S. A. K. Leeney

ORCID: 0000-0003-4366-1119
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About
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Research Areas
  • Radio Astronomy Observations and Technology
  • Advanced Wireless Communication Techniques
  • GNSS positioning and interference
  • Astrophysics and Cosmic Phenomena
  • Soil Moisture and Remote Sensing
  • Antenna Design and Optimization
  • Radio Wave Propagation Studies
  • Satellite Communication Systems
  • Millimeter-Wave Propagation and Modeling
  • Precipitation Measurement and Analysis

University of Cambridge
2023-2025

We detail the REACH radiometric system designed to enable measurements of 21-cm neutral hydrogen line. Included is radiometer architecture and end-to-end simulations as well a discussion challenges intrinsic highly-calibratable development. Following this, we share laboratory results based on calculation noise wave parameters utilising an over-constrained least squares approach. For five hours integration custom-made source with comparable impedance that antenna used in field, demonstrate...

10.1007/s10686-024-09975-3 article EN cc-by Experimental Astronomy 2025-01-17

Interfering signals such as radio frequency interference from ubiquitous satellite constellations are becoming an endemic problem in fields involving physical observations of the electromagnetic spectrum. To address this we propose a novel data cleaning methodology. Contamination is simultaneously flagged and managed at likelihood level. It modeled Bayesian fashion through piecewise that constrained by Bernoulli prior distribution. The techniques described paper can be implemented with just...

10.1103/physrevd.108.062006 article EN cc-by Physical review. D/Physical review. D. 2023-09-29

We detail the REACH radiometric system designed to enable measurements of 21-cm neutral hydrogen line. Included is radiometer architecture and end-to-end simulations as well a discussion challenges intrinsic highly-calibratable development. Following this, we share laboratory results based on calculation noise wave parameters utilising an over-constrained least squares approach demonstrating calibration RMSE 80 mK for five hours integration custom-made source with comparable impedance that...

10.48550/arxiv.2307.00099 preprint EN other-oa arXiv (Cornell University) 2023-01-01

Abstract Contamination by radio frequency interference (RFI) is a ubiquitous challenge for astronomy. In particular, transient RFI difficult to detect and avoid, especially in large data sets with many time bins. this work, we present Bayesian methodology time-dependent, anomaly mitigation performed jointly model fitting. The computation correcting anomalies manner time-separated grows proportionally the number of We demonstrate that utilizing likelihood reweighting can allow our method be...

10.1093/rasti/rzae025 article EN cc-by RAS Techniques and Instruments 2024-01-01

Due to the large dynamic ranges involved with separating cosmological 21-cm signal from Cosmic Dawn galactic foregrounds, a well-calibrated instrument is essential avoid biases instrumental systematics. In this paper we present three methods for calibrating global cosmology experiment using noise wave parameter formalisation characterise low amplifier including careful consideration of how calibrator temperature and singularities will bias result. The first method presented in builds upon...

10.48550/arxiv.2412.14023 preprint EN arXiv (Cornell University) 2024-12-18

Interfering signals such as Radio Frequency Interference from ubiquitous satellite constellations are becoming an endemic problem in fields involving physical observations of the electromagnetic spectrum. To address this we propose a novel data cleaning methodology. Contamination is simultaneously flagged and managed at likelihood level. It modeled Bayesian fashion through piecewise that constrained by Bernoulli prior distribution. The techniques described paper can be implemented with just...

10.48550/arxiv.2211.15448 preprint EN other-oa arXiv (Cornell University) 2022-01-01

Contamination by Radio Frequency Interference (RFI) is a ubiquitous challenge for radio astronomy. In particular, transient RFI difficult to detect and avoid, especially in large data sets with many time bins. this work, we present Bayesian methodology time-dependent, anomaly mitigation. general, the computation correcting anomalies time-separated grows proportionally number of We demonstrate that utilising likelihood reweighting can allow our mitigation method be performed close independent...

10.48550/arxiv.2310.02146 preprint EN other-oa arXiv (Cornell University) 2023-01-01
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