Improved sequence-based localization applied in coal mine

Mingzhi Song,Jiansheng Qian

doi:10.1177/1550147716669615

Abstract

Complex geographical environment brings tremendous challenges to get information of localization in underground coal mines. Sequence-based localization is a simple method; without calculating distance during the positioning stage in real time, this method uses the received signal strength indication matched degree between unknown node and regions to locate. However, sequence-based localization has a great issue on poor marginal nodes localization. Sequence–centroid localization contributes to improving this issue, but the location error on the boundary of whole area is unsatisfactory as well. This article proposes an improved sequence-based localization method which is integrated with quantum-behaved particle swarm optimization, as quantum-behaved particle swarm optimization makes good use of the search performance of global optimal solution. In our simulation, we consider that ZigBee devices can be used to construct wireless sensor networks and locate personnel location. The results prove that the improved sequence-based localization algorithm provides comparable accuracy than sequence-based localization.

Highlights

Over the past decades, the security problem of coal mines has been an important factor of constraining the development of coal industry around the world
Yedavalli and Krishnamachari[11] proposed a new method called sequence-based localization (SBL), and it expounds that the localization area can be classified into many different regions which can be uniquely identified by received signal strength indication (RSSI) sequences
The SBL method spends much time on the stage of RSSI sequence construction; the estimated location is calculated from the centroid of a region matched with the corresponding sequence on the positioning stage.[12]

Summary

Introduction

The security problem of coal mines has been an important factor of constraining the development of coal industry around the world. Yedavalli and Krishnamachari[11] proposed a new method called sequence-based localization (SBL), and it expounds that the localization area can be classified into many different regions which can be uniquely identified by received signal strength indication (RSSI) sequences. These sequences represent the ranking of distances from reference nodes to each region.[11] The SBL method spends much time on the stage of RSSI sequence construction; the estimated location is calculated from the centroid of a region matched with the corresponding sequence on the positioning stage.[12] The method is suitable for the personnel localization in coal mine environment. Simulation results are given in section ‘‘Simulation’’ to demonstrate the performance of the promoted scheme, and some conclusions and future works are given in section ‘‘Conclusions and future work.’’

Related works

Spearman’s rank-order correlation coefficient is shown as follows11

Findings

Conclusion and future work