Conference Proceeding

Time domain uncertainty bound of signal reconstruction in the case of jittery and noisy measurements

Dept. of Meas. & Inf. Syst., Tech. Univ. Budapest
06/1998; DOI:10.1109/IMTC.1998.676958 ISBN: 0-7803-4797-8 pp.1296 - 1301 vol.2 In proceeding of: Instrumentation and Measurement Technology Conference, 1998. IMTC/98. Conference Proceedings. IEEE, Volume: 2
Source: IEEE Xplore

ABSTRACT Time domain measurements are distorted by the measurement system
if the bandwidth of the system is not sufficiently high compared to that
of the signal to be measured. If the distortion is known the measured
signal can be compensated (inverse filtering or deconvolution). Since
the measurement is always corrupted by noise the reconstruction is an
estimation task. Our aim is to investigate the errors related to the
signal reconstruction, and provide an error bound around the
reconstructed waveform. Based on their nature we can distinguish between
two types of errors, bias and variance. In this paper we investigate the
stochastic type errors and suggest a method to calculate the uncertainty
(variance) of the reconstruction. We developed the method for the
calibration of high speed sampling systems. Beside the stationary
additive noise of the measurement system (quantization, electromagnetic
interferences etc.) the waveforms are distorted due to the uncertainty
of the time base (jitter). The effect of the jitter can be described as
a nonstationary additive noise. This noise causes both variance, and
bias, since the mean value of the noise is not zero. We will take both
stationary and jitter related nonstationary noise into account and
provide an uncertainty bound around the reconstructed signal. Because of
the nonstationary nature of the jitter the uncertainty bound is a
function of time. The complete error analysis should also involve the
investigation of the bias. This will be carried out in the future

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Keywords

complete error analysis
 
deconvolution
 
estimation task
 
interferences
 
jitter
 
measurement system
 
noise causes
 
nonstationary additive noise
 
nonstationary nature
 
nonstationary noise
 
quantization
 
reconstructed signal
 
reconstructed waveform
 
signal reconstruction
 
speed sampling systems
 
stationary
 
stochastic type errors
 
time base
 
Time domain measurements
 
waveforms
 

T. Daboczi