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An autonomous hybrid navigation filter using earth magnetic field measurements for low earth orbit satellite

机译:使用地球磁场测量的低地轨道卫星自主混合导航滤波器

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摘要

The primary focus of this paper is the design of an hybrid navigation filter algorithm based on Extended Kalman Filter (EKF), which autonomously and simultaneously estimates three axis attitude, rate and orbit using only Earth Magnetic Field (EMF) measurements. The presented hybrid navigation filter algorithm is based on the laws of orbital mechanics, attitude dynamic and the EMF measurements. According to our simulations study, the developed hybrid navigation filter shows the capability of estimating the attitude with accuracy less than 1.5 deg and rate order is 1.5 milli-deg/sec. In orbit estimation, the filter is able of estimating the position with accuracy of 15.5 km and velocity 0.013 km/s. Based upon results, the orbit and attitude accuracy is sufficient for Low Earth Orbit (LEO) satellite with coarse accuracy mission requirements and it can be used as a backup system to provide redundancy.
机译:本文的主要重点是基于扩展卡尔曼滤波器(EKF)的混合导航滤波器算法的设计,该算法仅使用地球磁场(EMF)测量值即可自动并同时估计三个轴的姿态,速率和轨道。提出的混合导航滤波算法是基于轨道力学,姿态动力学和EMF测量的定律。根据我们的仿真研究,开发的混合导航滤波器显示出以低于1.5度的精度和速率阶数为1.5毫度/秒来估计姿态的能力。在轨道估算中,滤波器能够以15.5 km的精度和0.013 km / s的速度估算位置。根据结果​​,轨道和姿态精度足以满足任务精度要求较低的低地球轨道(LEO)卫星,并且可以用作备用系统以提供冗余。

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