Multiple Target Detection Using Split SpectrumProcessing and
Group Delay Moving Entropy
The split spectrum processing technique obtains a frequency-diverse ensemble of
narrowband signals through afilterbank then recombines them nonlinearly to improve tar-get
visibility. Although split spectrum processing is an effectivemethod for suppressing grain noise in
ultrasonic nondestruc-tive testing, its application was mainly limited to the detectionof single targets
or multiple targets having similar spectralcharacteristics. In this paper, the group delay moving
entropy technique is introduced primarily to enhance the performanceof split spectrum processing in
detecting multiple targets whichexhibit different spectral characteristics (i.e., variations in target
signal center frequency and bandwidth). This is likely to occur in complex, dispersive, and
nonhomogeneous media such as composites, layered, and clad materials, etc. The analysis shows that the
group delay moving entropy method can beused effectively to select the optimal frequency region for
split spectrum processing when detecting such targets. Based on aniterative procedure that
combines group
delay moving entropyand split spectrum processing, multiple targets can be identifiedone at a time, and
subsequently eliminated by using time domain windows. The removal of the dominant target improves
the detection of the remaining weaker targets. Simulation results arepresented which demonstrate
the
feasibility of the multistep splitspectrum processing technique for detecting multiple targets insuch
materials.I.
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