摘要
伴随城市化的进程推进,人们对于室内定位技术的精度要求日益增长,室内定位的研究也受到了社会的广泛关注。本文在传统的波峰波谷检测算法的基础上做出改进,设计了多重门限检测的波谷检测算法。该算法通过波峰值或者波谷值判断行人的运动状态,然后检测相邻波谷之间的时间差和波谷与波峰之间的时间差是否满足阈值条件,消除伪波峰和伪波谷的影响,实现计步。同时,本文也使用了卡尔曼滤波降低原始数据的噪声,平滑曲线。实验表明本文算法提高了计步的准确性,能够应用于计步器、室内定位等领域。
With the advancement of urbanization, people are increasingly demanding the accuracy of indoor positioning technology. The research on indoor positioning has also received widespread attention from the society. This paper improves on the traditional wave and valley detection algorithm, and designs a valley detection algorithm for multiple threshold detection. This algorithm uses the wave peak or valley value to determine the pedestrian’s movement state, and then detects the time difference and valley between adjacent valleys. Whether the time difference between the peak and the peak meets the threshold condition, eliminates the effects of pseudo peaks and pseudo valleys, and realizes step counting. At the same time, this paper also uses Kalman filtering to reduce the noise of the original data and smooth the curve. Experiments show that the algorithm in this paper improves the step counting. The accuracy can be applied to pedometers, indoor positioning and other fields.
出处
《软件工程与应用》
2020年第1期93-101,共9页
Software Engineering and Applications
