Theoretical Limitations of Allan Variance-based Regression for Time Series Model Estimation

被引:22
|
作者
Guerrier, Stephane [1 ]
Molinari, Roberto [2 ,3 ]
Stebler, Yannick [4 ]
机构
[1] Univ Illinois, Dept Stat, Champaign, IL 61820 USA
[2] Univ Geneva, Res Ctr Stat, CH-1211 Geneva, Switzerland
[3] Univ Geneva, Geneva Sch Econ & Management, CH-1211 Geneva, Switzerland
[4] U Blox, CH-8800 Thalwil, Switzerland
关键词
Error modeling; inertial measurement units; latent time series models; sensor calibration; state space models;
D O I
10.1109/LSP.2016.2541867
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
This letter formally proves the statistical inconsistency of the Allan variance-based estimation of latent (composite) model parameters. This issue has not been sufficiently investigated and highlighted since it is a technique that is still being widely used in practice, especially within the engineering domain. Indeed, among others, this method is frequently used for inertial sensor calibration, which often deals with latent time series models and practitioners in these domains are often unaware of its limitations. To prove the inconsistency of this method, we first provide a formal definition and subsequently deliver its theoretical properties, highlighting its limitations by comparing it with another statistically sound method.
引用
收藏
页码:595 / 599
页数:5
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