VON WISPR Family Processors: Volume 1.
1997
Wagstaff, Ronald A. | Leybourne, Allen E. | George, Jacob
Fluctuation-based signal processing is a new approach to signal processing. It focuses on the situation in which the signals of interest fluctuate less than signals that are not of interest (clutter) and the background noise they are embedded in. Processors utilizing those fluctuations such as the von WISPR Family Processors discussed herein, are methods or algorithms that preferentially attenuate the fluctuating signals and noise as their fluctuation levels increase. Both amplitude and phase fluctuations can be exploited, the latter requiring novel approaches to coherent processing. The net effects can be significant enhancements in the characteristics, attributes, or products of the signal processor. Some examples include enhancements in signal-to-noise ratio, clutter reduction or elimination, spatial and spectral resolution, and minimum detectable level. Several processors that provide such enhancements are presented and discussed using measured and simulated data. In many cases, the results are independent of the spatial aperture of the measurement apparatus (sensor or array) and the spectral resolution (frequency binwidth) of the spectrum analyzer. The implication is that exploiting fluctuations is a means whereby the signal processor can tap into an additional independent source of gain. The results presented herein provide both qualitative and quantitative measures of the additional gains that can be achieved by exploiting the fluctuations in signal and noise. Although most of the examples presented are for underwater acoustic data, the generality of fluctuation-based processing is demonstrated for other types of data as well.
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