Improving surface current resolution using direction finding algorithms for multiantenna high-frequency radars

Author Posting. © American Meteorological Society, 2019. This article is posted here by permission of American Meteorological Society for personal use, not for redistribution. The definitive version was published in Journal of the Atmospheric and Oceanic Technology 36(10), (2019): 1997-2014, doi: 10.1175/JTECH-D-19-0029.1.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.This analysis was supported by NSF Grants OCE-1657896 and OCE-1736930 to Kirincich, OCE-1658475 to Emery and Washburn and OCE-1736709 to Flament. Flament is also supported by NOAA’s Integrated Ocean Observing System through Award NA11NOS0120039. The authors thank Lindsey Benjamin, Alma Castillo, Ken Constantine, Benedicte Dousset, Ian Fernandez, Mael Flament, Dave Harris, Garrett Hebert, Ben Hodges, Victoria Futch, Matt Guanci, and Philip Moravcik for assistance in building, deploying, and operating the radars.2020-04-1

Generalized DOA and Source Number Estimation Techniques for Acoustics and Radar

The purpose of this thesis is to emphasize the lacking areas in the field of direction of arrival estimation and to propose building blocks for continued solution development in the area. A review of current methods are discussed and their pitfalls are emphasized. DOA estimators are compared to each other for usage on a conformal microphone array which receives impulsive, wideband signals. Further, many DOA estimators rely on the number of source signals prior to DOA estimation. Though techniques exist to achieve this, they lack robustness to estimate for certain signal types, particularly in the case where multiple radar targets exist in the same range bin. A deep neural network approach is proposed and evaluated for this particular case. The studies detailed in this thesis are specific to acoustic and radar applications for DOA estimation

Study and applications of retrodirective and self-adaptive electromagnetic wave controls to a Mars probe Quarterly report, 1 Oct. - 31 Dec. 1965

Design feasibility and applications of adaptive antenna circuits for deep space communication - antenna concepts, environmental effects, and phase lock loops and adaptive circuitr

Neural Networks for improved signal source enumeration and localization with unsteered antenna arrays

Direction of Arrival estimation using unsteered antenna arrays, unlike mechanically scanned or phased arrays, requires complex algorithms which perform poorly with small aperture arrays or without a large number of observations, or snapshots. In general, these algorithms compute a sample covriance matrix to obtain the direction of arrival and some require a prior estimate of the number of signal sources. Herein, artificial neural network architectures are proposed which demonstrate improved estimation of the number of signal sources, the true signal covariance matrix, and the direction of arrival. The proposed number of source estimation network demonstrates robust performance in the case of coherent signals where conventional methods fail. For covariance matrix estimation, four different network architectures are assessed and the best performing architecture achieves a 20 times improvement in performance over the sample covariance matrix. Additionally, this network can achieve comparable performance to the sample covariance matrix with 1/8-th the amount of snapshots. For direction of arrival estimation, preliminary results are provided comparing six architectures which all demonstrate high levels of accuracy and demonstrate the benefits of progressively training artificial neural networks by training on a sequence of sub- problems and extending to the network to encapsulate the entire process

Experimental L-band SST satellite communications/surveillance terminal study. Volume 4 - Aircraft antenna studies

Antenna requirements for supersonic transport satellite communications syste

Study and applications of retrodirective and self adaptive electromagnetic-wave phase controls to a Mars probe

Computer analyses of retrodirective, and self adaptive antenna phase control techniques for Mars prob

Abstracts on Radio Direction Finding (1899 - 1995)

The files on this record represent the various databases that originally composed the CD-ROM issue of "Abstracts on Radio Direction Finding" database, which is now part of the Dudley Knox Library's Abstracts and Selected Full Text Documents on Radio Direction Finding (1899 - 1995) Collection. (See Calhoun record https://calhoun.nps.edu/handle/10945/57364 for further information on this collection and the bibliography). Due to issues of technological obsolescence preventing current and future audiences from accessing the bibliography, DKL exported and converted into the three files on this record the various databases contained in the CD-ROM. The contents of these files are: 1) RDFA_CompleteBibliography_xls.zip [RDFA_CompleteBibliography.xls: Metadata for the complete bibliography, in Excel 97-2003 Workbook format; RDFA_Glossary.xls: Glossary of terms, in Excel 97-2003 Workbookformat; RDFA_Biographies.xls: Biographies of leading figures, in Excel 97-2003 Workbook format]; 2) RDFA_CompleteBibliography_csv.zip [RDFA_CompleteBibliography.TXT: Metadata for the complete bibliography, in CSV format; RDFA_Glossary.TXT: Glossary of terms, in CSV format; RDFA_Biographies.TXT: Biographies of leading figures, in CSV format]; 3) RDFA_CompleteBibliography.pdf: A human readable display of the bibliographic data, as a means of double-checking any possible deviations due to conversion

Rotary-motion-extended Array Synthesis (R-MXAS)

R-MXAS is a revolutionary aerospace architecture for realizing a synthetic aperture imaging radiometer (SAIR) with dramatically lower SWaP than existing state-of-the-art (SOTA) methods. The space-based component of the RMXAS system (Figure 1) is a single platform comprising a 1-D sparse / decimated antenna array on a rigid tether (deployed parallel to the horizon) and one or more additional tethered antennas that rotate in a plane orthogonal to the 1-D array.The processing that correlates the data from these two antenna systems and performs image reconstruction has both space-based and ground-based components. The processing exploits the interferometric baselines formed between the rotating tethered antenna at radius R and each of the antennas of the 1-D array on the rigid tether

Holographic MIMO Communications exploiting the Orbital Angular Momentum

This study delves into the potential of harnessing the orbital angular momentum (OAM) property of electromagnetic waves in near-field and line-of-sight scenarios by utilizing large intelligent surfaces, in the context of holographic multiple-input multiple-output (MIMO) communications. The paper starts by characterizing OAM-based communications and investigating the connection between OAM-carrying waves and optimum communication modes recently analyzed for communicating with smart surfaces. Subsequently, it proposes implementable strategies for generating and detecting OAM-based communication signals using intelligent surfaces and optimization methods that leverage focusing techniques. Then, the performance of these strategies is quantitatively evaluated through simulations. The numerical results show that OAM waves while constituting a viable and more practical alternative to optimum communication modes are sub-optimal in terms of achievable capacity.Comment: 34 pages, 9 figures, 2 tables. Part of this article was presented at IEEE GLOBECOM 202