ITC/USA 2008 Conference Proceedings / The Forty-Fourth Annual International Telemetering Conference and Technical Exhibition / October 27-30, 2008 / Town and Country Resort & Convention Center, San Diego, California / A method for combining telemetry data and quantifying the resulting coding gain for a ballistic missile test flight is presented. Data received from five ground stations in 54 data files with 18 million intermittent frames is combined, to create a single file with 1.5 million continuous frames. Coding gain provided by data combining is as high as 30 dB, with a useful improvement of 5 dB at boost and terminal stages. With frame reconstruction techniques, erroneous words in a frame are reduced from 2.1% to 0.12 %.

ITC/USA 2015 Conference Proceedings / The Fifty-First Annual International Telemetering Conference and Technical Exhibition / October 26-29, 2015 / Bally's Hotel & Convention Center, Las Vegas, NV / There is great potential in using Best Source Selectors (BSS) to improve link availability in aeronautical telemetry applications. While the general notion that diverse data sources can be used to construct a consolidated stream of "better" data is well founded, there is no standardized means of determining the quality of the data streams being merged together. Absent this uniform quality data, the BSS has no analytically sound way of knowing which streams are better, or best. This problem is further exacerbated when one imagines that multiple vendors are developing data quality estimation schemes, with no standard definition of how to measure data quality. In this paper, we present measured performance for a specific Data Quality Metric (DQM) implementation, demonstrating that the signals present in the demodulator can be used to quickly and accurately measure the data quality, and we propose test methods for calibrating DQM over a wide variety of channel impairments. We also propose an efficient means of encapsulating this DQM information with the data, to simplify processing by the BSS. This work leads toward a potential standardization that would allow data quality estimators and best source selectors from multiple vendors to interoperate.

This dissertation presents a Bayesian hierarchical model to combine two-resolution metrology data for inspecting the geometric quality of manufactured parts. The high- resolution data points are scarce, and thus scatter over the surface being measured, while the low-resolution data are pervasive, but less accurate or less precise. Combining the two datasets could supposedly make a better prediction of the geometric surface of a manufactured part than using a single dataset. One challenge in combining the metrology datasets is the misalignment which exists between the low- and high-resolution data points. This dissertation attempts to provide a Bayesian hierarchical model that can handle such misaligned datasets, and includes the following components: (a) a Gaussian process for modeling metrology data at the low-resolution level; (b) a heuristic matching and alignment method that produces a pool of candidate matches and transformations between the two datasets; (c) a linkage model, conditioned on a given match and its associated transformation, that connects a high-resolution data point to a set of low-resolution data points in its neighborhood and makes a combined prediction; and finally (d) Bayesian model averaging of the predictive models in (c) over the pool of candidate matches found in (b). This Bayesian model averaging procedure assigns weights to different matches according to how much they support the observed data, and then produces the final combined prediction of the surface based on the data of both resolutions. The proposed method improves upon the methods of using a single dataset as well as a combined prediction without addressing the misalignment problem. This dissertation demonstrates the improvements over alternative methods using both simulated data and the datasets from a milled sine-wave part, measured by two coordinate measuring machines of different resolutions, respectively.