The development of lightweight MEMS sensors makes it possible to use inertial navigation for restoration of pedestrian trajectory. The main drawback of the current generation of MEMS sensors is their high level of noise and the bias instability due to incomplete factory calibration. One way to solve this problem is to create a multi-component Inertial Measurement Unit. This paper describes data processing algorithms for MEMS based multi-component Inertial Measurement Unit for indoor navigation. The module is constructed in the form of a truncated pyramid with five inertial sensors mounted on its planes at different angles relative to each other. The data from each sensor is fused to increase the accuracy of trajectory estimation.
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