Deconvolving oscillatory transients with a Kalman filter

TL;DR

This paper introduces a Kalman filter-based method for effectively removing large oscillatory transients from time series measurements, enabling high-resolution signal analysis with adjustable noise filtering.

Contribution

It presents a novel Kalman filter approach specifically designed for deconvolving large oscillatory transients in time series data.

Findings

Effective transient filtering demonstrated

Adjustable resolution and noise filtering achieved

Optimality property of the filter validated

Abstract

This paper describes a method to filter oscillatory transients from measurements of a time series which were at least an order of magnitude larger than the signal to be measured. Based on a Kalman filter, it has an optimality property and a natural scaling parameter that allows to tune it to high resolution or low noise.