AbstractsComputer Science

Leveraging the capture effect for indoor localization.:

by A. Drif




Institution: Delft University of Technology
Department:
Year: 2015
Keywords: indoor-localization; capture effect; orthogonal codes; spread spectrum; low-energy
Record ID: 1259834
Full text PDF: http://resolver.tudelft.nl/uuid:8c9d9db6-a6fa-4655-a1bc-659d8130e6dd


Abstract

This Msc. Thesis builds upon a work-in progress called collocal which researched room-level indoor-localization. Localization is the action of estimating the position of a certain entity on a map. For example tracking the postion of furniture and other inventory in a building over a long period of time. To localize these entities other static nodes are employed that know their own location. These static nodes, called anchors, beacon their coordinates periodically. Mobile nodes are the entities that try to estimate their position based on these beacon messages. In conventional systems this beaconing is done asynchronously. System designers employ complex schemes to prevent anchor nodes from beaconing at the same time to avoid interference. These systems consume lots of energy at the mobile node, because they have to keep their radio on for a longer time. A deployment of such a localization system is expected to last for a long term period without replacing batteries of the used device. Counterintuitive to what asynchronous system designers do, in collocal the anchor nodes beacon at the same time on purpose. Collocal reduces the energy consumption considerably by shortening the listening interval at the mobile node. Collocal however suffers from two major drawbacks: a dead zone area (an area where you can not be localized) between anchor nodes and a very high bit-error rate. In this Msc. thesis the two problems are solved with the use of orthogonal codes. I was able to improve the battery lifetime of the mobile node from 3 months in the asynchronous case to 2 years using a localization period of 1 second. The proposed method is evaluated against five state-of-the-art localization algorithms.