Running pace estimation using complementary filter based fusion of GPS and pedometer data

Abstract

This paper presents an application of complementary filtration for estimating running pace using GPS and pedometer data. In the approach presented two information sources are fused with dynamically adjusted importance factors. In the case of poor GPS signal the pedometer data are gained by the filter, and otherwise. The method proposed was verified using multiple simulations. An exemplary one is presented and discussed in the paper.