No / In this work we present the angle of arrival estimation techniques and their comparison at different values of SNR using a 5 element UCA. The techniques that have been considered include phase interferometry, Multiple Signal Classification and covariance. The results show that for very low values of SNR the performance of the covariance matrix based algorithm is the best but for slightly higher values of SNR, MUSIC algorithm outperforms covariance.

ITC/USA 2010 Conference Proceedings / The Forty-Sixth Annual International Telemetering Conference and Technical Exhibition / October 25-28, 2010 / Town and Country Resort & Convention Center, San Diego, California / Traditional angle of arrival algorithms operate with uniform receiver arrays. Non-uniform arrays typically introduce significant elevation of computation complexity. This paper utilizes the double-integration method for the accurate estimation of the angle of arrival with non-uniform receiver arrays, while maintaining high computation efficiency. Because of the simplicity, the double-integration method is not significantly affected by the increase of the number of receivers or the non-uniform configuration. This approach allows us to perform high-speed high-accuracy estimation of the two-dimensional bearing angle without the constraints of structured receiver arrays, which is important to the realization of real-time tracking of mobile acoustic sources.

<p>This thesis considers passive localization and tracking. Here, passive refers to passive observations - the type of observations for which the full position estimate of the target cannot be obtained using a single measurement, like those are from a sonar. Hence, localizing or tracking targets based on these measurements calls for the use of multiple sensors. This poses a different set of challenges to tracking with passive observations as opposed to active observations where full target position is available from a single measurement.</p><p>We identify different issues that are related to passive localization and tracking and propose algorithmic solutions to these problems. We consider the angle of arrival (AOA), which is the passive measurement that is often considered in target tracking and time difference of arrival (TDOA) as representative passive measurements to illustrate our algorithms. Whereas, the AOA measurements from different sensors can be considered independent, TDOA measurements, on the other hand, are not independent. That is, they are correlated. We would, however, like to note that the proposed algorithms can be applied with straightforward, but simple, modifications to other types of passive measurements.</p><p>In particular, this thesis provides solutions to the following problems. First, it provides efficient and improved algorithms to the data association problem when tracking with multiple passive synchronous sensors. These solutions are based on the assignment formulation. Whereas one of the algorithms proposed, the gated assignment algorithm, uses the validation gates to reduce the computational cost, the other is a new extension to the multidimensional assignment algorithm that associates the measurements directly to the tracks. This is called the (S + 1)-D assignment-based data association, where S is the number of synchronous sensors available in the tracking system. An approximation to this new (S + 1)-D algorithm is also presented.</p> <p> In literature one finds algorithms to localize a single target using TDOA measurements. None of these algorithms considered the issues that might arise in tracking the localized targets. This thesis provides a framework to localize and track targets based on TDOA measurements. The localization algorithm uses a formulation based on the sensor-emitter geometry. This formulation is considered as a constrained optimization problem and two relaxation-based algorithms are provided to solve this optimization problem. The assignment-based data association provides an additional challenge because the TDOA measurements are correlated. This problem is identified and a solution is provided by modifying the calculation of the association cost.</p> <p> Finally, this thesis also provides an efficient algorithm to form AOA mono tracks using the fast Fourier transform (FFT) and the assignment algorithm. Formation of the mono tracks is very useful in distributed tracking and is the well-known direction of arrival tracking problem in the signal processing community.</p> / Thesis / Doctor of Philosophy (PhD)

