Detection of Weak Signals Using Adaptive Stochastic Resonance
Ahmad. S. Asdi and Ahmed. H. Tewfik
Abstract-
We present a novel nonlinear filtering approach for detecting
weak signals in heavy noise
from short data records. Such detection problems arise in many applications
including
communications, radar, sonar, medical imaging, seismology, industrial
measurements, etc.
The performance of a matched filter detector of a weak signal in
heavy noise is directly proportional to the observation time . We
discuss an alternative detection
approach
that relies on a nonlinear filtering of the input signal using a bistable
system. We show that
by adaptively selecting the parameters of the system, it is possible to
increase the ratio of
the square of the amplitude of a sinusoid to that of the noise intensity
around the frequency
of the sinusoid (stochastic resonance). The sinusoid can then be reliably
detected at the
output of the nonlinear system using a suitable matched
filter even when the data record is short .
To appear in Proc. of ICASSP'95