A Mixed Convex/Nonconvex Distributed Localization Approach for the Deployment of Indoor Positioning Services

In this paper the indoor wireless localization problem is addressed both from the theoretical and application standpoints. The main result of the paper is on the theoretical side: the topological definition of regular and irregular nodes is introduced, and formal results are presented to support reg...

Full description

Saved in:
Bibliographic Details
Published in:IEEE transactions on mobile computing 2008-11, Vol.7 (11), p.1325-1337
Main Authors: Abramo, A., Blanchini, F., Geretti, L., Savorgnan, C.
Format: Magazinearticle
Language:English
Subjects:
Algorithms
Applied sciences
Blinds
Computational modeling
Constrained optimization
Context awareness
Convergence
Convex programming
Exact sciences and technology
Indoor
Localization
Mobile Applications
Network topology
Networks
Optimization
Peer to peer computing
Pervasive computing
Position (location)
Position measurement
Studies
Telecommunications
Telecommunications and information theory
Teleprocessing networks. Isdn
Valuation and optimization of characteristics. Simulation
Wireless application protocol
Wireless networks
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:In this paper the indoor wireless localization problem is addressed both from the theoretical and application standpoints. The main result of the paper is on the theoretical side: the topological definition of regular and irregular nodes is introduced, and formal results are presented to support regularity as a desirable network property for the attainment of precise node localization. In force of this definition, a mixed convex/non-convex optimization approach has been derived for the solution of the positioning problem. The two procedures, suitably combined, allow the achievement of better convergence towards the best positioning of a multitude of blind wireless nodes. A completely decentralized, partially asynchronous algorithm is presented, which proceeds locally on each node based on the sole knowledge of the distances measured from, and of the estimated positions of the connected nodes only. Its repeated asynchronous application on each nodes guarantees the convergence of the algorithm to the positioning of the whole network, even in presence of a limited number of peripheral reference points. Indeed, no global information is required for the proper functioning of the algorithm. Simulations of relevant case studies have been performed to qualify the proposed scheme in realistic conditions, and the results are presented.
ISSN:1536-1233
1558-0660
DOI:10.1109/TMC.2008.59