Unobservable Systems: No Problem for Noise Identification

2025/05/29 by Oliver Kost, Jindřich Duník, Kost, Oliver +5
Engineering · #Control Systems and Identification #FOS: Electrical engineering #Signal Processing (eess.SP) #electronic engineering #information engineering

paper · pdf · doi:10.48550/arxiv.2505.23983

openalex publication_date 2025/05/29 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28

Abstract

This paper deals with the noise identification of a linear time-varying stochastic dynamic system described by the state-space model. In particular, the stress is laid on the design of the correlation measurement difference method for estimation of the state and measurement noise covariance matrices for both observable and unobservable systems with possibly unknown input sequence. The method provides unbiased and consistent estimates and is implemented in a publicly available MATLAB toolbox and numerically evaluated.

Citations

• Identifiability Analysis of Noise Covariances for LTI Stochastic Systems with Unknown Inputs
• Autonomous Tracking and State Estimation with Generalised Group Lasso

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• Supervisory Measurement-Guided Noise Covariance Estimation: Discussing Forward and Reverse Differentiation
• A simple and robust method for noise variance estimation for time-varying signals