Next-Generation Inertial Navigation Computation Based on Functional Iteration

Yuanxin Wu
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引用次数: 8

Abstract

Inertial navigation computation is to acquire the attitude, velocity and position information of a moving body by integrating inertial measurements from gyroscopes and accelerometers. Over half a century has witnessed great efforts in coping with the motion non-commutativity errors to accurately compute the navigation information as far as possible, so as not to comprise the quality measurements of inertial sensors. Highly dynamic applications and the forthcoming cold-atom precision inertial navigation systems demand for even more accurate inertial navigation computation. The paper gives birth to an ultimate inertial navigation algorithm to fulfill that demand, named the iNavFIter, which is based on a brand new framework of functional iterative integration and Chebyshev polynomials. Remarkably, the proposed iNavFIter reduces the non-commutativity errors to almost machine precision, namely, the coning/sculling/scrolling errors that have perplexed the navigation community for long. Numerical results are provided to demonstrate its accuracy superiority over the-state-of-the-art inertial navigation algorithms at affordable computation cost.
基于函数迭代的下一代惯性导航计算
惯性导航计算是将陀螺仪和加速度计的惯性测量值综合起来,获取运动物体的姿态、速度和位置信息。半个多世纪以来,人们一直在努力解决运动非交换性误差,以尽可能准确地计算导航信息,从而不影响惯性传感器的质量测量。高动态应用和即将到来的冷原子精密惯性导航系统需要更精确的惯性导航计算。为了满足这一需求,本文提出了一种基于全新泛函迭代积分和切比雪夫多项式框架的终极惯性导航算法iNavFIter。值得注意的是,所提出的inavfilter将非交换性误差降低到几乎机器精度,即长期困扰导航界的圆锥/划水/滚动误差。数值结果表明,该方法在计算成本低廉的情况下,在精度上优于当前的惯性导航算法。
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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