Logo of the Physikalisch-Technische Bundesanstalt

Measurement uncertainty

Working Group 8.42
To top


Comparison of measurement results, reliable decision-making and conformity assessment require the evaluation of uncertainties associated with measurement results. The ability to compare measurements made in different places and at different times underpins international metrology. The Guide to the Expression of Uncertainty in Measurement (Opens external link in new windowGUM) provides guidance for the evaluation of uncertainties, and it has been applied successfully in many applications throughout metrology.


Illustration of Monte Carlo method according to Opens external link in new windowSupplement 1 to the GUM.

In recent years metrology has expanded to support new fields to address societal challenges relating to energy and sustainability, climate and environmental monitoring, life sciences and health, using measurement modalities such as imaging, spectroscopy, earth observation and sensor networks. Reliable uncertainty evaluation is particularly important in these applications, e.g. to safeguard the diagnosis of a tumor in quantitative imaging or to reliably monitor air pollution. The GUM does not adequately address the challenges arising in these applications, and the development of statistical procedures for improved uncertainty evaluation is an urgent need.

To top


The focus of PTB’s Working Group 8.42 is on the development of Bayesian methods for the evaluation of uncertainties. The development is carried out within the context of different research areas of data analysis such as large-scale data analysis or deep learning. Bayesian inference procedures suitable for the extension of the current GUM methodology are also part of the current research in PTB’s Working Group 8.42. Examples include simple means to assign distributions representing the available prior knowledge, or procedures for the numerical calculation of results. Open source software support is provided to ease the application of the research results.

To top


To top


Publication single view


Title: On-line dynamic error compensation of accelerometers by uncertainty-optimal filtering
Author(s): S. Eichstädt, A. Link, T. Bruns and C. Elster
Journal: Measurement
Year: 2010
Volume: 43
Issue: 5
Pages: 708-713
DOI: 10.1016/j.measurement.2009.12.028
Web URL: http://www.sciencedirect.com/science/article/pii/S0263224110000023
Keywords: Accelerometer,Digital filter,Dynamic measurements,Dynamik,Uncertainty
Tags: 8.42, Dynamik, Unsicherheit
Abstract: The output signal of an accelerometer typically contains dynamic errors when a broadband acceleration is applied. In order to determine the applied acceleration, post-processing of the accelerometer’s output signal is required. To this end, we propose the application of a digital FIR filter. We evaluate the uncertainty associated with the filtered output signal and give explicit formulae which allow for on-line calculation. In this way, estimation of the applied acceleration and the calculation of associated uncertainties may be carried out during the measurement. The resulting uncertainties can strongly depend on the design of the applied filter and we describe a simple method to construct an uncertainty-optimal filter. The benefit of the proposed procedures is illustrated by means of simulated measurements.

Back to the list view

To top