New Analytical and Algorithmic Framework for Hybrid Wireless Localization

  • In recent years, due to the fast development of Wireless Sensor Networks in terms of size, energy and processing capability, and their growing penetration into new areas of application, wireless localization as one of the key features in this field has developed significant research interest amongst academia and industry community. Researchers and engineers conduct numerous attempts to design optimum wireless localization systems with high location precision and low energy consumption. A well known mechanism to improve accuracy is to rely on multiple types of information, which leads to hybrid or heterogeneous algorithms that have been shown to have advantages over algorithms admitting only a given type of input. For this reason, such algorithms have gained prominent importance in the recent years. Based on the well theorem of Cram`er-Rao lower bound, in this work we introduce a new generic analytical framework in which the fundamental performance limit of hybrid localization algorithms can be easily addressed. Furthermore, focusing on the design of new hybrid algorithms with the aim to improve localization accuracy and/or computational complexity, we introduce a new algorithmic framework from which many algorithms with different complexity/performance tradeoffs can be tailor designed for different scenarios of information availability. We revisit the super multidimensional scaling (SMDS) wireless localization algorithm first proposed a decade ago, recasting it onto the complex-domain. Under this new formulation, the edge kernel which carries both angle and distance information simultaneously and plays a central role in the SMDS algorithm, becomes a complex-valued rank-one matrix, resulting in a new complex-domain SMDS framework which yields several advantages over the original, including the elimination of redundancy, the enhancement of conditions to handle information erasure, and the possibility of designing a new hybrid algorithmic framework.

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Publishing Institution:IRC-Library, Information Resource Center der Jacobs University Bremen
Granting Institution:Jacobs Univ.
Author:Alireza Ghods
Referee:Giuseppe Abreu, Francesco Maurelli, Sven Zeisberg
Advisor:Giuseppe Abreu
Persistent Identifier (URN):urn:nbn:de:gbv:579-opus-1008034
Document Type:PhD Thesis
Language:English
Date of Successful Oral Defense:2018/05/05
Date of First Publication:2018/05/08
Academic Department:Computer Science & Electrical Engineering
PhD Degree:Electrical Engineering
Focus Area:Mobility
Call No:Thesis 2018/7

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