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Range-Only Node Localization: The Arbitrary Anchor Case in D-Dimensions / Pedro Paulo Ventura Tecchio.
- Format:
- Book
- Thesis/Dissertation
- Author/Creator:
- Ventura Tecchio, Pedro Paulo, author.
- Language:
- English
- Subjects (All):
- Electrical engineering.
- Computer science.
- Robotics.
- Electrical and systems engineering--Penn dissertations.
- Penn dissertations--Electrical and systems engineering.
- Local Subjects:
- Electrical engineering.
- Computer science.
- Robotics.
- Electrical and systems engineering--Penn dissertations.
- Penn dissertations--Electrical and systems engineering.
- Genre:
- Academic theses.
- Physical Description:
- 1 online resource (114 pages)
- Contained In:
- Dissertations Abstracts International 81-05B.
- Place of Publication:
- [Philadelphia, Pennsylvania] : University of Pennsylvania ; Ann Arbor : ProQuest Dissertations & Theses, 2019.
- Language Note:
- English
- System Details:
- Mode of access: World Wide Web.
- text file
- Summary:
- This work is situated at the intersection of two large fields of research the Localization problem and applications in Wireless Networks. We are interested in providing good estimations for network node locations in a defined space based on sensor measurements. Many methods have being created for the localization problem, in special we have the classical Triangulation and Trilateration procedures and MultiDimensional Scaling. A more recent method, DILOC, utilizes barycentric coordinates in order to simplify part of the non-linearities inherent to this problem. Except for Triangulation in which we require angle measurements between nodes, the other cited methodologies require, typically only, range measurements. Off course, there exists variants which allow the use of range and angle measurements. We specialize our interest in range only methods utilizing barycentric coordinates by first providing a novel way to compute barycentric coordinates for any possible node-neighbor spatial configuration in any given dimension. Which, we use as basis for our experiments with averaging processes and the development of our centralized and distributed gradient descent algorithms. Our distributed algorithm is able to receive range measurements with noise of uncharacterized distributions as it inputs. Using simulations in Matlab, we provide comparisons of our algorithms with Matlab's MDS function. Lastly, we show our efforts on providing a physical network implementation utilizing existing small form factor computers, wireless communication modules and range sensors.
- Notes:
- Source: Dissertations Abstracts International, Volume: 81-05, Section: B.
- Advisors: Pappas, George J.; Committee members: Victor Preciado; Nikolay Atanasov; Shahin Shahrampour.
- Department: Electrical and Systems Engineering.
- Ph.D. University of Pennsylvania 2019.
- Local Notes:
- School code: 0175
- ISBN:
- 9781088372265
- Access Restriction:
- Restricted for use by site license.
- This item must not be sold to any third party vendors.
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