| Summary: | Approved for public release; distribution unlimited. === There is a growing need within the Na\ry for methods of detecting
discrete narrowband signals in a non-stationary background. This paper
concerns itself with the application of digital processing and spectral
analysis techniques toward that goal. The use of the fast Fourier
Transform in estimating the power spectrum of a signal is described.
The method involves sectioning the time record, making "raw" estimates
of the spectrum from these sections, and averaging these "raw" estimates.
It is shown that more stable estimates are available if the segments are
overlapped and an optimum amount of overlap for the case of the Manning
Window is found. It is shown that the stability of these spectral estimates
can be interpreted as processing gain in the case of a discrete
narrowband signal in additive noise. And finally, a brief description of signal detection theory applied to a human observer is presented to emphasize
the flexibility that a human operator can bring to a signal detection
system.
|
|---|
