Improved SuperDARN radar signal processing: A first principles statistical approach for reliable measurement uncertainties and enhanced data products

Ground-based radar systems are the best way to continuously monitor medium-to-large-scale features of the near-Earth space environment on a global scale. The Super Dual Auroral Radar Network (SuperDARN) radars are used to image the high-latitude ionospheric plasma circulation, which is produced by magnetosphere-ionosphere coupling processes generated by the interaction of both the solar and terrestrial magnetic fields. While investigating ways to expand the usable data products of SuperDARN to include electron density inferred using a multiple-frequency technique, it was determined that SuperDARN error estimates were lacking sufficient rigour. The method to calculate SuperDARN parameters was developed approximately 25 years ago when available computing resources were significantly less powerful, which required a number of simplifications to ensure both valid data and reasonable processing time. This resulted in very conservative criteria being applied to ensure valid data, but at the expense of both rigorous error analysis and the elimination of some otherwise valid data. With access to modern computing resources, the SuperDARN data processing methodology can be modernized to provide proper error estimates for the SuperDARN parameters (power, drift velocity, width). This research has resulted in 3 publications, which are presented here as Chapters 5, 6, and 7. The error analysis started with a first principles analysis of the self-clutter generated by the multiple-pulse technique that is used to probe the ionosphere (Chapter 5). Next, the statistical properties of voltage fluctuations as measured by SuperDARN were studied and the variance of these measurements were derived (Chapter 6). Finally, the statistical error analysis was propagated to the standard SuperDARN data products using a new First-Principles Fitting Methodology (Chapter 7). These results can be applied to all previously recorded SuperDARN data and have shown a practical increase in data of >50%. This has significant impact on the SuperDARN and space science communities with respect to, for example, global convection maps and their use in global modelling efforts. These results also enable quantitative experiment design facilitating research into using SuperDARN to provide electron density measurements, with a preliminary investigation using the new SuperDARN fitting methodology presented in Chapter 8

Scattering images from autocorrelation functions of P-wave seismic velocity images: the case of Tenerife Island (Canary Islands, Spain)

We present a P-wave scattering image of the volcanic structures under Tenerife Island using the autocorrelation functions of P-wave vertical velocity fluctuations. We have applied cluster analysis to total quality factor attenuation (Q inv t) and scattering quality factor attenuation (Q inv PSc) images to interpret the structures in terms of intrinsic and scattering attenuation variations on a 2D plane, corresponding to a depth of 2000 m, and check the robustness of the scattering imaging. The results show that scattering patterns are similar to total attenuation patterns in the South of the island. There are two main areas where patterns differ: at Ca\~nadas-Teide-Pico Viejo Complex high total attenuation and average-to-low scattering values are observed. We interpret the difference as induced by intrinsic attenuation. In the Santiago Ridge Zone (SRZ) region, high scattering values correspond to average total attenuation. In our interpretation, the anomaly is induced by an extended scatterer, geometrically related to the surficial traces of Garachico and El Chinyero historical eruptions and the area of highest seismic activity during the 2004-2008 seismic crises.Comment: Final reviewed version of the published pape

Space-time sampling strategies for electronically steerable incoherent scatter radar

Incoherent scatter radar (ISR) systems allow researchers to peer into the ionosphere via remote sensing of intrinsic plasma parameters. ISR sensors have been used since the 1950s and until the past decade were mainly equipped with a single mechanically steerable antenna. As such, the ability to develop a two or three dimensional picture of the plasma parameters in the ionosphere has been constrained by the relatively slow mechanical steering of the antennas. A newer class of systems using electronically steerable array (ESA) antennas have broken the chains of this constraint, allowing researchers to create 3-D reconstructions of plasma parameters. There have been many studies associated with reconstructing 3-D fields of plasma parameters, but there has not been a systematic analysis into the sampling issues that arise. Also, there has not been a systematic study as to how to reconstruct these plasma parameters in an optimum sense as opposed to just using different forms of interpolation. The research presented here forms a framework that scientists and engineers can use to plan experiments with ESA ISR capabilities and to better analyze the resulting data. This framework attacks the problem of space-time sampling by ESA ISR systems from the point of view of signal processing, simulation and inverse theoretic image reconstruction. We first describe a physics based model of incoherent scatter from the ionospheric plasma, along with processing methods needed to create the plasma parameter measurements. Our approach leads to development of the space-time ambiguity function, forming a theoretical foundation of the forward model for ISR. This forward model is novel in that it takes into account the shape of the antenna beam and scanning method along with integration time to develop the proper statistics for a desired measurement precision. Once the forward model is developed, we present the simulation method behind the Simulator for ISR (SimISR). SimISR uses input plasma parameters over space and time and creates complex voltage samples in a form similar to that produced by a real ISR system. SimISR allows researchers to evaluate different experiment configurations in order to efficiently and accurately sample specific phenomena. We present example simulations using input conditions derived from a multi-fluid ionosphere model and reconstructions using standard interpolation techniques. Lastly, methods are presented to invert the space-time ambiguity function using techniques from image reconstruction literature. These methods are tested using SimISR to quantify accurate plasma parameter reconstruction over a simulated ionospheric region

