Emery
Brian
Emery
Brian
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ArticleDirection finding and likelihood ratio detection for oceanographic HF radars(American Meteorological Society, 2022-02-01) Emery, Brian ; Kirincich, Anthony R. ; Washburn, LibePrevious work with simulations of oceanographic high-frequency (HF) radars has identified possible improvements when using maximum likelihood estimation (MLE) for direction of arrival; however, methods for determining the number of emitters (here defined as spatially distinct patches of the ocean surface) have not realized these improvements. Here we describe and evaluate the use of the likelihood ratio (LR) for emitter detection, demonstrating its application to oceanographic HF radar data. The combined detection–estimation methods MLE-LR are compared with multiple signal classification method (MUSIC) and MUSIC parameters for SeaSonde HF radars, along with a method developed for 8-channel systems known as MUSIC-Highest. Results show that the use of MLE-LR produces similar accuracy, in terms of the RMS difference and correlation coefficients squared, as previous methods. We demonstrate that improved accuracy can be obtained for both methods, at the cost of fewer velocity observations and decreased spatial coverage. For SeaSondes, accuracy improvements are obtained with less commonly used parameter sets. The MLE-LR is shown to be able to resolve simultaneous closely spaced emitters, which has the potential to improve observations obtained by HF radars operating in complex current environments.
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ArticleImproving surface current resolution using direction finding algorithms for multiantenna high-frequency radars(American Meteorological Society, 2019-10-11) Kirincich, Anthony R. ; Emery, Brian ; Washburn, Libe ; Flament, Pierre J.While land-based high-frequency (HF) radars are the only instruments capable of resolving both the temporal and spatial variability of surface currents in the coastal ocean, recent high-resolution views suggest that the coastal ocean is more complex than presently deployed radar systems are able to reveal. This work uses a hybrid system, having elements of both phased arrays and direction finding radars, to improve the azimuthal resolution of HF radars. Data from two radars deployed along the U.S. East Coast and configured as 8-antenna grid arrays were used to evaluate potential direction finding and signal, or emitter, detection methods. Direction finding methods such as maximum likelihood estimation generally performed better than the well-known multiple signal classification (MUSIC) method given identical emitter detection methods. However, accurately estimating the number of emitters present in HF radar observations is a challenge. As MUSIC’s direction-of-arrival (DOA) function permits simple empirical tests that dramatically aid the detection process, MUSIC was found to be the superior method in this study. The 8-antenna arrays were able to provide more accurate estimates of MUSIC’s noise subspace than typical 3-antenna systems, eliminating the need for a series of empirical parameters to control MUSIC’s performance. Code developed for this research has been made available in an online repository.
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Working PaperHigh Frequency Radar Wind Turbine Interference Community Working Group Report(Woods Hole Oceanographic Institution, 2019-06) Kirincich, Anthony R. ; Cahl, Douglas ; Emery, Brian ; Kosro, Mike ; Roarty, Hugh ; Trockel, Dale ; Washburn, Libe ; Whelan, ChadLand-based High Frequency (HF) Radars provide critically important observations of the coastal ocean that will be adversely affected by the spinning blades of utility-scale wind turbines. Pathways to mitigate the interference of turbines on HF radar observations exist for small number of turbines; however, a greatly increased pace of research is required to understand how to minimize the complex interference patterns that will be caused by the large arrays of turbines planned for the U.S. outer continental shelf. To support the U.S.’s operational and scientific needs, HF radars must be able to collect high-quality measurements of the ocean’s surface inand around areas with significant numbers of wind turbines. This is a solvable problem, but given the rapid pace of wind energy development, immediate action is needed to ensure that HF radar wind turbine interference mitigation efforts keep pace with the planned build out of turbines.
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ArticleRevisiting HF ground wave propagation losses over the ocean: a comparison of long‐term observations and models(American Geophysical Union, 2023-03-31) Kirincich, Anthony ; Emery, BrianUnderstanding variations in the received power levels for land‐based high frequency radar (HFR) systems is critical to advancing radar‐based estimates of winds and waves. We use a long‐term record of one‐way HFR power observations to explore the key factors controlling propagation losses over the ocean. Observed propagation loss was quantified using an 8‐month record of radio frequency power from a shore‐based transmitter, received at two locations: an offshore tower and a nearby island. Observations were compared to environmental factors such as wind speed and air temperature as well as models of path loss incorporating smooth and rough surface impedances and varying atmospheric properties. Significant differences in the observations at the two sites existed. One‐way path loss variations at the tower, a wavelength above mean sea level, were closely related to atmospheric forcing, while variations at the distant island site were dominated by wind‐driven surface gravity wave variability. Seasonal variability in ocean conductivity had no significant effect on over‐ocean path losses. Simplistic analytical models of path loss were found to have more skill than either ground wave propagation models or more complex numerical models of field strength in matching the observations, due in part to under‐observation of the atmosphere but also the differences in rough surface impedance between models of ocean waves.