Localization based on magnetic and RSS data fusion with covariance intersection for mobile sensor network

Abstract

A mobile sensor node plays an important role in wireless sensor network. Not only can it replace a failed sensor node dynamically and automatically, but also can search the dangerous region autonomously. To keep mobile node in continuously working condition, power supply is an important issue. For this reason, docking for the mobile node is an important issue in mobile sensor network. How to guide it to anchor the docking station and recharge successfully is a key element for stable and long-term usages. In this paper we propose Covariance Intersection (CI) to fuse the localization estimation obtained from RSS (received signal strength) and magnetic localization together in order to dock mobile node accurately. Moreover a docking station with an auto-recharging device and mobile node docking mechanism are implemented. Nevertheless, the localization estimation error of RSS is 4 times larger than magnetic localization in short range usage while the docking process. This paper brings out a reliable algorithm through CI data fusion method to fuse the RSS and the magnetic localization estimations. Our experimental results show that error can be reduced less than 5%. Besides, the docking control strategy and automatic recharging device for the mobile node also will be proposed.