Localization and tracking of electronic devices with their unintended emissions

The precise localization and tracking of electronic devices via their unintended emissions has a broad range of commercial and security applications. Active stimulation of the receivers of such devices with a known signal generates very low power unintended emissions. This dissertation presents localization and tracking of multiple devices using both simulation and experimental data in the form of five papers. First the localization of multiple emitting devices through active stimulation under multipath fading with a Smooth MUSIC based scheme in the near field region is presented. Spatial smoothing helps to separate the correlated sources and the multipath fading and results confirm improved accuracy. A cost effective near-field localization method is proposed next to locate multiple correlated unintended emitting devices under colored noise conditions using two well separated antenna arrays since colored noise in the environment degrades the subspace-based localization techniques. Subsequently, in order to track moving sources, a near-field scheme by using array output is introduced to monitor direction of arrival (DOA) and the distance between the antenna array and the moving source. The array output, which is a nonlinear function of DOA and distance information, is employed in the Extended Kalman Filter (EKF). In order to show the near- and far-field effect on estimation accuracy, computer simulation results are included for localization and tracking techniques. Finally, an L-shaped array is constructed and a suite of schemes are introduced for localization and tracking of such devices in the three-dimensional environment. Experimental results for localization and tracking of unintended emissions from single and multiple devices in the near-field environment of an antenna array are demonstrated --Abstract, page iv

Audio Source Positioning Based on Angle of Arrival Measurements

Estimating position is done in various contexts from locating phones with GPS to locating boats using hydrophones. In this thesis we study estimating audio source position based on angle of arrival measurements. Multiple different filters can be used on measured angles of arrival to deduce the position of the source. The filter to be used in this work was chosen to be the particle filter. Even though particle filter is computationally more heavy than many other filters, modern computers can simulate hundreds of particles in a short time without too much of an effort. We introduce the reader to the use of particle filter in positioning, along with theoretical background of it and positioning in a more general sense. The data in this work is recorded in either an anechoic chamber or a room that has no special equipment installed to enhance audio quality in it. The measurements are done with a mobile device with four microphones. Audio source in the anechoic chamber is a loudspeaker playing speech or a person speaking and walking randomly in the room. If the data contains noise, it is played from loudspeakers in the same space as the source is located in. Another type of data handled in this work is measured outside in a racing event where multiple cars passed the measurement device as well as generated data with multiple sources. The data is handled as a mixture between von Mises and uniform distribution. An important parameter of von Mises distribution is a variable called κ, which tells the concentration of the distribution. In this work we show and prove a way to estimate said variable with maximum likelihood method. Additionally, we introduce the reader to mathematical background of particle filter and positioning in more general sense. Results given by the particle filter depend on the chosen value of κ along with chosen q-value, which tells the smoothness of the result, and measurement model. Finally, we present and compare the results obtained by constant velocity and random walk models with several different q-values

Biologically Inspired Sensing and MIMO Radar Array Processing

The contributions of this dissertation are in the fields of biologically inspired sensing and multi-input multi-output: MIMO) radar array processing. In our research on biologically inspired sensing, we focus on the mechanically coupled ears of the female Ormia ochracea. Despite the small distance between its ears, the Ormia has a remarkable localization ability. We statistically analyze the localization accuracy of the Ormia\u27s coupled ears, and illustrate the improvement in the localization performance due to the mechanical coupling. Inspired by the Ormia\u27s ears, we analytically design coupled small-sized antenna arrays with high localization accuracy and radiation performance. Such arrays are essential for sensing systems in military and civil applications, which are confined to small spaces. We quantitatively demonstrate the improvement in the antenna array\u27s radiation and localization performance due to the biologically inspired coupling. On MIMO radar, we first propose a statistical target detection method in the presence of realistic clutter. We use a compound-Gaussian distribution to model the heavy tailed characteristics of sea and foliage clutter. We show that MIMO radars are useful to discriminate a target from clutter using the spatial diversity of the illuminated area, and hence MIMO radar outperforms conventional phased-array radar in terms of target-detection capability. Next, we develop a robust target detector for MIMO radar in the presence of a phase synchronization mismatch between transmitter and receiver pairs. Such mismatch often occurs due to imperfect knowledge of the locations as well as local oscillator characteristics of the antennas, but this fact has been ignored by most researchers. Considering such errors, we demonstrate the degradation in detection performance. Finally, we analyze the sensitivity of MIMO radar target detection to changes in the cross-correlation levels: CCLs) of the received signals. Prior research about MIMO radar assumes orthogonality among the received signals for all delay and Doppler pairs. However, due to the use of antennas which are widely separated in space, it is impossible to maintain this orthogonality in practice. We develop a target-detection method considering the non-orthogonality of the received data. In contrast to the common assumption, we observe that the effect of non-orthogonality is significant on detection performance

