多连续测量偏差估计的GLR算法

G. Lundin, P. Mouyon, A. Manecy
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引用次数: 3

摘要

针对小型低空无人机GNSS中由于距离误差和信号阻塞导致的频繁出现和消失的多个连续测量偏差,提出了一种处理算法。该方法是对已知的GLR算法的扩展,基于修正的创新序列进行检测和基于最小二乘估计的识别阶段。在识别阶段提出了递归和非递归两种解决方案。在GNSS位置误差实例中,当误差频繁出现和消失时,本文算法的估计精度明显优于原算法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A GLR algorithm for multiple consecutive measurement bias estimation
This paper proposes an algorithm for handling multiple consecutive measurement biases that appear and disappear frequently, typically encountered in GNSS in small low flying UAVs due to range errors and signal blocking. The method is derived as an extension to the well known GLR algorithm and is based on a corrected innovation sequence for detection and an identification stage based on least square estimation. A recursive (RLS) and a non-recursive (LS) solution is proposed in the identification stage. Results in a GNSS position error example show that the proposed algorithms are significantly better than the original algorithm in terms of estimation precision when biases appear and disappear frequently.
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