NDLI: Non-line-of-sight localization using low-rank + sparse matrix decomposition

Content Provider	IEEE Xplore Digital Library
Author	Ekambaram, V.N. Ramchandran, K.
Copyright Year	2012
Description	Author affiliation: Department of EECS, University of California, Berkeley, USA (Ekambaram, V.N.; Ramchandran, K.)
Abstract	We consider the problem of estimating the locations of a set of points in a k-dimensional euclidean space given a subset of the pairwise distance measurements between the points. We focus on the case when some fraction of these measurements can be arbitrarily corrupted by large additive noise. This is motivated by applications like sensor networks, molecular conformation and manifold learning where the measurement process can induce large bias errors in some fraction of the distance measurements due to physical effects like multipath, spin-diffusion etc. Given the NP-completeness of the problem, we propose a convex relaxation that involves decomposing the partially observed matrix of distance measurements into low-rank and sparse components, wherein the low-rank component corresponds to the Euclidean Distance Matrix and the sparse component is a matrix of biases. Using recent results from the literature, we show that this convex relaxation yields the exact solution for the class of fixed radius random geometric graphs. We evaluate the performance of the algorithm on an experimental data set obtained from a network of 44 nodes in an indoor environment and show that the algorithm is robust to non-line-of-sight bias errors.
Starting Page	317
Ending Page	320
File Size	1033023
Page Count	4
File Format	PDF
ISBN	9781467301824
e-ISBN	9781467301817
DOI	10.1109/SSP.2012.6319692
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2012-08-05
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Sparse matrices Matrix decomposition Distance measurement Noise measurement Measurement uncertainty Vectors Nonlinear optics robust matrix decomposition Non-Line-of-Sight localization
Content Type	Text
Resource Type	Article

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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