Analysis and modeling of inertial sensors using Allan variance
Analysis and modeling of inertial sensors using Allan variance
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DOI：
10.1109/tim.2007.908635
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发表时间：
2008-01-01
影响因子：
5.6
通讯作者：
Niu, Xiaoji
中科院分区：
文献类型：
--
作者：
EI-Sheimy, Naser;Hou, Haiying;Niu, Xiaoji
众所周知，惯性导航系统可以在短时间内提供高精度的位置、速度和姿态信息。然而，它们的准确性随着时间的推移而迅速下降。为了准确估计导航信息，需要对传感器的误差分量进行建模。已经设计了几种方差技术用于惯性传感器误差的随机建模。它们基本上非常相似，主要区别在于各种信号处理，通过加权函数、窗函数等，被合并到分析算法中，以便实现用于改进模型表征的特定期望结果。最简单的是Allan方差。Allan方差是将均方根（RMS）随机漂移误差表示为平均时间的函数的方法。它计算起来很简单，解释和理解起来也相对简单。Allan方差法可用于确定引起数据噪声的潜在随机过程的特征。该技术可用于通过对整个数据长度执行某些操作来表征惯性传感器数据中的各种类型的误差项。本文采用Allan方差技术对不同等级的惯性测量组合中的惯性传感器进行误差分析和建模。通过对整个数据长度进行简单的运算，获得特性曲线，其检查提供了惯性传感器输出数据中包含的各种随机误差的系统表征。作为一个可直接测量的量，Allan方差可以提供关于各种误差项的类型和大小的信息。本文介绍了用Allan方差对惯性传感器误差项进行建模的理论基础及其在不同等级惯性传感器建模中的实现方法。
It is well known that inertial navigation systems can provide high-accuracy position, velocity, and attitude information over short time periods. However, their accuracy rapidly degrades with time. The requirements, for an accurate estimation of navigation information necessitate the modeling of the sensors' error components. Several variance techniques have been devised for stochastic modeling of the error of inertial sensors. They are basically very similar and primarily differ in that various signal processings, by way of weighting functions, window functions, etc., are incorporated into the analysis algorithms in order to achieve a particular desired result for improving the model characterizations. The simplest is the Allan variance. The Allan variance is a method of representing the root means square (RMS) random-drift error as a function of averaging time. It is simple to compute and relatively simple to interpret and understand. The Allan variance method can be used to determine the characteristics of the underlying random processes that give rise to the data noise. This technique can be used to characterize various types of error terms in the inertial-sensor data by performing certain operations on the entire length of data. In this paper, the Allan variance technique will be used in analyzing and modeling the error of the inertial sensors used in different grades of the inertial measurement units. By performing a simple operation on the entire length of data, a characteristic curve is obtained whose inspection provides a systematic characterization of various random errors contained in the inertial-sensor output data. Being a directly measurable quantity, the Allan variance can provide information on the types and magnitude of the various error terms. This paper covers both the theoretical basis for the Allan variance for modeling the inertial sensors' error terms and its implementation in modeling different grades of inertial sensors.