Retarding Potential Analyzers (RPA) have a rich flight heritage. These instruments are largely popular since a single current-voltage (I-V) profile can provide in-situ measurements of ion temperature, velocity and composition. The estimation of parameters from an RPA I-V curve is affected by grid geometries and non-ideal biasing which have been studied in the past. In this dissertation, we explore the uncertainties associated with estimated ion parameters from an RPA in the presence of instrument noise. Simulated noisy I-V curves representative of those expected from a mid-inclination low Earth orbit are fitted with standard curve fitting techniques to reveal the degree of uncertainty and inter-dependence between expected errors, with varying levels of additive noise. The main motive is to provide experimenters working with RPA data with a measure of error scalable for different geometries. In subsequent work, we develop a statistics based bootstrap technique designed to mitigate the large inter-dependency between spacecraft potential and ion velocity errors, which were seen to be highly correlated when estimated using a standard algorithm. The new algorithm - BATFORD, acronym for "Bootstrap-based Algorithm with Two-stage Fit for Orbital RPA Data analysis" - was applied to a simulated dataset treated with noise from a laboratory calibration based realistic noise model, and also tested on real in-flight data from the C/NOFS mission. BATFORD outperforms a traditional algorithm in simulation and also provides realistic in-situ estimates from a section of a C/NOFS orbit when the satellite passed through a plasma bubble. The low signal-to-noise ratios (SNR) of measured I-Vs in these bubbles make autonomous parameter estimation notoriously difficult. We thus propose a method for robust autonomous analysis of RPA data that is reliable in low SNR environments, and is applicable for all RPA designs. / Doctor of Philosophy / The plasma environment in Earth’s upper atmosphere is dynamic and diverse. Of particular interest is the ionosphere - a region of dense ionized gases that directly affects the variability in weather in space and the communication of radio wave signals across Earth. Retarding potential analyzers (RPA) are instruments that can directly measure the characteristics of this environment in flight. With the growing popularity of small satellites, these probes need to be studied in greater detail to exploit their ability to understand how ions - the positively charged particles- behave in this region. In this dissertation, we aim to understand how the RPA measurements, obtained as current-voltage relationships, are affected by electronic noise. We propose a methodology to understand the associated uncertainties in the estimated parameters through a simulation study. The results show that a statistics based algorithm can help to interpret RPA data in the presence of noise, and can make autonomous, robust and more accurate measurements compared to a traditional non-linear curve-fitting routine. The dissertation presents the challenges in analyzing RPA data that is affected by noise and proposes a new method to better interpret measurements in the ionosphere that can enable further scientific progress in the space physics community.

Baigiamajame magistro darbe nagrinėjamas dviejų vėjo jėgainių parkų keliamas triukšmas. Analizuojami triukšmo susidarymo ypatumai vėjo jėgainių parkų viduje bei sklaida parko išorėje. Vertinamos infragarso bei žemo dažnio garso dažninės charakteristikos vėjo jėgainių parkų aplinkoje. Darbą sudaro 4 skyriai. Pirmajame skyriuje apžvelgiama garso fizikinė prasmė, triukšmo šaltiniai, problema bei keliamo triukšmo poveikis žmonėms. Antrajame skyriuje aprašomi tyrimo objektai bei eksperimentinė vėjo jėgainių keliamo triukšmo tyrimų metodika. Trečiajame skyriuje pateikiami dviejų vėjo jėgainių parkų keliamo triukšmo tyrimų rezultatai bei analizė. Dviejų vėjo jėgainių parko Anužių kaime bei šešių vėjo jėgainių parko „Liepynė“ Kretingos rajone. Ketvirtajame skyriuje pateikiamas vėjo jėgainių parkų keliamo triukšmo modeliavimo rezultatai taikant „CadnaA“ modeliavimo programą. Taip pat pateikiamos bendros išvados, rekomendacijos, literatūros sąrašas ir publikacijų sąrašas šio darbo tema. Darbo apimtis – 103 p. teksto be priedų, 72 iliustr., 5 lent., 84 bibliografiniai šaltiniai. / In this master analyzing of noise dispersion around two wind farms. Analyzing the noise generation and dissemination characteristics of wind farms within and outside the park. Assessed infrasound and low frequency sound frequency response in the places around of wind farms. The master consists of 4 chapters. The first chapter provides an overview of sound physical meaning, sources of noise, the problem and the noise impact to people. The second section describes the objects of research, experimental wind noise research methodology. The third section presents the research results and analysis of two wind parks. Wind farm of two wind turbines in Anužiai village and wind farm of six wind turbines in „Liepynė“ Kretingos district. The fourth section describes the modeling results of wind park using simulation program „CadnaA“ . Also provides an overall conclusion, recommendations, bibliography and list of publications of this master. The volume of master – 103 pages text without attachments, 72 pictures, 5 tables, 84 references.