Abstract

The demand for indoor localization is becoming urgent, but the traditional location fingerprint approach takes a lot of manpower and time to construct a fine-grained location fingerprint database. To address this problem, we propose to use the approach of combining dynamic collection of fingerprint samples with Radial Basis Function (RBF) interpolation. Specifically, the raw sparse fingerprint database is constructed from a small number of fingerprints collected on a few paths, in which the pedestrian track correction algorithm improves the validity and accuracy of the sparse fingerprint database. Then, the RBF interpolation approach is applied to enrich the sparse fingerprint database, in which the Genetic Algorithm (GA) is used to optimize the free shape parameter and the cut-off radius is determined according to the experimental results. Extensive experiments show that the proposed approach guarantees high interpolation and localization accuracy and also significantly reduces the effort of manual collection of fingerprint samples.

Highlights

  • With the rapid development of intelligent terminals and communication technologies, location-based services have become an indispensable and important element in daily life

  • The gait detection is completed by using the periodic characteristics of the acceleration when the human body walks, and the step length empirical model is applied to output the real-time step value

  • 5 Conclusion In this paper, we have proposed a new approach of reducing the effort of fingerprint database construction for indoor Bluetooth Low Energy (BLE) localization by decreasing Received Signal Strength (RSS) sample capacity, collecting the fingerprints dynamically and interpolating raw sparse fingerprint database by the proposed Dynamic Multi Direction (DMD)-RI approach

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Summary

Introduction

With the rapid development of intelligent terminals and communication technologies, location-based services have become an indispensable and important element in daily life. Innovative services such as Didi taxi and Mobike shared bicycles are closely related to the development and application of localization technology. Intelligent transportation is based on the Internet of Things (IoT) [1], 5G [2], and other technologies, which provide enormous connections of devices and sensors with applications. Satellite communications keep step with the quick development of wireless terrestrial communications [3, 4], such as Global Positioning System (GPS) [5], and can provide good localization services.

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