Robust Algorithms for Localizing Moving Nodes in Wireless Sensor Networks

TL;DR

This paper introduces a hybrid localization algorithm for moving nodes in wireless sensor networks, combining Particle Filter and TDOA techniques, demonstrating improved accuracy and robustness through simulations.

Contribution

It presents a novel hybrid approach merging Particle Filter and TDOA for localizing moving nodes, addressing mobility in WSNs.

Findings

Outperforms existing methods in accuracy

Demonstrates robustness in dynamic scenarios

Effective in mobile sensor network localization

Abstract

The vivid success of the emerging wireless sensor technology (WSN) gave rise to the notion of localization in the communications field. Indeed, the interest in localization grew further with the proliferation of the wireless sensor network applications including medicine, military as well as transport. By utilizing a subset of sensor terminals, gathered data in a WSN can be both identified and correlated which helps in managing the nodes distributed throughout the network. In most scenarios presented in the literature, the nodes to be localized are often considered static. However, as we are heading towards the 5th generation mobile communication, the aspect of mobility should be regarded. Thus, the novelty of this research relies in its ability to merge the robotics as well as WSN fields creating a state of art for the localization of moving nodes. The challenging aspect relies in the capability of merging these two platforms in a way where the limitations of each is minimized as much as possible. A hybrid technique which combines both the Particle Filter (PF) method and the Time Difference of Arrival Technique (TDOA) is presented. Simulation results indicate that the proposed approach outperforms other techniques in terms of accuracy and robustness.