Modern mobile phones are powerful devices that are equipped with an array of technologies of interest to the world of pedestrian navigation. On-board inertial sensors allow phones to be used for navigation in areas with limited or no GPS signal availability. An inherent problem with inertial navigation in the absence of GPS signals, i.e., in indoor environments, is that the low-cost MEMS sensors used in calculating users position suffer from errors which accumulate over time. These accumulated errors result in a drift of the navigation solution with respect to time even with appropriate error modeling. Though this drift exists in all scenarios where MEMS sensors are used for navigation, it makes the navigation solution completely useless for long periods of indoor navigation without external updates. Another problem associated with smartphone-based navigation is due to the fact that a user does not keep a phone precisely fixed in a specific orientation. As a user moves around their environment and interacts with the device, the device orientation and user orientation are free to change with respect to one another. Common examples of changing device orientation include those when texting, on ear, in pocket, on a belt, etc. The estimation of the device heading and the user heading especially when the device heading is changing with respect to the user's heading is a challenging task and the effects of any errors here can significantly reduce the accuracy of the navigation solution.
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