One Anchor Distance and Angle Based Multi - Hop Adaptive Iterative Localization Algorithm for Wireless Sensor Networks

One Anchor Distance and Angle Based Multi - Hop Adaptive Iterative Localization Algorithm for Wireless Sensor Networks

S. B. Kotwal (SMVD University, India), Shekhar Verma (Indian Institute of Information Technology, India), G. S. Tomar (Malwa Institute of Technology, India) and R. K. Abrol (SMVD University, India)
DOI: 10.4018/978-1-4666-0056-0.ch018
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Abstract

This paper presents distance and angle measurements based Multi-Hop Adaptive and Iterative Localization algorithm for localization of unknown nodes in wireless sensor networks (WSNs). The present work determines uncertainty region of unknown nodes with respect to known (anchor) nodes using noisy distance and angle measurements. This node transmits its uncertainty region to other unknown nodes to help them determine their uncertainty region. Because of noisy distance and angle measurements, the error propagation increases the size of regions of nodes in subsequent hops. Using only one anchor node as reference, the proposed iterative localization algorithm reduces the error propagation of this noisy distance and angle measurements and the uncertainty region of all unknown nodes within a given communication range. The results clearly indicate the improved efficiency of the proposed algorithm in comparison with existing algorithms.
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Ii. Problem Statement

We define the localization problem as estimating the smallest region which has the highest probability of having a node. With the available hardware and software support, any node within one hop from anchor can determine its uncertainty region w.r.t. anchor node from data sent by anchor with received signal strength index (RSSI) and angle of arrival (AOA) measurements. Before working on an algorithm based on above measurements, the uncertainties and their effects need to be taken into consideration. Therefore we discuss these uncertainties as under:

  • A. Uncertainty due to noisy distance measurement: With available RSSI, the distance between two nodes can be approximated by:Uj2=UkiUk1(1)

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