摘要
在行人惯性导航中,零速检测是实现速度误差清零和导航误差估计的前提,有着重要的作用。针对行人运动过程中零速区间时间间隔短难以检测的问题,提出了一种基于人体脚部运动特征的零速检测算法,将步行运动抽象成了一个包含4个隐含状态与15个观测量的隐马尔可夫模型,并阐述了模型构建机理。利用Baum—Welch算法训练和优化模型参数,提高了检测准确率。实验结果表明:所提出的方法零速检测效果较好,且采用该方法的行人惯性导航系统,其定位误差约为行进距离的0.73%,定位精度较高。
In pedestrian inertial navigation, zero velocity detection is premise to reset velocity errors and estimate navigation error. Aiming at problem that time interval of zero velocity is short and it is difficult to detect in pedestrian moving process, a zero velocity detection algorithm based on human foot movement characteristics is proposed, where walking motion is abstracted into a hidden Markov model with 4 hidden states and 15 observations, and construction mechanism of model is described. The model parameters are trained and optimized by Baum-Welch algorithm and detection accuracy is improved. Experimental results show that the proposed method has better effect on zero velocity detection, and the positioning error of pedestrian inertial navigation system using this method is about 0.73 % of the travel distance, and the positioning precision is high.
出处
《传感器与微系统》
CSCD
2016年第3期147-150,153,共5页
Transducer and Microsystem Technologies
基金
国家自然科学基金资助项目(61471046)
北京市科技计划课题项目(Z131100005313009)
北京市教委创新能力提升计划项目(PXM2015-014224-000029)
