Matthew Gilliam

Friedreich ataxia (FRDA) is typically caused by homozygosity for an expanded GAA triplet-repeat in intron 1 of the FXN gene, which results in transcriptional deficiency via epigenetic silencing. Most patients are homozygous for alleles containing > 500 triplets, but a subset (~20%) have at least one expanded allele with < 500 triplets and a distinctly milder phenotype. We show that in FRDA DNA methylation spreads upstream from the expanded repeat, further than previously recognized, and establishes an FRDA-specific region of hypermethylation in intron 1 (~90% in FRDA versus < 10% in non-FRDA) as a novel epigenetic signature. The hypermethylation of this differentially methylated region (FRDA-DMR) was observed in a variety of patient-derived cells; it significantly correlated with FXN transcriptional deficiency and age of onset, and it reverted to the non-disease state in isogenically corrected induced pluripotent stem cell (iPSC)-derived neurons. Bisulfite deep sequencing of the FRDA-DMR in peripheral blood mononuclear cells from 73 FRDA patients revealed considerable intra-individual epiallelic variability, including fully methylated, partially methylated, and unmethylated epialleles. Although unmethylated epialleles were rare (median = 0.33%) in typical patients homozygous for long GAA alleles with > 500 triplets, a significantly higher prevalence of unmethylated epialleles (median = 9.8%) was observed in patients with at least one allele containing < 500 triplets, less severe FXN deficiency (>20%) and later onset (>15 years). The higher prevalence in mild FRDA of somatic FXN epialleles devoid of DNA methylation is consistent with variegated epigenetic silencing mediated by expanded triplet-repeats. The proportion of unsilenced somatic FXN genes is an unrecognized phenotypic determinant in FRDA and has implications for the deployment of effective therapies.

Using ultra-wideband (UWB) impulse radar for detecting and tracking fast-moving small targets over the ocean surface has been considered before with limited applications. The challenges of deploying such radar sensors on small, unmanned marine platforms are addressed in this study. The first challenge is the stringent size and weight requirement to allow a tracking radar sensor to be fitted into the payload of a small unmanned surface vehicle (USV). For the first time, we implemented a design that is based on a single chip UWB radar sensor operating at X-band, which effectively achieves the size and weight requirement for a small USV payload. The second challenge is range extension and range ambiguity resolution. With the UWB radar operating various high-PRF modes, we developed a novel approach that stitches together range profiles from multiple PRFs, to extend the effective non-ambiguous range at the cost of scan speed. The third challenge is developing a lowcost, ultra-wideband planar antenna and front-end, which is also part of the USV payload and needs to be able to perform either sector scanning, or even electronic scanning, with a very low profile. We have successfully designed and implemented one such antenna using a dipole array design. By integrating the solutions into a complete system, we have performed a series of lab and outdoor tests of the UWB radar sensor and obtained some promising target data. Simulations are also being developed for testing the potential target signatures and tracking effectiveness of moving targets over ocean surface clutter environments.

The background of this thesis is related to the enhancement and optimization of the Pulsed-Doppler Radar sensor for the need of Detect and Avoid (DAA), or Sense and Avoid (SAA), for both weather and air-traffic (collision aircraft) detection and monitoring. Such radars are used in both manned and unmanned aircraft for the situation awareness of pilot navigation operations. The particular focus of this study is to develop a simulation model that is based on MATLAB's phased array toolbox and use that simulation model to predict the performance of an end-to-end radar signal processing chain for all-weather, multi-mission DAA. To achieve this goal, we developed an airborne system model based on MATLAB toolboxes, NASA’s airborne radar flight test data, and NEXRAD radar data. The measured data from airborne and ground-based radars are used as the “truth field” for the weather. During the modeling and verification process, we primarily investigated the impact of ground or surface clutters on the radar outputs and results, which include the testing of the constant-gamma model using actual measured radar data and improved system and sensor modeling based on the clutter geometry. Evaluation of various moving target indication (MTI) techniques were tested with the simulation model.

During the design and development of multi-functional airborne hazard detection and avoidance radars, as well as radar navigation functions, we usually need a precise and reliable simulation evaluation. However, the existing solutions are usually highly proprietary for specific developers. In previous studies, we developed PASIM as one possible framework to unify the multi-functional radar developments. In this study, more novel enhancements and applications of PASIM are introduced based on the needs of communities, and the software tools are updated specifically for airborne radars. These updates include: (1) Enhancement and evaluation of airborne radar ground clutter modules, which supports different terrain or water surface types. (2) Combination of measured data as part of simulations. In this case, we used NASA’s pulsed-Doppler weather radar data as “meta-truth” and created simulation examples of a new generation of Sense and Avoid (SAA) simulation operation based on them. (3) Incorporation of realistic target impulse responses, RF channel modeling and processing chain. (4) Incorporation of automatic radar mode optimization, ground clutter mitigation solution and algorithms. (5) Enhanced data quality evaluation for both air-target tracking and weather surveillance. A generic airborne pulsed-Doppler radar with reasonable system parameters are used for our studies as an example and the design/evaluation procedure and results are presented.

Data processing, calibration, and quality evaluation are critical elements for successful airborne radar missions. For a downward-looking airborne radar, the usage of ground as a calibration target has been discussed before but not completely analyzed for precipitation measurement missions at Ka-band. In this study, the team performed data analysis and calibration modeling for the Millimeter-Wave Airborne Radar for Learning and Education (MARBLE), which was developed as a recent undergraduate team effort beginning in 2016. Millimeter-wave radar missions for MARBLE include precipitation measurement and terrain remote sensing through vertical profiling. To achieve these mission goals, the team used multiple time- and spectrum-domain processing methods on the ground return data collected from 2018 NASA ER- 2 engineering calibration flights. Some of the algorithms include spectrum analysis with various CPI arrangement and multi-lag processing to enhance signal-to-noise ratio (SNR). Doppler calibration based on aircraft platform motion and orientation is also considered. Useful results are obtained from ground power calibration as well as Doppler estimation. In addition, multiple ground calibration tests with actual weather results are incorporated to supplement the airborne measurements after some hardware checking and improvement. Based on the reasonable outcomes from the calibration measurements, a new high-altitude flight campaign for precipitation measurement is being planned for 2020.