基于频域特征分析和步态识别的步长估算方法,用于行人惯性计算

IF 1.6 4区 工程技术 Q3 INSTRUMENTS & INSTRUMENTATION
Guosheng Deng, Wei Zhang, Zhitao Wu, Minglei Guan, Dejin Zhang
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引用次数: 0

摘要

目的步长是行人惯性导航(PDR)的关键因素,影响定位精度和可靠性。传统方法难以处理动态步态的步长估计,误差较大,不适应真实行走。本文旨在提出一种基于频域特征分析和步态识别的步长估算方法,用于 PDR,该方法考虑了实时步态的影响。设计/方法/途径新的步长估算方法将行人的加速度从时域转换到频域,获得了行人的步态特征,并与不同的步行速度相匹配。原创性/价值提出了在快速傅立叶变换中使用滑动窗口策略来实现加速度的频域分析,并提出了一种快速自适应步态识别机制来识别行人的步态。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A step length estimation method based on frequency domain feature analysis and gait recognition for pedestrian dead reckoning

Purpose

Step length is a key factor for pedestrian dead reckoning (PDR), which affects positioning accuracy and reliability. Traditional methods are difficult to handle step length estimation of dynamic gait, which have larger error and are not adapted to real walking. This paper aims to propose a step length estimation method based on frequency domain feature analysis and gait recognition for PDR, which considers the effects of real-time gait.

Design/methodology/approach

The new step length estimation method transformed the acceleration of pedestrians from time domain to frequency domain, and gait characteristics of pedestrians were obtained and matched with different walking speeds.

Findings

Many experiments are conducted and compared with Weinberg and Kim models, and the results show that the average errors of the new method were improved by about 2 meters to 5 meters. It also shows that the proposed method has strong stability and device robustness and meets the accuracy requirements of positioning.

Originality/value

A sliding window strategy used in fast Fourier transform is proposed to implement frequency domain analysis of the acceleration, and a fast adaptive gait recognition mechanism is proposed to identify gait of pedestrians.

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来源期刊
Sensor Review
Sensor Review 工程技术-仪器仪表
CiteScore
3.40
自引率
6.20%
发文量
50
审稿时长
3.7 months
期刊介绍: Sensor Review publishes peer reviewed state-of-the-art articles and specially commissioned technology reviews. Each issue of this multidisciplinary journal includes high quality original content covering all aspects of sensors and their applications, and reflecting the most interesting and strategically important research and development activities from around the world. Because of this, readers can stay at the very forefront of high technology sensor developments. Emphasis is placed on detailed independent regular and review articles identifying the full range of sensors currently available for specific applications, as well as highlighting those areas of technology showing great potential for the future. The journal encourages authors to consider the practical and social implications of their articles. All articles undergo a rigorous double-blind peer review process which involves an initial assessment of suitability of an article for the journal followed by sending it to, at least two reviewers in the field if deemed suitable. Sensor Review’s coverage includes, but is not restricted to: Mechanical sensors – position, displacement, proximity, velocity, acceleration, vibration, force, torque, pressure, and flow sensors Electric and magnetic sensors – resistance, inductive, capacitive, piezoelectric, eddy-current, electromagnetic, photoelectric, and thermoelectric sensors Temperature sensors, infrared sensors, humidity sensors Optical, electro-optical and fibre-optic sensors and systems, photonic sensors Biosensors, wearable and implantable sensors and systems, immunosensors Gas and chemical sensors and systems, polymer sensors Acoustic and ultrasonic sensors Haptic sensors and devices Smart and intelligent sensors and systems Nanosensors, NEMS, MEMS, and BioMEMS Quantum sensors Sensor systems: sensor data fusion, signals, processing and interfacing, signal conditioning.
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