Measurement Difference Method: A Universal Tool for Noise Identification

• 成果类型: Article
• 署名作者: Kost, Oliver; Dunik, Jindrich; Straka, Ondrej
• 署名单位: University of West Bohemia Pilsen
• 刊物名称: IEEE TRANSACTIONS ON AUTOMATIC CONTROL
• ISSN/ISSBN: 0018-9286
• DOI: 10.1109/TAC.2022.3160679
• 发表日期: 2023
• 页码: 1792-1799
• 关键词: Covariance matrices; Noise measurement; correlation; Time measurement; State-space methods; Probability density function; computational modeling; Correlation methods; identification; Linear systems; Index Terms; noise moments; noise parameters; state-space models

摘要

This article deals with noise identification of a system described by the linear time-varying state-space model using correlation methods. In particular, the stress is laid on the measurement difference method (MDM) as a universal tool allowing estimation of moments and parameters of the state and measurement noises. The recent results are summarized in a common framework and the full (and weighted) MDM implementation is developed. This implementation provides unbiased and weakly consistent estimate of an arbitrary raw or central moment of the state and measurement noises. The performance of the method is shown in a numerical study.