JOURNAL ARTICLE

Enhanced mechanism for localization in Wireless Sensor Networks using PSO assisted Extended Kalman Filter Algorithm (PSO-EKF)

Abstract

Localization is one of the challenges in achieving reliable communication in Wireless Sensor Networks (WSN). Estimating a sensor's node's position is known as Localization. Nonlinear version of Kalman filtering is known as the Extended Kalman Filter which deals with the case governed by the nonlinear stochastic differential equations, Extended kalman filter is nonlinear filter having their own problem of consistency. In this paper proposed efficient localization algorithm that enables sensor nodes to estimate their location with high accuracy. The purpose of this paper is to develop the particle swarm optimization assisted Extended Kalman Filter (PSO-EKF) for Localization in WSN. Performance evaluation for the PSO-EKF as compared to the conventional KF could be better for time critical applications.

Keywords:
Extended Kalman filter Kalman filter Particle swarm optimization Wireless sensor network Computer science Invariant extended Kalman filter Algorithm Control theory (sociology) Node (physics) Nonlinear system Fast Kalman filter Engineering Artificial intelligence Computer network

Metrics

16
Cited By
1.67
FWCI (Field Weighted Citation Impact)
15
Refs
0.88
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Indoor and Outdoor Localization Technologies
Physical Sciences →  Engineering →  Electrical and Electronic Engineering
Energy Efficient Wireless Sensor Networks
Physical Sciences →  Computer Science →  Computer Networks and Communications
Underwater Vehicles and Communication Systems
Physical Sciences →  Engineering →  Ocean Engineering

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