A cost-effective Wi-Fi-based indoor positioning system for mobile phones

Fingerprinting-based indoor positioning systems require a significant amount of time to set up due to the need for prior, offline signal map creation. We propose a mobile phone-based indoor positioning system that can be set up in a short amount of time in any environment with existing Wi-Fi infrastructure. We introduce interpolation into a fingerprinting-based system to reduce the number of reference points needed, leading to a reduction in signal map creation time. The proposed interpolation method is used in conjunction with a particle filter algorithm to provide an accuracy level comparable to the state-of-the-art. We created signal maps at three separate locations using a 100%, 50%, 20%, and 10% scan coverage in order to evaluate the effectiveness of our interpolation on the localization error on a lower scan percentage. We evaluated our signal maps before and after interpolation using 16 tests which included both motion and stationary tests, as well as tests taken 2 and 3 weeks after the initial data gathering. We show that our interpolation method is able to reduce the effects of a dimensional mismatch between signal map reference point vectors and a test sample vector, as well as reduce the effects of signal map aging.