Adaptive linear estimation of the dynamic measurement error

This paper presents a review of publications on methods for estimating the dynamic measurement error and methods for its correction. The error components are due to the dynamic properties (inertia) of the sensor and the additive noise at its output. A method is proposed for estimating and reducing the dynamic measurement error based on the principle of adaptive linear prediction or adaptive linear signal amplification. This approach generates an error estimation signal based on the result of comparing a delayed copy of the recovered signal with the same reconstructed signal passed through an adaptive nonrecursive filter with a linear phase characteristic. Based on this approach, a measurement system structure has been developed to estimate the dynamic measurement error and reduce it by correcting the dynamic characteristics of the sensor and adaptive filtering of measurement noise. A computer simulation of the proposed measurement system for a second-order sensor was performed. Optimal (in the sense of the mean squared deviation of the error) orders of the restoring adaptive filter were obtained in the presence of additive harmonic noise with variable frequency at the sensor output. The properties of the proposed measurement system structure with a dynamic measurement error estimator adaptive to the noise parameter are determined. The application field of the results obtained is the processing of measurement results of rapidly varying processes (including in real time), when the component of the dynamic measurement error caused by the dynamic properties (inertia) of the sensor, as well as the additive noise at its output, is dominant. The solution to such a problem is relevant, for example, when processing the results of ground tests of space technology.