Optimal enforcement of causality in non-parametric transfer function estimation

被引：2

作者：

González, Rodrigo A. ^{[1
]}

Valenzuela, Patricio E. ^{[2
]}

Rojas, Cristian R. ^{[2
]}

Rojas, Ricardo A. ^{[1
]}

机构：

[1] Electronic Engineering Department, Universidad Técnica Federico Santa María, Valparaíso,2390123, Chile

[2] Department of Automatic Control and ACCESS Linnaeus Centre, KTH Royal Institute of Technology, Stockholm,10044, Sweden

来源：

IEEE Control Systems Letters | 2017年 / 1卷 / 02期

关键词：

Spectral density - Transfer functions - Frequency response - Parameter estimation;

D O I：

10.1109/LCSYS.2017.2713821

中图分类号：

O1 [数学];

学科分类号：

0701 ; 070101 ;

摘要：

Traditionally, non-parametric impulse and frequency response functions are estimated by taking the ratio of power spectral density estimates. However, this approach may often lead to non-causal estimates. In this letter, we derive a closed form expression for the impulse response estimator by smoothed empirical transfer function estimate, which allows optimal enforcement of causality on non-parametric estimators based on spectral analysis. The new method is shown to be asymptotically unbiased and of minimum covariance in a positive semidefinite sense among a broad class of linear estimators. Numerical simulations illustrate the performance of the new estimator. © 2017 IEEE.

引用

页码：268 / 273