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

Sensor array signal processing : two decades later

Caption title.Includes bibliographical references (p. 55-65).Supported by Army Research Office. DAAL03-92-G-115 Supported by the Air Force Office of Scientific Research. F49620-92-J-2002 Supported by the National Science Foundation. MIP-9015281 Supported by the ONR. N00014-91-J-1967 Supported by the AFOSR. F49620-93-1-0102Hamid Krim, Mats Viberg

Lunar gravitational field estimation and the effects of mismodeling upon lunar satellite orbit prediction

Lunar spherical harmonic gravity coefficients are estimated from simulated observations of a near-circular low altitude polar orbiter disturbed by lunar mascons. Lunar gravity sensing missions using earth-based nearside observations with and without satellite-based far-side observations are simulated and least squares maximum likelihood estimates are developed for spherical harmonic expansion fit models. Simulations and parameter estimations are performed by a modified version of the Smithsonian Astrophysical Observatory's Planetary Ephemeris Program. Two different lunar spacecraft mission phases are simulated to evaluate the estimated fit models. Results for predicting state covariances one orbit ahead are presented along with the state errors resulting from the mismodeled gravity field. The position errors from planning a lunar landing maneuver with a mismodeled gravity field are also presented. These simulations clearly demonstrate the need to include observations of satellite motion over the far side in estimating the lunar gravity field. The simulations also illustrate that the eighth degree and order expansions used in the simulated fits were unable to adequately model lunar mascons

Pattern-theoretic foundations of automatic target recognition in clutter

Issued as final reportAir Force Office of Scientific Research (U.S.

Long Span Bridges: Enhanced data fusion of GPS displacement and deck accelerations

This is the author accepted manuscript. The final version is available from Elsevier via the DOI in this record.Displacement data under operational loads are an important aid for the estimation of structural performance, but accurate measurement of structural displacement remains as a challenging task, especially for long-span bridges. The global positioning system (GPS) is the common choice for long-span bridge displacement monitoring but the measurement accuracy is not satisfactory. The purpose of this study is to improve the GPS accuracy using a practical data fusion method. Although the main algorithms of data fusion method based on multi-rate Kalman filter are already reported, the detail about how to select the noise parameters required for Kalman filter is not provided. This paper demonstrates that maximum likelihood estimation (MLE) can be used to determine the necessary noise parameters. The proposed approach was validated on numerical and field data, the latter from a single-day displacement monitoring campaign on the Humber Bridge in the UK. The direct measurement by GPS was merged with the collocated acceleration data and the resulting displacement signal was evaluated by comparing it to the displacement signal from an independent vision-based system. Through the comparison, it is shown that MLE enhanced data fusion is practical to improve the GPS measurement accuracy and to widen the frequency bandwidth. The MLE provides an estimation about the GPS noise (assumed as zero-mean Gaussian process) with the standard deviation varying from 6 mm to 16 mm in the test day. The normalised root mean square deviation of GPS measurement compared with the vision-based measurement was decreased from 3.17% to 2.37% after applying the data fusion.The field test was possible via permission of Humber Bridge Board and was assisted by James Bassitt from University of Exeter and Mungo Morgan from Imetrum Ltd. The Humber Bridge monitoring system was installed using funding from EPSRC grant EP/F035403/1. Finally the authors would like to thank the three anonymous reviewers for their constructive comments