Modeling the Effects of the Local Environment on a Received GNSS Signal

There is an ongoing need in the GNSS community for the development of high-fidelity simulators which generate data that replicates what can truly be expected from a challenging environment such as an urban canyon or an indoor environment. The algorithm developed for use in the research in this dissertation, the Signal Decomposition and Parameterization Algorithm (SDPA), is presented in order to respond to this need. This algorithm is designed to decompose a signal received using a GNSS recording and playback system and output parameters that can be used to reconstruct the effects on the signal of the environment local to the receiver at the time of recording. The SDPA itself is presented and compared with what is believed to be the state-of-the-art in GNSS multipath parameterization, a Space Alternating Generalized Expectation Maximization (SAGE) algorithm. The development and characterization of a stopping criteria that can be used to halt the SDPA when parameterization of salient components within a recorded signal has been completed

Hardware Realization of a Transform Domain Communication System

The purpose of this research was to implement a Transform Domain Communication System (TDCS) in hardware and compare experimental bit error performance with results published in literature. The intent is to demonstrate the effectiveness or ineffectiveness of a TDCS in communicating binary data across a real channel. In this case, an acoustic channel that is laden with narrowband interference was considered. A TDCS user pair was constructed to validate the proposed design using Matlab™ to control a PC sound card. The proposed TDCS design used the Bartlett method of spectrum estimation, the spectral notching algorithm found in TDCS literature, quadrature phase shift keying, and minimum mean square error transverse equalization to mitigate the effects of noise and intersymbol interference. Water-filling was evaluated as an alternative to spectral notching for performing waveform design and is shown to perform equivalently. Validated software was migrated to code suitable for use onboard a Digital Signal Processor Starter Kit (DSK). Two DSK boards were used, one for transmission and reception, and bit error performance results were obtained. Bit error analysis reveals that the TDCS hardware performs approximately the same as literature suggests

Adults with autism overestimate the volatility of the sensory environment.

Insistence on sameness and intolerance of change are among the diagnostic criteria for autism spectrum disorder (ASD), but little research has addressed how people with ASD represent and respond to environmental change. Here, behavioral and pupillometric measurements indicated that adults with ASD are less surprised than neurotypical adults when their expectations are violated, and decreased surprise is predictive of greater symptom severity. A hierarchical Bayesian model of learning suggested that in ASD, a tendency to overlearn about volatility in the face of environmental change drives a corresponding reduction in learning about probabilistically aberrant events, thus putatively rendering these events less surprising. Participant-specific modeled estimates of surprise about environmental conditions were linked to pupil size in the ASD group, thus suggesting heightened noradrenergic responsivity in line with compromised neural gain. This study offers insights into the behavioral, algorithmic and physiological mechanisms underlying responses to environmental volatility in ASD