An Indoor Fingerprinting Localization Approach for ZigBee Wireless Sensor Networks

TL;DR

This paper presents an indoor fingerprinting localization method using RSS that reduces the need for extensive reference point collection, achieving good accuracy with fewer measurements in ZigBee WSNs.

Contribution

It introduces a novel RSS-based fingerprinting approach dividing the area into subareas with unique features, minimizing reference point requirements.

Findings

Achieves accurate indoor localization with fewer reference points

Demonstrates effectiveness through real experiments with Jennic sensor nodes

Reduces setup complexity and cost for indoor positioning systems

Abstract

Location tracking systems are increasingly becoming the focus of research in the field of Wireless Sensor Network (WSN). Received Signal Strength (RSS)-based localization systems are at the forefront of tracking research applications. Radio location fingerprinting is one of the most promising indoor positioning approaches due to its powerful in terms of accuracy and cost. However, fingerprinting systems require the collection of a large number of reference points in the tracking area to achieve reasonable localization accuracy. In this paper, we propose a fingerprinting localization approach based on a RSS technique. The proposed system does not require gathering a large number of reference points and offers good localization accuracy indoors. The implemented approach is based on dividing the tracking area into subareas and assigning a unique feature to each subarea through ranging the RSS values from different reference points. In order to test the proposed system's efficiency, a number of real experiments have been conducted using Jennic sensor nodes.