Novel decision-fusion algorithms for target tracking using ad hoc networks

Nicolás Fariña; Joaquín Míguez; Mónica F. Bugallo

doi:10.1109/VETECS.2005.1543796

Novel decision-fusion algorithms for target tracking using ad hoc networks

Nicolás Fariña
, Joaquín Míguez
, Mónica F. Bugallo

Electrical Engineering

University of A Coruna
Universidad Carlos III de Madrid

Research output: Contribution to journal › Conference article › peer-review

2 Scopus citations

Abstract

In this paper we address the problem of tracking an object which moves along a certain area monitored by an ad hoc network of wireless sensors. We investigate two approaches based on the sequential Monte Carlo (SMC) methodology: an approximate version of the classical sequential importance sampling (SIS) algorithm and a recently proposed SMC methodology called cost-reference particle filtering (CRPF), which provides more flexibility in the algorithm design. Computer simulations show the feasibility and performance of the proposed methods.

Original language	English
Pages (from-to)	2556-2559
Number of pages	4
Journal	IEEE Vehicular Technology Conference
Volume	61
Issue number	4
DOIs	https://doi.org/10.1109/VETECS.2005.1543796
State	Published - 2005
Event	61st IEEE Vehicular Technology Conference, VTC 2005-Spring - Stockholm, Sweden Duration: May 30 2005 → Jun 1 2005

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10.1109/VETECS.2005.1543796

Cite this

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title = "Novel decision-fusion algorithms for target tracking using ad hoc networks",

abstract = "In this paper we address the problem of tracking an object which moves along a certain area monitored by an ad hoc network of wireless sensors. We investigate two approaches based on the sequential Monte Carlo (SMC) methodology: an approximate version of the classical sequential importance sampling (SIS) algorithm and a recently proposed SMC methodology called cost-reference particle filtering (CRPF), which provides more flexibility in the algorithm design. Computer simulations show the feasibility and performance of the proposed methods.",

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AU - Míguez, Joaquín

AU - Bugallo, Mónica F.

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N2 - In this paper we address the problem of tracking an object which moves along a certain area monitored by an ad hoc network of wireless sensors. We investigate two approaches based on the sequential Monte Carlo (SMC) methodology: an approximate version of the classical sequential importance sampling (SIS) algorithm and a recently proposed SMC methodology called cost-reference particle filtering (CRPF), which provides more flexibility in the algorithm design. Computer simulations show the feasibility and performance of the proposed methods.

AB - In this paper we address the problem of tracking an object which moves along a certain area monitored by an ad hoc network of wireless sensors. We investigate two approaches based on the sequential Monte Carlo (SMC) methodology: an approximate version of the classical sequential importance sampling (SIS) algorithm and a recently proposed SMC methodology called cost-reference particle filtering (CRPF), which provides more flexibility in the algorithm design. Computer simulations show the feasibility and performance of the proposed methods.

UR - https://www.scopus.com/pages/publications/26444435331

U2 - 10.1109/VETECS.2005.1543796

DO - 10.1109/VETECS.2005.1543796

M3 - Conference article

AN - SCOPUS:26444435331

SN - 0740-0551

VL - 61

SP - 2556

EP - 2559

JO - IEEE Vehicular Technology Conference

JF - IEEE Vehicular Technology Conference

IS - 4

T2 - 61st IEEE Vehicular Technology Conference, VTC 2005-Spring

Y2 - 30 May 2005 through 1 June 2005

ER -

Novel decision-fusion algorithms for target tracking using ad hoc networks

Abstract

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