针对MEMS陀螺仪输出信号随机漂移噪声较大的问题,结合室内行人导航应用需求,在分析传统小波阈值去噪方法的基础上,设计了一种优化的小波阈值去噪方法。该方法构造了一种小波系数介于软硬阈值之间的连续小波阈值函数,在一定程度上克服了...针对MEMS陀螺仪输出信号随机漂移噪声较大的问题,结合室内行人导航应用需求,在分析传统小波阈值去噪方法的基础上,设计了一种优化的小波阈值去噪方法。该方法构造了一种小波系数介于软硬阈值之间的连续小波阈值函数,在一定程度上克服了软硬阈值函数自身固有的缺陷。最后,分别采用传统阈值去噪法与优化小波阈值去噪法对行人导航系统中采集到的MEMS陀螺仪数据进行去噪处理,结果表明,相对传统的软硬阈值滤波法,优化阈值去噪法处理后的信号获得了更高的信噪比40.8748 d B,同时均方差降低了40%,MEMS陀螺信号中的随机噪声被有效剔除,满足了行人导航后续研究工作的需求。展开更多
In outdoor environments, GPS is often used for pedestrian navigation by utilizing its signals for position computation, but in indoor or semi-obstructed environments, GPS signals are often unavailable. Therefore, pede...In outdoor environments, GPS is often used for pedestrian navigation by utilizing its signals for position computation, but in indoor or semi-obstructed environments, GPS signals are often unavailable. Therefore, pedestrian navigation for these environments should be realized by the integration of GPS and inertial navigation system （INS）. However, the lowcost INS could induce errors that may result in a large position drift. The problem can be minimized by mounting the sensors on the pedestrian＇s foot, using zero velocity update （ZUPT） method with the standard navigation algorithm to restrict the error growth. However, heading drift still remains despite using ZUPT measurements since the heading error is unobservable. Also, tbot mounted INS suffers from the initialization ambiguity of position and heading from GPS. In this paper, a novel algorithm is developed to mitigate the heading drift problem when using ZUPT. The method uses building lay- out to aid the heading measurement in Kalman filter, and it could also be combined for the initial- ization. The algorithm has been investigated with real field trials using the low cost Microstrain 3DM-GX3-25 inertial sensor, a Leica GS10 GPS receiver and a uBlox EVK-6T GPS receiver. It could be concluded that the proposed method offers a significant improvement in position accuracy for the long period, allowing pedestrian navigation for nearly40 min with mean position error less than 2.8 m. This method also has a considerable effect on the accuracy of the initialization.展开更多
对于手持式移动设备的定位导航需求,特别是在室内无法接收到GPS信号的恶劣环境,提出了一种基于智能手机上的磁力计,陀螺仪和加速度计(magnetic,angular rate and gravity,MARG)传感器的行人导航算法,该算法在行人航迹推算的基础上,利用...对于手持式移动设备的定位导航需求,特别是在室内无法接收到GPS信号的恶劣环境,提出了一种基于智能手机上的磁力计,陀螺仪和加速度计(magnetic,angular rate and gravity,MARG)传感器的行人导航算法,该算法在行人航迹推算的基础上,利用数字低通滤波器滤波后的加速度计三轴模值数据,对行人步态进行检测,采用经验模型对行人步长进行估计,并结合扩展卡尔曼滤波器,采用自适应的方式实时调整测量噪声协方差矩阵,将MARG传感器融合数据用于最佳航向角估算。在智能手机平台上进行测试验证,实验结果表明,在无磁或有磁干扰环境下,所提出的行人导航算法均可保证准确、可靠、持续的位置信息。展开更多
文摘针对MEMS陀螺仪输出信号随机漂移噪声较大的问题,结合室内行人导航应用需求,在分析传统小波阈值去噪方法的基础上,设计了一种优化的小波阈值去噪方法。该方法构造了一种小波系数介于软硬阈值之间的连续小波阈值函数,在一定程度上克服了软硬阈值函数自身固有的缺陷。最后,分别采用传统阈值去噪法与优化小波阈值去噪法对行人导航系统中采集到的MEMS陀螺仪数据进行去噪处理,结果表明,相对传统的软硬阈值滤波法,优化阈值去噪法处理后的信号获得了更高的信噪比40.8748 d B,同时均方差降低了40%,MEMS陀螺信号中的随机噪声被有效剔除,满足了行人导航后续研究工作的需求。
文摘In outdoor environments, GPS is often used for pedestrian navigation by utilizing its signals for position computation, but in indoor or semi-obstructed environments, GPS signals are often unavailable. Therefore, pedestrian navigation for these environments should be realized by the integration of GPS and inertial navigation system （INS）. However, the lowcost INS could induce errors that may result in a large position drift. The problem can be minimized by mounting the sensors on the pedestrian＇s foot, using zero velocity update （ZUPT） method with the standard navigation algorithm to restrict the error growth. However, heading drift still remains despite using ZUPT measurements since the heading error is unobservable. Also, tbot mounted INS suffers from the initialization ambiguity of position and heading from GPS. In this paper, a novel algorithm is developed to mitigate the heading drift problem when using ZUPT. The method uses building lay- out to aid the heading measurement in Kalman filter, and it could also be combined for the initial- ization. The algorithm has been investigated with real field trials using the low cost Microstrain 3DM-GX3-25 inertial sensor, a Leica GS10 GPS receiver and a uBlox EVK-6T GPS receiver. It could be concluded that the proposed method offers a significant improvement in position accuracy for the long period, allowing pedestrian navigation for nearly40 min with mean position error less than 2.8 m. This method also has a considerable effect on the accuracy of the initialization.
文摘对于手持式移动设备的定位导航需求,特别是在室内无法接收到GPS信号的恶劣环境,提出了一种基于智能手机上的磁力计,陀螺仪和加速度计(magnetic,angular rate and gravity,MARG)传感器的行人导航算法,该算法在行人航迹推算的基础上,利用数字低通滤波器滤波后的加速度计三轴模值数据,对行人步态进行检测,采用经验模型对行人步长进行估计,并结合扩展卡尔曼滤波器,采用自适应的方式实时调整测量噪声协方差矩阵,将MARG传感器融合数据用于最佳航向角估算。在智能手机平台上进行测试验证,实验结果表明,在无磁或有磁干扰环境下,所提出的行人导航算法均可保证准确、可靠、持续的位置信息。
