Measurement of distorted exponential signal components using maximum likelihood estimation

•The maximum likelihood method for the measurement of signal components is presented.•Prony’s method serves for initiating of the differential evolution procedure.•The robustness on ADC nonlinearities, quantization and clopping noise is analyzed.•Simulation and experimental data approved the effecti...

Full description

Saved in:
Bibliographic Details
Published in:Measurement : journal of the International Measurement Confederation Vol. 58; pp. 503 - 510
Main Authors: Michaeli, Linus, Šaliga, Ján, Liptak, Jozef, Godla, Marek, Kollár, István
Format: Journal Article
Language:English
Published: Elsevier Ltd 01-12-2014
Subjects:
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:•The maximum likelihood method for the measurement of signal components is presented.•Prony’s method serves for initiating of the differential evolution procedure.•The robustness on ADC nonlinearities, quantization and clopping noise is analyzed.•Simulation and experimental data approved the effectiveness of the method. Exponential signal is a suitable stimulus for dynamic ADC testing because of the simplicity of the generating RC circuit. A potential distortion source of the ideal exponential shape is the dielectric absorption of the capacitor, whose effect can be represented by additional superimposed exponential components with longer time constant and smaller peak value. Measurement of the distortion of the exponential signal by using a reference waveform recorder with known nonlinearity is the initial step in the calibration of an ADC testing stand with exponential stimulus, along with the assessment of its uncertainty. Lack of the orthogonality of stimulus signal components makes classical analysis methods difficult to apply. This paper presents a method for measurement of multiexponential signal components as an example of the more general task of signal decomposition where signal components are non-orthogonal. The proper optimization procedure based on the ML method will be presented, which usually reaches the global minimum of the cost function. Effectiveness will be shown by simulation, and by application to measurement of a multiexponential signal acquired by a reference waveform recorder with known error parameters.
ISSN:0263-2241
1873-412X
DOI:10.1016/j.measurement.2014.09.024