基于动作识别和步幅估计的步行者航位推算

针对步行者的运动特点,采用和传统航位推算不同的思路,提出低成本步行者航位推算方案.通过分析安装在步行者身体上的加速度计输出采样,采用支持向量机识别步行者运动状态,并采用滑动窗长度可变的峰值捕获算法测算实时步频.为提高峰值捕获正确率,使用Daubechies 4作为基函数的小波滤波器对加速度计的原始输出进行平滑.通过实验拟合出步幅与步频的关系模型,并以此估算步行者实时步幅作为步行者实时移动距离,再结合电磁罗盘的航向角输出,完成步行者航位推算.经实地实验验证,该方案具有较好的定位效果.

Pedestrian Dead Reckoning Based on Activity Recognition and Stride Assessment

This paper addressed an approach of low cost pedestrian dead reckoning by using different idea from traditional dead reckoning.Activity recognition using support vector machines(SVM) was realized by analyzing the readings from the accelerometer attached to the pedestrian.And the peak detection algorithm taking advantage of alterable length sliding window was employed to estimate the real-time step frequency,Daubechies 4(DB4) wavelet base was introduced to smooth the raw data from accelerometer to enhance the performance of peak detection.Then the real-time stride was assessed as the locomotion distance according to the model of relationship between the stride and step frequency.Finally,the pedestrian dead reckoning was implemented by coupling the distance with the azimuth.And the results of experiments demonstrate the effectiveness of the proposed approach.