INS errors compensation algorithm based on Luenberger Observer

I. Rataichuk, V. Kortunov
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Abstract

INS errors present one of the major problems in development of navigation systems for aerial vehicles. This problem is especially actual for Mini and Micro UAVs where INS is based on MEMS which possesses high spectral density noise and instability. Another problem for Micro UAVs is restrictions applied for onboard hardware. Autopilots designed for this UAVs utilizes microcontrollers for CPU, which executes functions of flight control, navigation system, payload control and etc. So one needs simple and reliable algorithm for errors compensation in this particular types of autopilots. Existing algorithms, such as Complementary Filters or Kalman Filter, already are used in INS and performs very well. But there is always a way for improvements. Such improvement is a Luenberger Observer. It can estimate navigation and sensors errors. This algorithm is simpler, thus faster, than Kalman Filter. In this paper implementation of Luenberger Observer in Attitude and Heading Reference System (AHRS) (specific type of INS) is considered. The simulation of algorithm performance using real onboard data and feasibility of its implementation in navigation systems is shown.
基于Luenberger观测器的惯导系统误差补偿算法
惯导系统误差是飞行器导航系统开发中的主要问题之一。对于基于MEMS的小型和微型无人机来说,这一问题尤其现实,这类无人机具有高频谱密度噪声和不稳定性。微型无人机的另一个问题是机载硬件的限制。为该型无人机设计的自动驾驶仪采用单片机作为CPU,执行飞行控制、导航系统、载荷控制等功能。因此在这种特殊类型的自动驾驶仪中需要简单可靠的误差补偿算法。现有的算法,如互补滤波器或卡尔曼滤波器,已经在惯性导航系统中使用,并取得了很好的效果。但总有改进的办法。这样的改进是一个卢恩伯格观察家。它可以估计导航和传感器的误差。该算法比卡尔曼滤波更简单,因此速度更快。本文研究了Luenberger观测器在姿态和航向参考系统(AHRS)中的实现。最后利用实际机载数据对算法性能进行了仿真,证明了算法在导航系统中实现的可行性。
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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