Abstract

An accurate orientation is crucial to a satisfactory position in pedestrian navigation. The orientation estimation, however, is greatly affected by errors like the biases of gyroscopes. In order to minimize the error in the orientation, the biases of gyroscopes must be estimated and subtracted. In the state of the art it has been proposed, but not proved, that the estimation of the biases can be accomplished using magnetic field measurements. The objective of this work is to evaluate the effectiveness of using magnetic field measurements to estimate the biases of medium-cost micro-electromechanical sensors (MEMS) gyroscopes. We carry out the evaluation with experiments that cover both, quasi-error-free turn rate and magnetic measurements and medium-cost MEMS turn rate and magnetic measurements. The impact of different homogeneous magnetic field distributions and magnetically perturbed environments is analyzed. Additionally, the effect of the successful biases subtraction on the orientation and the estimated trajectory is detailed. Our results show that the use of magnetic field measurements is beneficial to the correct biases estimation. Further, we show that different magnetic field distributions affect differently the biases estimation process. Moreover, the biases are likewise correctly estimated under perturbed magnetic fields. However, for indoor and urban scenarios the biases estimation process is very slow.

Highlights

  • In Europe and North America, people spend more than 90% of their time indoors [1], which is a satellite-denied environment

  • The aim of this section is endorsing the previous results obtained with emulated magnetic field measurements and quasi-error-free turn rate measurements with added constant biases

  • This work aims at evaluating experimentally the effectiveness of using magnetic field measurements to estimate the biases of medium-cost micro-electromechanical sensors (MEMS) gyroscopes

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Summary

Introduction

In Europe and North America, people spend more than 90% of their time indoors [1], which is a satellite-denied environment. The indoor scenario is the base of highly demanded mass market applications like guidance in shopping malls or professional applications for rescue personnel, among others. The navigation of pedestrians based on inertial measurement units has experienced great growth in recent years due to the miniaturization and the price reduction of the micro-electromechanical sensors (MEMS). These sensors are nowadays embedded in every smartphone, that is usually carried in the front pocket of the trousers. MEMS inertial sensors are plentiful and inexpensive. Their noise characteristics cause ever growing errors when processing their measurements

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