Pedestrian step length modeling method based on inertial data time-frequency domain feature extraction

Abstract

The invention provides a pedestrian step length modeling method based on inertial data time-frequency domain feature extraction. The method comprises the following steps of firstly, acquiring the inertial data under an unconventional gait, and segmenting the inertial data of different gaits; then calculating the stride frequency and acceleration variance in a single-step period, and constructing a time domain linear step model; performing fractional Fourier transform on a triaxial acceleration vector and signal in the single-step period, calculating a standard deviation factor and a quartile difference factor of the transformed acceleration signal, and constructing a frequency domain linear step model; and finally, fusing the time domain linear step length model and the frequency domain linear step length model by using a weighting method to obtain a fused step length model. According to the method, through the extraction and fusion of the time-frequency domain features of the inertial data, pedestrian dead reckoning precision based on an inertial sensor under multiple motion states is improved, and the technical problem that an existing step length modeling method cannot be directly applied to the unconventional gaits, such as running, side walking, backward walking, etc., is solved.

Description

technical field [0001] The invention belongs to the technical field of pedestrian navigation, and in particular relates to a pedestrian step modeling method based on time-frequency domain feature extraction of inertial data. Background technique [0002] The waist-bound pedestrian navigation system connects the micro-inertial sensor to the waist of the human body, and uses the dead reckoning method to update the position. When the traditional inertial sensor-based pedestrian navigation method performs dead reckoning, the step length is obtained by modeling the acceleration signal. The conventional modeling method mainly considers the normal walking gait and cannot be directly applied to running, walking sideways, and backwards. Walking and other unconventional gaits, so a pedestrian step length modeling method suitable for walking and unconventional gaits is needed. Contents of the invention [0003] The purpose of the present invention is to provide a pedestrian step len...

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Problems solved by technology

[0003] The purpose of the present invention is to provide a pedestrian step length modeling method based on the time-frequency domain feature extraction of inertial data, through the extraction and fusion of the time-frequency domain features of inertial data, the pedestrian step size model under different stances is obtained, and the improvement is improved. The dead reckoning accuracy of pedestrians based on inertial sensors in multi-motion state solves the technical problem that existing step length modeling methods cannot be directly applied to unconventional gaits such as running, walking sideways, and walking backwards

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