Engineering Commons^™

Uwb Precise Indoor Localization System Performance, Limitations And Its Integration, Essam Abdelkadir Elkhouly

Doctoral Dissertations

An indoor localization system that was built at University of Tennessee is extensively studied and improved. The goal of the system is to achieve mm down to sub-mm accuracy/precision.

Sub-sampling is used to alleviate the high sampling rate required for UWB signals. Current commercial direct sampling systems are still too slow or prohibitively expensive for UWB applications. We developed two different sub-sampling techniques, but the two systems suffer numerous shortcomings: low throughput, non-robustness, non-linearity. A third system is introduced that achieve both high accuracy and high through-put. Changes in the detection algorithm and the frame synchronization are developed to accommodate …

Improved Accuracy In Real-Time Rfid Localization Systems Using Kalman Filtering, Benjamin J. Sanda

Masters Theses

The use of Radio Frequency Identification (RFID) has become widespread in industry as a means to quickly and wirelessly identify and track packages and equipment. Now there is a commercial interest in using RFID to provide real-time localization. Efforts to use RFID technology for this purpose experience localization errors due to noise and multipath effects inherent to these environments. This paper presents the use of both linear Kalman filters and non-linear Unscented Kalman filters to reduce error effects inherent to real-time RFID localization systems and provide more accurate localization results in indoor environments. A commercial RFID localization system designed for …

Global Optimization Methods For Localization In Compressive Sensing, Marco Rossi

Dissertations

The dissertation discusses compressive sensing and its applications to localization in multiple-input multiple-output (MIMO) radars. Compressive sensing is a paradigm at the intersection between signal processing and optimization. It advocates the sensing of “sparse” signals (i.e., represented using just a few terms from a basis expansion) by using a sampling rate much lower than that required by the Nyquist-Shannon sampling theorem (i.e., twice the highest frequency present in the signal of interest). Low-rate sampling reduces implementation’s constraints and translates into cost savings due to fewer measurements required. This is particularly true in localization applications when the number of measurements is …

Compact Fmcw Radar For Gps-Denied Navigation And Sense And Avoid, James David Mackie

Theses and Dissertations

Location information is vital for any type of aircraft and even more crucial for Unmanned Aerial Systems (UAS). GPS is a readily available solution but signals can easily be jammed or lost. In this thesis, radar is explored as a backup system for self-localization when GPS signals are not available. The method proposed requires that an area be pre mapped by collecting radar data with known latitude and longitude coordinates. New radar data is then collected and compared to previously stored values. Channel matrices are stored at each point and are used as the basis for location comparisons. Various methods …

Wireless Sensor Localization: Error Modeling And Analysis For Evaluation And Precision, Omar Ali Zargelin

Electronic Theses and Dissertations

Wireless sensor networks (WSNs) have shown promise in a broad range of applications. One of the primary challenges in leveraging WSNs lies in gathering accurate position information for the deployed sensors while minimizing power cost. In this research, detailed background research is discussed regarding existing methods and assumptions of modeling methods and processes for estimating sensor positions. Several novel localization methods are developed by applying rigorous mathematical and statistical principles, which exploit constraining properties of the physical problem in order to produce improved location estimates. These methods are suitable for one-, two-, and three-dimensional position estimation in ascending order of …

Visual Geo-Localization And Location-Aware Image Understanding, Amir Roshan Zamir

Electronic Theses and Dissertations

Geo-localization is the problem of discovering the location where an image or video was captured. Recently, large scale geo-localization methods which are devised for ground-level imagery and employ techniques similar to image matching have attracted much interest. In these methods, given a reference dataset composed of geo-tagged images, the problem is to estimate the geo-location of a query by finding its matching reference images. In this dissertation, we address three questions central to geo-spatial analysis of ground-level imagery: 1) How to geo-localize images and videos captured at unknown locations? 2) How to refine the geo-location of already geo-tagged data? 3) …

Localization And Security Algorithms For Wireless Sensor Networks And The Usage Of Signals Of Opportunity, Gustavo Andres Chacon Rojas

LSU Doctoral Dissertations

In this dissertation we consider the problem of localization of wireless devices in environments and applications where GPS (Global Positioning System) is not a viable option. The _x000C_rst part of the dissertation studies a novel positioning system based on narrowband radio frequency (RF) signals of opportunity, and develops near optimum estimation algorithms for localization of a mobile receiver. It is assumed that a reference receiver (RR) with known position is available to aid with the positioning of the mobile receiver (MR). The new positioning system is reminiscent of GPS and involves two similar estimation problems. The _x000C_rst is localization using …