First, I present evidence that our knowledge of verb meanings is at least two-layered -- we have access to a very information-rich base of event knowledge, but we also have a more schematic level of representation that is easier to access. Second, I show that these different sources of information enable different semantic processing strategies, and that moreover the choice between these strategies is dependent upon situational characteristics. I additionally argue for the more general relevance of the decision making literature to the study of language processing, and suggest future applications of this approach for work in experimental semantics and pragmatics.