On Consistency of EKF for Pedestrian Dead Reckoning with Foot Mounted IMU

Bolotin, Yury; Bragin, Alexander; Gulevskiy, Daniil

doi:10.23919/icins43215.2020.9133753

Cited by 5 publications

(2 citation statements)

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“…One of the popular micromechanical IMU calibration methods is the so-called calibration without external equipment [ 13 , 14 ], etc., which we have used a lot in our experiments in pedestrian navigation [ 9 ]. We have found (the results are not included here) that the new algorithm performs considerably better when it comes to the angular rate calibration of the sensors because their scale factors are estimated better with relatively fast and lengthy rotations, which are impossible to perform by hand.…”

Section: Discussionmentioning

confidence: 99%

“…When we consider calibrating low-cost micromechanical IMUs, which are now broadly used, in, for instance, biomechanics, robotics or pedestrian dead reckoning (see earlier work [ 6 ], later [ 7 , 8 ], or recent [ 9 , 10 , 11 ]), the calibration procedure should be straightforward and reliable. In most practical cases, using a precise turntable is impossible.…”

Section: Introductionmentioning

confidence: 99%

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Turntable IMU Calibration Algorithm Based on the Fourier Transform Technique

Bolotin

Savin

2023

Sensors

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The paper suggests a new approach to calibration of a micromechanical inertial measurement unit. The data are collected on a simple rotating turntable with horizontal (or close to) rotation axis. For such a turntable, an electric screwdriver with fairly low rotation rate can be used. The algorithm is based on the Fourier transform applied to the rotation experimental data, implemented as FFT. The frequencies and amplitudes of the spectral peaks are calculated and collected in a small set of data, and calibration is done explicitly with these data. Calibration of an accelerometer triad and choosing the IMU coordinate frame are reduced to approximating the collected data with an ellipsoid in three dimensions. With rotation frequency calculated as the peak frequency of accelerometer readings, calibration of the gyros is a straightforward linear least square problem. The algorithm is purely algebraic, requires no iterations and no initial guess on the parameters, and thus encounters no convergence problems. The algorithm was tested both with simulated and experimental data, with some promising results.

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Section: Discussionmentioning

confidence: 99%