Article: An Interlaced Extended Kalman Filter for sensor networks localisation Journal: International Journal of Sensor Networks (IJSNET) 2009 Vol.5 No.3 pp.164 - 172 Abstract: Sensor networks have become a widely used technology for applications ranging from military surveillance to industrial fault detection. So far, the evolution in micro-electronics has made it possible to build networks of inexpensive nodes characterised by modest computation and storage capability as well as limited battery life. In such a context, having an accurate knowledge about nodes position is fundamental to achieve almost any task. Several techniques to deal with the localisation problem have been proposed in literature: most of them rely on a centralised approach, whereas others work in a distributed fashion. However, a number of approaches do require a prior knowledge of particular nodes, i.e. anchors, whereas others can face the problem without relying on this information. In this paper, a new approach based on an Interlaced Extended Kalman Filter (IEKF) is proposed: the algorithm, working in a distributed fashion, provides an accurate estimation of node poses with a reduced computational complexity. Moreover, no prior knowledge for any nodes is required to produce an estimation in a relative coordinate system. Exhaustive experiments, carried on MICAz nodes, are shown to prove the effectiveness of the proposed IEKF. Inderscience Publishers - linking academia, business and industry through research

Title: An Interlaced Extended Kalman Filter for sensor networks localisation

Authors: A. Gasparri, S. Panzieri, F. Pascucci, G. Ulivi

Addresses: Dipartimento di Informatica e Automazione, Universita degli Studi ''Roma TRE'', Via della Vasca Navale, 79, Roma, Italy. ' Dipartimento di Informatica e Automazione, Universita degli Studi ''Roma TRE'', Via della Vasca Navale, 79, Roma, Italy. ' Dipartimento di Informatica e Automazione, Universita degli Studi ''Roma TRE'', Via della Vasca Navale, 79, Roma, Italy. ' Dipartimento di Informatica e Automazione, Universita degli Studi ''Roma TRE'', Via della Vasca Navale, 79, Roma, Italy

Abstract: Sensor networks have become a widely used technology for applications ranging from military surveillance to industrial fault detection. So far, the evolution in micro-electronics has made it possible to build networks of inexpensive nodes characterised by modest computation and storage capability as well as limited battery life. In such a context, having an accurate knowledge about nodes position is fundamental to achieve almost any task. Several techniques to deal with the localisation problem have been proposed in literature: most of them rely on a centralised approach, whereas others work in a distributed fashion. However, a number of approaches do require a prior knowledge of particular nodes, i.e. anchors, whereas others can face the problem without relying on this information. In this paper, a new approach based on an Interlaced Extended Kalman Filter (IEKF) is proposed: the algorithm, working in a distributed fashion, provides an accurate estimation of node poses with a reduced computational complexity. Moreover, no prior knowledge for any nodes is required to produce an estimation in a relative coordinate system. Exhaustive experiments, carried on MICAz nodes, are shown to prove the effectiveness of the proposed IEKF.

Keywords: sensor networks; localisation; extended Kalman filter; EKF; node positions.

DOI: 10.1504/IJSNET.2009.026364

International Journal of Sensor Networks, 2009 Vol.5 No.3, pp.164 - 172

Published online: 08 Jun 2009 *

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Title: An Interlaced Extended Kalman Filter for sensor networks localisation

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