Crowdsource Based Indoor Localization by Uncalibrated Heterogeneous Wi-Fi Devices

Abstract EN

Many indoor localization techniques that rely on received signals from Wi-Fi access points have been explored in the last decade.

Recently, crowdsourced Wi-Fi fingerprint attracts much attention, which leads to a self-organized localization system avoiding painful survey efforts.

However, this participatory approach introduces new challenges with no previously proposed techniques such as heterogeneous devices, short measurement time, and multiple values for a single position.

This paper proposes an efficient localization method combating the three major technical issues in the crowdsourcing based systems.

We evaluate our indoor positioning method using 5 places with different radio environment and 8 different mobile phones.

The experimental results show that the proposed approach provides consistent localization accuracy and outperforms existing localization algorithms.