TY - Jour A2 - 王，Qingling Au - Ji，苗oxin au - liu，金浩奥 - 徐，湘波奥武，玉阳奥 - 路，zhenchun py - 2020 da - 2020/01/08 - 2020/01/08 Ti改进了行人定位惯性基于自适应梯度下降和双约束扩展卡尔曼滤波器SP-4361812 VL-2020 AB的传感器 - 基于微惯性测量单元（MIMU）的脚踏惯性步位定位系统（FIPPS）是一个不错的选择全球导航卫星系统无法使用时森林消防员。零速度更新（zupt）提供了一种用于减少由惯性导航的积分计算引起的累积定位误差的解决方案。然而，Zupt的性能受到MIMU的低精度和高噪声的高度影响。通过在站立相期间的加速度和陀螺仪的漂移的零点偏移来减小常规ZUPT的准确性。提出了一种基于自适应梯度下降算法（AGDA）的初始对准算法。在步进阶段，扩展的卡尔曼滤波器（EKF）通常用于校正轨道估计中的姿态和位置。然而，EKF的测量噪声受高频加速度和角速度的影响。因此，姿态和位置的准确性将减少。 A double-constrained extended Kalman filtering (DEKF) is proposed. An adaptive parameter positively correlated with the acceleration and angular velocity is set, and the measurement noise in the DEKF is adaptively adjusted. The performance of the proposed method is verified by implementing the pedestrian test trajectory using MPU-9150 MIMU manufactured by InvenSense. The results show that the attitude error of the AGDA is 33.82% less than that of the conventional GDA. The attitude error of DEKF is 21.70% less than that of the conventional EKF. The experimental results verify the effectiveness and applicability of the proposed method. SN - 1076-2787 UR - https://doi.org/10.1155/2020/4361812 DO - 10.1155/2020/4361812 JF - Complexity PB - Hindawi KW - ER -