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Spatial direction corrections to improve indoor localization using inertial navigation with sensors on a smartphone

We present results of an improved smartphone based inertial navigation based indoor localization system. Spatial constraints drawn from domain specific knowledge for direction correction and actual velocity model for velocity correction are applied to increase the accuracy by counteracting the accumulation of large drift caused by sensor reading errors. We investigated the accuracy of the algorithm with diverse experiments of walks along corridors. Our results show that the proposed method achieves a reduction in percentage error by 0.9% with a 30% less variance over Step and Heading approach proving the accuracy and robustness of proposed method. We also investigated the frequency of applying corrections and found that a 4-5% corrections per step is required for improved accuracy.