Polarized skylight/MIMU/geomagnetic orientation algorithm based on adaptive Kalman filter

Mingyao Yuan, Xiaofeng He, Xiaoping Hu, Lilian Zhang, Hang Shang
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引用次数: 2

Abstract

This paper presents an adaptive Kalman filter algorithm for polarized skylight/geomagnetic/GNSS/MIMU bionic integrated navigation system. In the bionic navigation system, the magnetometer, polarized light camera, and satellite antenna are susceptible to environmental interference, which affects the accuracy of the navigation solution. In this paper, a algorithm based on Sage-Husa Kalman filter is given for navigation. The algorithm uses a polarized light camera and a magnetometer to obtain the heading angles information, a satellite receiver to collect speed and position information, and use these messages to estimate and adjust the filter parameters to get an optimal estimate of the system heading angle. In this paper, two land vehicle tests were conducted, and the heading angles were increased by 20.49% and 9.59%, respectively, which proved the effectiveness and availability of the given method.
基于自适应卡尔曼滤波的极化天窗/MIMU/地磁定向算法
针对偏振光/地磁/GNSS/MIMU仿生组合导航系统,提出了一种自适应卡尔曼滤波算法。在仿生导航系统中,磁力计、偏振光相机和卫星天线容易受到环境干扰,从而影响导航方案的精度。本文给出了一种基于Sage-Husa卡尔曼滤波的导航算法。该算法利用偏振光相机和磁力计获取航向角信息,利用卫星接收机采集速度和位置信息,利用这些信息估计和调整滤波参数,得到系统航向角的最优估计值。本文通过两次地面车辆试验,分别提高了航向角20.49%和9.59%,验证了所提方法的有效性和有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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