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As wireless devices become more common, the ability to position a wireless device has become a topic of importance. Accurate positioning through technologies such as the Global Positioning System is possible for outdoor environments. Indoor environments pose a different challenge, and research continues to position users indoors. Due to the prevalence of wireless local area networks (WLANs) in many indoor spaces, it is prudent to determine their capabilities for the purposes of positioning. Signal strength and time based positioning systems have been studied for WLANs. Direction or angle of arrival (AOA) based positioning will be possible with multiple antenna arrays, such as those included with upcoming devices based on the IEEE 802.11n standard. The potential performance of such a system is evaluated. The positioning performance of such a system depends on the accuracy of the AOA estimation as well as the positioning algorithm. Two different maximum-likelihood (ML) derived algorithms are used to determine the AOA of the mobile user: a specialized simple ML algorithm, and the space- alternating generalized expectation-maximization (SAGE) channel parameter estimation algorithm. The algorithms are used to determine the error in estimating AOAs through the use of real wireless signals captured in an indoor office environment. The statistics of the AOA error are used in a positioning simulation to predict the positioning performance. A least squares (LS) technique as well as the popular extended Kalman filter (EKF) are used to combine the AOAs to determine position. The position simulation shows that AOA- based positioning using WLANs indoors has the potential to position a wireless user with an accuracy of about 2 m. This is comparable to other positioning systems previously developed for WLANs.

Millimeter wave (mm-Wave) systems have become very attractive recently as lower frequency spectrums used for mobile device communications have been experiencing a “spectral crunch” due to the dissemination of smartphones. Channel characterization of the outdoor urban environment, where networks for mobile devices require the highest data capacity, has been quite scarce and even non-existent for cellular (rooftop to ground) setting measurements. Our project characterizes the urban environment at 38 GHz in a cellular setting and 38 and 60 GHz in a peer-to-peer setting. A sliding correlator channel sounder with an 800 MHz RF bandwidth at 38 GHz and 1.5 GHz RF bandwidth at 60 GHz was constructed to measure the channel using a bandwidth that is larger than the expected bandwidths of future mm-Wave channels. Directional antennas were utilized during the measurements to imitate mm-Wave systems using beam steering antenna arrays, which also allowed for AOA characterization. Path loss and RMS delay spread statistics are provided. Finally, an outage study was performed to test the outage likelihood in an urban environment with many multi-story buildings. / text

As wireless devices become more common, the ability to position a wireless device has become a topic of importance. Accurate positioning through technologies such as the Global Positioning System is possible for outdoor environments. Indoor environments pose a different challenge, and research continues to position users indoors. Due to the prevalence of wireless local area networks (WLANs) in many indoor spaces, it is prudent to determine their capabilities for the purposes of positioning. Signal strength and time based positioning systems have been studied for WLANs. Direction or angle of arrival (AOA) based positioning will be possible with multiple antenna arrays, such as those included with upcoming devices based on the IEEE 802.11n standard. The potential performance of such a system is evaluated. The positioning performance of such a system depends on the accuracy of the AOA estimation as well as the positioning algorithm. Two different maximum-likelihood (ML) derived algorithms are used to determine the AOA of the mobile user: a specialized simple ML algorithm, and the space- alternating generalized expectation-maximization (SAGE) channel parameter estimation algorithm. The algorithms are used to determine the error in estimating AOAs through the use of real wireless signals captured in an indoor office environment. The statistics of the AOA error are used in a positioning simulation to predict the positioning performance. A least squares (LS) technique as well as the popular extended Kalman filter (EKF) are used to combine the AOAs to determine position. The position simulation shows that AOA- based positioning using WLANs indoors has the potential to position a wireless user with an accuracy of about 2 m. This is comparable to other positioning systems previously developed for WLANs.

