Abstract
Accurate positioning is an important issue to enhance the reality and immersion of 3D urban navigation. The most common positioning technology is GPS, but it can't provide a continuous and accurate solution in dense urban canyons and indoor environments due to signal blockage, interference, or jamming, etc. This paper proposes an integrated GPS and multisensor pedestrian positioning system to bridge the gaps of GPS signal outages. It includes an OEM GPS receiver, a MEMS 3-axis accelerometer and a 2-axis digital compass. The positioning algorithm is a loosely coupled integration of GPS and Pedestrian Dead Reckoning sensors via a Kalman filter. Considering the future applications in embedded systems, the paper gives the minimum sampling rate of accelerometers for the step detection algorithm, which is a combination of three approaches: sliding window, peak detection and zero-crossing. Some field tests were conducted to evaluate the system performance.
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