Position location has become one of the more important tasks for improving communication and networking performance for future commercial wireless systems. It is also the enabling technology for many control and sensing applications envisioned by the wireless sensor networks (WSN). Despite its meaningfulness and many algorithms being developed in the past several years, position location in harsh propagation environments remains to be a challenging issue, due mainly to the lack of sufficient infrastructure support and the prominent phenomenon of non-line-of-sight (NLOS) signal propagation. Recently, adopting the concept of collaborative position location has attracted much research interest due to its potential in overcoming the abovementioned two difficulties. In this work, we approach collaborative position location from two different angles. Specifically, we investigate the optimal performance of collaborative position location, which serves as a theoretical performance benchmark. In addition, we developed a computationally efficient algorithm for collaborative position location and incorporated an effective NLOS mitigation method to improve its performance in NLOS-dense environments. Overall, our work provides insight into both theoretical and practical aspects of collaborative position location. / Ph. D.

The ability to find the location of a mobile user has become of utmost importance. The demands of first responders necessitates the ability to accurately identify the location of an individual who is calling for help. Their response times are directly influenced by the ability to locate the caller. Thus, applications such as Enhanced 911 and other location-based services warrant the ability to quickly and accurately calculate location. The FCC has also put in place a timeline for indoor location accuracy requirements that must be met by the mobile communications service providers. In order to meet these requirements, there are many means of performing indoor geolocation that require research; in this thesis two specific methods of identifying the location of a user will be investigated. In the first part, the indoor localization of a target, whose exact location is unknown, in a LTE network is studied. In this problem the time difference of arrival of the LTE uplink signals sent from the target to an observer are used as the means to estimate the target position. The two-dimensional location of a user is then estimated through the use of a nonlinear least-squares algorithm. To improve this approach, a cooperative localization technique in uplink LTE is proposed in which the User Equipment (UE) communicates with base stations as well as other handsets. Through simulated results it is shown that utilizing collaboration can improve location estimation and outperform non-collaborative localization. In the second part, the indoor localization of a target, focusing on its third dimension or elevation, is studied through the use of barometric pressure sensors in mobile handsets. Finding the third dimension of location, or the correct height above the ground level which equates to the floor in a building that a UE is on, cannot be performed with two-dimensional measurement models. For this problem, the pressure sensors are used to accurately find an immediate pressure measurement and allow for the altitude of a handset to be calculated. This altitude can be translated into an estimation for a specific floor of a building given the use of a ground floor pressure reference. Through simulation results it is then shown that the accuracy of third dimension or indoor-floor localization can be improved with the use of collaborative pressure sensors of other mobile handsets. / Master of Science

The localization of wireless devices, e.g. mobile phones, laptops, and handheld GPS receivers, has gained much interest due to the benefits it provides, including quicker emergency personnel dispatch, location-aided routing, as well as commercial revenue opportunities through location based services.  GPS is the dominant position location system in operation, with 31 operational satellites producing eight line of sight satellites available to users at all times making it very favorable for system implementation in all wireless networks.  Unfortunately when a GPS receiver is in a challenging environment, such as an urban or indoor scenario, the signal quality often degrades causing poor accuracy in the position estimate or failure to localize altogether due to satellite availability. Our goal is to introduce a new solution that has the ability to overcome this limitation by improving the accuracy and availability of a GPS receiver when in a challenging environment.  To test this theory we created a simulated GPS receiver using a MATLAB simulation to mimic a standard GPS receiver with all 31 operational satellites.  Here we are able to alter the environment of the user and examine the errors that occur due to noise and limited satellite availability.  Then we introduce additional user(s) to the GPS solution with the knowledge (or estimate) of the distances between the users.  The new solutions use inter-receiver distances along with pseudoranges to cooperatively determine all receiver location estimates simultaneously, resulting in improvement in both the accuracy of the position estimate and availability. / Master of Science

This thesis focuses on the least-squares formulation of the non-collaborative and collabo- rative position location problems. For the non-collaborative problem, characterization encompassing the number of minima and the causes thereof is provided. Based on these efforts, we propose an improvement to the existing modified parallel projection method (MPPM), the reflected parallel projection method (RPPM). We show that the global minimum to the non-collaborative objective function can nearly always be found using the non-optimal reflected parallel projection method (RPPM). For the collaborative position location problem, we provide a characterization that shows a heavy tail of root-mean-square (RMS) error due to a small percentage of simulated node/anchor layouts when solved by the iterative parallel projection method (IPPM). We provide an identification technique that successfully identifies most layouts that show large RMS error followed by a proposed solution to improve the accuracy in those problematic layouts. Finally, we report the findings of a measurement campaign that validates our Gaussian model for line-of-sight (LOS) noise and shows that, for these particular measurements, non-line-of-sight (NLOS) noise is difficult to accurately model and can be very large. This research was supported by a Bradley Fellowship from Virginia Tech's Bradley Department of Electrical and Computer Engineering, made possible by an endowment from the Harry Lynde Bradley Foundation. / Master of Science