论文标题
F2IMU-R：低成本安装的双IMU和脚上的行人导航
f2IMU-R: Pedestrian Navigation by Low-cost Foot-Mounted Dual IMUs and Inter-foot Ranging
论文作者
论文摘要
脚踏式惯性传感器在许多室内或受GPS的应用程序中都很流行，包括但不限于医疗监测，步态分析，士兵和第一响应者定位。但是，脚部安装的惯性导航在很大程度上取决于零速度更新（ZUPT）的帮助，并且遇到了诸如前进漂移之类的固有问题。本文根据双脚架的低成本惯性测量单元（IMU）和脚内超声波范围实现行人导航系统。进行系统的可观察性分析是为了研究ZUPT测量的作用以及远距离测量在改善状态估计性方面的作用。基于卡尔曼的估计算法是在地球框架中机械化的，而不是在常见的局部级框架中，发现在抑制卡尔曼滤波中的线性化误差方面有效。还提出了地球框架中的椭圆形约束，以进一步限制高度漂移。模拟和实际场实验表明，所提出的方法比传统的行人导航方案具有更好的鲁棒性和定位精度（约0.1-0.2％的行驶距离）。
Foot-mounted inertial sensors become popular in many indoor or GPS-denied applications, including but not limited to medical monitoring, gait analysis, soldier and first responder positioning. However, the foot-mounted inertial navigation relies largely on the aid of Zero Velocity Update (ZUPT) and has encountered inherent problems such as heading drift. This paper implements a pedestrian navigation system based on dual foot-mounted low-cost inertial measurement units (IMU) and inter-foot ultrasonic ranging. The observability analysis of the system is performed to investigate the roles of the ZUPT measurement and the foot-to-foot ranging measurement in improving the state estimability. A Kalman-based estimation algorithm is mechanized in the Earth frame, rather than in the common local-level frame, which is found to be effective in depressing the linearization error in Kalman filtering. An ellipsoid constraint in the Earth frame is also proposed to further restrict the height drift. Simulation and real field experiments show that the proposed method has better robustness and positioning accuracy (about 0.1-0.2% travelled distance) than the traditional pedestrian navigation schemes do.
