@inproceedings{92bd7dc8bc8943ef94f1968f372b8fde,
title = "Error characterization of duty cycle estimation for sampled non-band-limited pulse signals with finite observation period",
abstract = "In many applications the pulse duration of a periodic pulse signal is the parameter of interest. Thereby, the non-band-limited pulse signal is sampled during a finite observation period yielding to aliasing and windowing effects, respectively. In this work, the pulse duration estimation based on the mean value of the samples is considered, and an exact expression of the mean squared estimation error (averaged over all possible time shifts) is derived. The resulting mean squared error expression depends on the observation period, the pulse period and the pulse duration. Analyzing the effect of these parameters shows that the mean squared error can be reduced (i) if the observation period is a multiple of the pulse period, (ii) if the pulse period is not a multiple of the sampling period, and (iii) if the total number of samples is a prime number. All results were validated with simulation results.",
keywords = "Frequency-domain analysis, Estimation error, Signal processing, Europe, Ultrasonic variables measurement, Pulse measurements, Sampling error, Wireless sensor networks (WSN), Synchronization, Sampling process, Signal reconstruction, Localization, Band width, Ultrasonic",
author = "Hans-Peter Bernhard and Bernhard Etzlinger and Andreas Springer",
year = "2016",
month = sep,
day = "2",
doi = "10.1109/EUSIPCO.2016.7760626",
language = "English",
isbn = "978-1-5090-1891-8",
series = "2016 24th European Signal Processing Conference (EUSIPCO)",
publisher = "IEEE Computer Society",
pages = "2136--2140",
booktitle = "2016 24th European Signal Processing Conference (EUSIPCO)",
address = "United States",
note = "2016 24th European Signal Processing Conference (EUSIPCO) ; Conference date: 29-08-2016 Through 02-09-2016",
}