Statistical signal characterization-new help for real-time processing

The author presents and explains statistical signal characterization (SSC), a technique by which certain easily measured time and amplitude attributes of a signal may be extracted and used to calculate a set of SSC parameters. It is shown how the SSC parameter extraction and statistical analysis processes can be accomplished at considerable savings in computational burden, compared to waveform processing through conventional Fourier methods. The SSC technique is applied to some selected problems within the fields of signal identification and association (or discrimination), and to conventional waveform parameter (amplitude, frequency, phase) extraction. General examples are presented to clarify the use of the technique. Specific examples in radar processing, medical waveform analysis, and seismology are given. Discussions on combining SSC with more conventional processing methods, to arrive at an optimal system design for a particular application, are presented