Smartphones have become an indispensable tool in the work and life of most people. Given the many kinds of sensors built into smartphones, solving indoor navigation problems using these phones has become feasible. This paper proposes such a solution, using a particle-filter-based indoor positioning method. This method improves the positioning accuracy and helps improve the user experience. The major features of the method are that it leverages and fuses the advantages of two different indoor positioning methods [pedestrian dead reckoning (PDR) and received-signal-strength-indicator-based indoor positioning], and considers the influence on positioning of the indoor spatial map. The smartphone built-in sensors are used as data sources and constitute a feasible method for PDR. The iBeacon devices are also used - because of the many advantages, they present in indoor environments, such as low energy consumption, convenient deployment, and popular applications - and their received signal strength indicator values are used as observations in the particle filter. The devices used in this paper are conventional, without any special equipment, and the experimental sites are common work environments. Therefore, we believe that the proposed method has a wide application potential for indoor navigation applications (e.g., museum guides), and is especially suitable for working with indoor navigation maps.
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Xia et al. (2018) studied this question.
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