Voronoi Diagram and Crowdsourcing-Based Radio Map Interpolation for GRNN Fingerprinting Localization Using WLAN.

Yongliang Sun,Weixiao Meng,Xinggan Zhang,Yu He

doi:10.3390/s18103579

Abstract

In the last decade, fingerprinting localization using wireless local area network (WLAN) has been paid lots of attention. However, this method needs to establish a database called radio map in the off-line stage, which is a labor-intensive and time-consuming process. To save the radio map establishment cost and improve localization performance, in this paper, we first propose a Voronoi diagram and crowdsourcing-based radio map interpolation method. The interpolation method optimizes propagation model parameters for each Voronoi cell using the received signal strength (RSS) and location coordinates of crowdsourcing points and estimates the RSS samples of interpolation points with the optimized propagation model parameters to establish a new radio map. Then a general regression neural network (GRNN) is employed to fuse the new and original radio maps established through interpolation and manual operation, respectively, and also used as a fingerprinting localization algorithm to compute localization coordinates. The experimental results demonstrate that our proposed GRNN fingerprinting localization system with the fused radio map is able to considerably improve the localization performance.

Highlights

With the rapid development of information technology, especially the emergence of electronic maps, location-based service (LBS) has been one of current research hot-spots and has been applied to various aspects of people’s daily life, bringing great convenience to people [1]
We propose an interpolation method for radio map establishment based on a Voronoi diagram and crowdsourcing
We propose a wireless local area network (WLAN) fingerprinting localization system, which is able to save labor and time cost for radio map establishment, and achieves a comparable localization performance

Summary

Introduction

With the rapid development of information technology, especially the emergence of electronic maps, location-based service (LBS) has been one of current research hot-spots and has been applied to various aspects of people’s daily life, bringing great convenience to people [1]. As a core technology of LBS, localization technology has attracted more and more concerns. The increasing demands for LBS have prompted the vigorous development of localization technology [2,3]. To offer satisfactory LBS in indoor environments, such as airports, museums, shopping malls, and underground car parks, many technologies have been applied to indoor localization like infrared, ultrasound, ZigBee, ultra-wide band (UWB), radio frequency identification (RFID), inertial sensors, and wireless local area network (WLAN) [2,5,6,7]. Considering the establishment cost and localization performance, WLAN fingerprinting localization has been favored among the existing indoor localization techniques

Methods

Results

Conclusion