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We present a generalized velocity model to improve localization when using anInertial Navigation System (INS). This algorithm was applied to correct thevelocity of a smart phone based indoor INS system to increase the accuracy bycounteracting the accumulation of large drift caused by sensor reading errors.We investigated the accuracy of the algorithm with three different velocitymodels which were derived from the actual velocity measured at the hip ofwalking person. Our results show that the proposed method with Gaussianvelocity model achieves competitive accuracy with a 50\% less variance overStep and Heading approach proving the accuracy and robustness of proposedmethod. We also investigated the frequency of applying corrections and foundthat a minimum of 5\% corrections per step is sufficient for improved accuracy.The proposed method is applicable in indoor localization and trackingapplications based on smart phone where traditional approaches such as GNSSsuffers from many issues.

Novel velocity model to improve indoor localization using inertial navigation with sensors on a smartphone