Satellite-based radionavigation systems provide accurate and reliable positioning and navigation whenever the satellite-to-receiver path is free from obstacles. In personal navigation this condition cannot always be guaranteed. Many applications require accurate position solutions in downtown areas and indoor. Due to the very low transmission power and signal delays caused by the obstacles, the performance of satellite navigation systems decreases in these environments. Conversely, self-contained sensors can provide navigation information in any environment. In the doctoral thesis of M.Sc. Jussi Collin, the aim was to construct a framework for algorithms that can take advantage of the sensor information, but are much less sensitive to large measurement errors than the traditional inertial navigation algorithms.

Special attention of the thesis was brought to algorithms that provide sensor navigation information independently of the unit orientation. A technique that classifies the user motion using only sensor information independent of orientation was developed. This method is developed from the navigation algorithm point of view, where successful detection of a walking user and a stationary user enables usage of specific navigation algorithms that are less sensitive to sensor errors. The same algorithm is useful in other applications requiring situational awareness of the user’s mode of transportation.

During the research, it was found that accurate satellite signal measurements, combined with the sensor data can be used to obtain the first position fix with less than four visible satellites. The cases shown in this thesis are a 3-satellite solution without external altitude information, and a 2-satellite solution with external altitude information. The accuracy of these solutions is highly sensitive to measurement errors, but the methods can be used to obtain a rough position estimate in situations where stand-alone systems could not provide position information at all.

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