Interferometric Synthetic Aperture Sonar Signal Processing for Autonomous Underwater Vehicles Operating Shallow Water

The goal of the research was to develop best practices for image signal processing method for InSAS systems for bathymetric height determination. Improvements over existing techniques comes from the fusion of Chirp-Scaling a phase preserving beamforming techniques to form a SAS image, an interferometric Vernier method to unwrap the phase; and confirming the direction of arrival with the MUltiple SIgnal Channel (MUSIC) estimation technique. The fusion of Chirp-Scaling, Vernier, and MUSIC lead to the stability in the bathymetric height measurement, and improvements in resolution. This method is computationally faster, and used less memory then existing techniques

Processing of Interferometric Data

In this thesis, fast and highly accurate interferometric metrology systems for both smooth and rough surfaces are presented. First, high-speed algorithms for white-light interferometry (WLI) and line scanning WLI are developed and their performance is compared. For large height differences, multiple wavelength interferometry is significantly faster, though, as in this approach the number of frames required for a surface estimate does not increase with surface height range. A system based on a tunable diode laser is discussed in detail, and new sampling schemes and estimation algorithms for the device are derived. An approximation to the theoretically optimal sampling pattern is given and a corresponding fast estimation algorithm is presented. As a building block for that algorithm, accurate and fast phase and frequency estimation from a low number of samples is discussed, and a new approach based on an interpolated FFT is presented. The influence of laser speckle on rough surfaces is investigated. A robust, adaptive filtering algorithm is developed. It takes spatial relationships into account — without imposing strong smoothness constraints — and uses additional knowledge on the signal from the raw data to improve performance significantly, especially on rough surfaces

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

Measurement-Based Automatic Parameterization of a Virtual Acoustic Room Model

Modernien auralisaatiotekniikoiden ansiosta kuulokkeilla voidaan tuottaa kuuntelukokemus, joka muistuttaa useimpien äänitteiden tuotannossa oletettua kaiutinkuuntelua. Huoneakustinen mallinnus on tärkeä osa toimivaa auralisaatiojärjestelmää. Huonemallinnuksen parametrien määrittäminen vaatii kuitenkin ammattitaitoa ja aikaa. Tässä työssä kehitetään järjestelmä parametrien automaattiseksi määrittämiseksi huoneakustisten mittausten perusteella. Parametrisaatio perustuu mikrofoniryhmällä mitattuihin huoneen impulssivasteisiin ja voidaan jakaa kahteen osaan: suoran äänen ja aikaisten heijastusten analyysiin sekä jälkikaiunnan analyysiin. Suorat äänet erotellaan impulssivasteista erilaisia signaalinkäsittelytekniikoita käyttäen ja niitä hyödynnetään heijastuksia etsivässä algoritmissa. Äänilähteet ja heijastuksia vastaavat kuvalähteet paikannetaan saapumisaikaeroon perustuvalla paikannusmenetelmällä ja taajuusriippuvat etenemistien vaikutukset arvioidaan kuvalähdemallissa käyttöä varten. Auralisaation jälkikaiunta on toteutettu takaisinkytkevällä viiveverkostomallilla. Sen parametrisointi vaatii taajuusriippuvan jälkikaiunta-ajan ja jälkikaiunnan taajuusvasteen määrittämistä. Normalisoitua kaikutiheyttä käytetään jälkikaiunnan alkamisajan löytämiseen mittauksista ja simuloidun jälkikaiunnan alkamisajan asettamiseen. Jälkikaiunta-aikojen määrittämisessä hyödynnetään energy decay relief -metodia. Kuuntelukokeiden perusteella automaattinen parametrisaatiojärjestelmä tuottaa parempia tuloksia kuin parametrien asettaminen manuaalisesti huoneen summittaisten geometriatietojen pohjalta. Järjestelmässä on ongelmia erityisesti jälkikaiunnan ekvalisoinnissa, mutta käytettyihin suhteellisen yksinkertaisiin tekniikoihin nähden järjestelmä toimii hyvin.Modern auralization techniques enable making the headphone listening experience similar to the experience of listening with loudspeakers, which is the reproduction method most content is made to be listened with. Room acoustic modeling is an essential part of a plausible auralization system. Specifying the parameters for room modeling requires expertise and time. In this thesis, a system is developed for automatic analysis of the parameters from room acoustic measurements. The parameterization is based on room impulse responses measured with a microphone array and can be divided into two parts: the analysis of the direct sound and early reflections, and the analysis of the late reverberation. The direct sounds are separated from the impulse responses using various signal processing techniques and used in the matching pursuit algorithm to find the reflections in the impulse responses. The sound sources and their reflection images are localized using time difference of arrival -based localization and frequency-dependent propagation path effects are estimated for use in an image source model. The late reverberation of the auralization is implemented using a feedback delay network. Its parameterization requires the analysis of the frequency-dependent reverberation time and frequency response of the late reverberation. Normalized echo density is used to determine the beginning of the late reverberation in the measurements and to set the starting point of the modeled late field. The reverberation times are analyzed using the energy decay relief. A formal listening test shows that the automatic parameterization system outperforms parameters set manually based on approximate geometrical data. Problems remain especially in the precision of the late reverberation equalization but the system works well considering the relative simplicity of the processing methods used