Our increased reliance on localization devices such as GPS navigation has led to an increased demand for localization solutions in all environments, including indoors. Indoor localization has received considerable attention in the last several years for a number of application areas including first responder localization to targeted advertising and social networking. The difficult multipath encountered indoors degrades the performance of RF based localization solutions and so far no optimal solution has been published. This dissertation presents an algorithm called Coherent Array Reconciliation Tomography (CART), which is a Direct Positioning Algorithm (DPA) that incorporates signal fusion to perform a simultaneous leading edge and position estimate for a superior localization solution in a high multipath environment. The CART algorithm produces position estimates that are near optimal in the sense that they achieve nearly the best theoretical accuracy possible using an Impulse Radio (IR) Ultra-Wideband (UWB) waveform. Several existing algorithms are compared to CART including a traditional two step Leading Edge Detection (LED) algorithm, Singular value Array Reconciliation Tomography (SART), and Transactional Array Reconciliation Tomography (TART) by simulation and experimentation. As shown under heavy simulated multipath conditions, where traditional LED produces a limited solution and the SART and TART algorithms fail, the CART algorithm produces a near statistically optimal solution. Finally, the CART algorithm was also successfully demonstrated experimentally in a laboratory environment by application to the fire fighter homing device that has been a part of the ongoing research at Worcester Polytechnic Institute (WPI).

Wireless video capsule endoscopy has been in use for over a decade and it uses radio frequency (RF) signals to transmit approximately fifty five thousands clear pictures of inside the GI tract to the body-mounted sensor array. However, physician has no clue on the exact location of the capsule inside the GI tract to associate it with the pictures showing abnormalities such as bleeding or tumors. It is desirable to use the same RF signal for localization of the VCE as it passes through the human GI tract. In this thesis, we address the accuracy limits of RF localization techniques for VCE localization applications. We present an assessment of the accuracy of cooperative localization of VCE using radio frequency (RF) signals with particular emphasis on localization inside the small intestine. We derive the Cramer-Rao Lower Bound (CRLB) for cooperative location estimators using the received signal strength(RSS) or the time of arrival (TOA) of the RF signal. Our derivations are based on a three-dimension human body model, an existing model for RSS propagation from implant organs to body surface and a TOA ranging error model for the effects of non-homogenity of the human body on TOA of the RF signals. Using models for RSS and TOA errors, we first calculate the 3D CRLB bounds for cooperative localization of the VCE in three major digestive organs in the path of GI tract: the stomach, the small intestine and the large intestine. Then we analyze the performance of localization techniques on a typical path inside the small intestine. Our analysis includes the effects of number of external sensors, the external sensor array topology, number of VCE in cooperation and the random variations in transmit power from the capsule.

Locating a radiating source based on range or range measurements obtained from a network of passive sensors has been a subject of research over the past two decades due to the problem’s importance in applications in wireless communications, surveillance, navigation, geosciences, and several other fields. In this thesis, we develop new solution methods for the problem of localizing a single radiating source based on range and range-difference measurements. Iterative re-weighting algorithms are developed for both range-based and range-difference-based least squares localization. Then we propose a penalty convex-concave procedure for finding an approximate solution to nonlinear least squares problems that are related to the range measurements. Finally, the sequential convex relaxation procedures are proposed to obtain the nonlinear least squares estimate of source coordinates. Localization in wireless sensor network, where the RF signals are used to derive the ranging measurements, is the primary application area of this work. However, the solution methods proposed are general and could be applied to range and range-difference measurements derived from other types of signals. / Graduate / 0544 / ismailds@uvic.ca