As wireless devices become more common, the ability to position a wireless device has become a topic of importance. Accurate positioning through technologies such as the Global Positioning System is possible for outdoor environments. Indoor environments pose a different challenge, and research continues to position users indoors. Due to the prevalence of wireless local area networks (WLANs) in many indoor spaces, it is prudent to determine their capabilities for the purposes of positioning. Signal strength and time based positioning systems have been studied for WLANs. Direction or angle of arrival (AOA) based positioning will be possible with multiple antenna arrays, such as those included with upcoming devices based on the IEEE 802.11n standard. The potential performance of such a system is evaluated. The positioning performance of such a system depends on the accuracy of the AOA estimation as well as the positioning algorithm. Two different maximum-likelihood (ML) derived algorithms are used to determine the AOA of the mobile user: a specialized simple ML algorithm, and the space- alternating generalized expectation-maximization (SAGE) channel parameter estimation algorithm. The algorithms are used to determine the error in estimating AOAs through the use of real wireless signals captured in an indoor office environment. The statistics of the AOA error are used in a positioning simulation to predict the positioning performance. A least squares (LS) technique as well as the popular extended Kalman filter (EKF) are used to combine the AOAs to determine position. The position simulation shows that AOA- based positioning using WLANs indoors has the potential to position a wireless user with an accuracy of about 2 m. This is comparable to other positioning systems previously developed for WLANs. / Applied Science, Faculty of / Engineering, School of (Okanagan) / Graduate

This thesis aims at evaluating a proposed interferometry Angle of Arrival method for Bluetooth Low Energy and investigating the feasibility of using it together with current technology in a keyless entry access control solution. The current technology is an evaluation kit from Texas Instrument that is used together with various types of antennae arranged in arrays. An in-depth look at it revealed that it does not implement the proposed Angle of Arrival method for Bluetooth Low Energy but the deviations are minor. Results obtained from tests with delay lines show enough accuracy for a keyless entry access control solution. However, none of the tested antenna types do. The work concludes that current technology cannot be used as a keyless entry access control solution due to strong antenna dependencies. Future work is thus proposed to be done on antenna development. / Detta arbete syftar till att utvärdera en förslagen interferometri Angle of Arrival-metod för Bluetooth Low Energy samt undersöka möjligheten att använda den tillsammans med nuvarande tekniken i nyckellös åtkomstkontroll. Den nuvarande tekniken är ett utvärderingspaket från Texas Instrument som används tillsammans med olika typer av antenner. En utförlig undersökning av tekniken avslöjade att den inte implementerar den föreslagna Angle of Arrival-metod för Bluetooth Low Energy men avvikelserna är minimala. Resultat som erhållits från tester med fördröjningslinjer visar tillräckligt noggrannhet för nyckellös åtkomstkontroll. Men ingen av de testade antenntyperna gör det. Arbetet drar slutsatsen att den nuvarande tekniken inte kan användas som nyckellös åtkomstkontroll på grund av starka antennberoende. Framtida arbete föreslås således att fokusera på antennutveckling.

The Bluetooth direction finding working group proposed functionalities to the Bluetooth core that can realize Angle of Arrival estimations using interferometry. The technology can be employed to develop new access control applications. Following previous findings in Englund (2018), the purpose of this project is to investigate the feasibility of such systems when antennas are being used. The goal is to design a matchbox size antenna array which can be used by the system to distinguish between two sides in an inside-outside scenario. A number of antennas were designed, simulated and tested on a prototype. While the simulations results were consistent with the theory, the prototype measurements were not. However, it is shown that it is possible to estimate between inside and outside. / Bluetooth direction finding working group har lagt fram ett förslag om att lägga till Angle of Arrival estimerings funktionalitet baserat på en interferometri metod i Bluetooth kärnan. Tekniken kan användas för att utveckla nya åtkomstkontrolls lösningar. Detta projekt en påbyggnad av arbetet utfört av Englund (2018), syftet är att utvärdera möjligheten av en sådan åtkomstkontrolls lösning där antenner används. Målet är att designa en tändsticksask stor antenn array som kan användas av ett systemet för att särskilja mellan två sidor i ett insida-utsida scenario. Ett antal antenner konstruerades, simulerades och prototyper byggdes samt testades. Medan simuleringsresultaten var förenliga med teorin, så påvisade prototyperna inte samma beteende då resultatet skiljde sig från teorin. Projektet konstaterar dock att det är möjligt att skilja mellan insida och utsida.