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Deconvolution filters for the analysis of dynamic measurement processes: a tutorial.

Eichstädt, S*; Elster, C*; Esward, T J; Hessling, J P* (2010) Deconvolution filters for the analysis of dynamic measurement processes: a tutorial. Metrologia, 47 (5). pp. 522-533.

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Analysis of dynamic measurements is of growing importance in metrology as an increasing number of applications requires the determination of measurands showing a time-dependence. Often, linear time-invariant (LTI) systems are appropriate to model the relation between the available measurement data and the sought time-dependent value of the measurand. Estimation of the measurand is then done by deconvolution of the measurement data and digital filtering is a suitable tool for this task.

Different techniques are available for the construction of a deconvolution filter and recently two approaches have been proposed in the context of metrology. Here we compare these two and other approaches for a dynamic model type relevant in many metrological applications and we discuss different scenarios of how information about the LTI system is given. In detail, we consider the method of minimum-phase allpass decomposition, asynchronous time reversal using the exact inverse filter and construction of stable IIR and FIR approximate inverse filters by a least squares approach in the frequency domain. The methods are compared qualitatively by assessing their (numerical) complexity and quantitatively in terms of their performance for simulated measurements. The goal of the paper is to assess the different methods in the various situations and to give some guidance for the choice of a method.

Item Type: Article
Keywords: uncertainty, dynamic measurement, deconvolution, filter design
Subjects: Mathematics and Scientific Computing
Mathematics and Scientific Computing > Signal Processing
Identification number/DOI: 10.1088/0026-1394/47/5/003
Last Modified: 02 Feb 2018 13:15
URI: http://eprintspublications.npl.co.uk/id/eprint/4935

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