Scattering images from autocorrelation functions of P-wave seismic velocity images : the case of Tenerife Island (Canary Islands, Spain)

We thank Edoardo Del Pezzo for the valuable idea of this paper and suggestions regarding the methodology. J. Prudencio is partially supported by NSF1521855 Hazard SEES project. This paper has been partially supported by the Spanish project KNOWAVES (TEC2015-68752-R (MINECO/FEDER)), the European project MED-SUV funded by the European Union’s Seventh Framework Program for research, technological development and demonstration under Grant Agreement No 308665, and by the Regional project ‘Grupo de Investigación en Geofísica y Sismología de la Junta de Andalucía, RNM104’.Peer reviewedPostprin

Developing A System For Blind Acoustic Source Localization And Separation

This dissertation presents innovate methodologies for locating, extracting, and separating multiple incoherent sound sources in three-dimensional (3D) space; and applications of the time reversal (TR) algorithm to pinpoint the hyper active neural activities inside the brain auditory structure that are correlated to the tinnitus pathology. Specifically, an acoustic modeling based method is developed for locating arbitrary and incoherent sound sources in 3D space in real time by using a minimal number of microphones, and the Point Source Separation (PSS) method is developed for extracting target signals from directly measured mixed signals. Combining these two approaches leads to a novel technology known as Blind Sources Localization and Separation (BSLS) that enables one to locate multiple incoherent sound signals in 3D space and separate original individual sources simultaneously, based on the directly measured mixed signals. These technologies have been validated through numerical simulations and experiments conducted in various non-ideal environments where there are non-negligible, unspecified sound reflections and reverberation as well as interferences from random background noise. Another innovation presented in this dissertation is concerned with applications of the TR algorithm to pinpoint the exact locations of hyper-active neurons in the brain auditory structure that are directly correlated to the tinnitus perception. Benchmark tests conducted on normal rats have confirmed the localization results provided by the TR algorithm. Results demonstrate that the spatial resolution of this source localization can be as high as the micrometer level. This high precision localization may lead to a paradigm shift in tinnitus diagnosis, which may in turn produce a more cost-effective treatment for tinnitus than any of the existing ones

Middle Atmosphere Program. Handbook for MAP. Volume 30: International School on Atmospheric Radar

Broad, tutorial coverage is given to the technical and scientific aspects of mesosphere stratosphere troposphere (MST) meteorological radar systems. Control issues, signal processing, atmospheric waves, the historical aspects of radar atmospheric dynamics, incoherent scatter radars, radar echoes, radar targets, and gravity waves are among the topics covered

Ray tracing applications for high-frequency radar: characterizing artificial layers and background density perturbations in the ionosphere

Thesis (M.S.) University of Alaska Fairbanks, 2012In this thesis a numerical method of calculating ground-scattered power from the results of a ray tracing analysis is presented. The method is based on a conservation of energy approach and offers advantages over an alternative method derived from the radar equation. The improved numerical method is used to investigate two different physical phenomena by comparison with measured ground-scattered power observed by a high-frequency (HF) radar located in Kodiak, AK that is part of the Super Dual Auroral Radar Network (SuperDARN). First, the effects of artificial electron density layers on observed ground scatter is studied through a comparison of simulated and measured power profiles. The results demonstrate that the location and spatial dimensions of artificial layers may be estimated by a comparison of the location and amplitude of simulated and measured power enhancements. Second, a Monte-Carlo simulation method is used to characterize the temporal distribution of ground-scattered power. Random processes including background electron density perturbations, polarization, noise, and sample correlation are modeled in simulation and used to estimate statistical moment profiles. The simulated statistical moment profiles are compared to measured profiles as a means of model verification and to roughly approximate background electron density perturbations in the ionosphere