1. A method for implementation of a Spectrum Sensing Function wherein Higher Order Statistics (HOS) are applied to segments of received waveforms in time and frequency domains comprising the steps of: selecting a particular portion of a frequency spectrum; applying a first band pass filter which is configured to exclude regions of the frequency spectrum that are outside of the selected portion; applying a low noise amplifier; collecting waveforms from said portion of said frequency spectrum; downconverting said collected waveforms; applying an analog to digital conversion to said waveforms at a first sampling rate; applying a second filter to said waveforms; up or down converting said waveforms so as to shift a characteristic frequency component of said waveforms to a specified detection frequency; applying a third filter which is configured to pass only frequencies near the specified detection frequency; resampling said waveforms so as to adjust the sampling rate; applying serial to parallel conversion to convert the digitized waveforms to a stream of time domain segments, each time domain segment including a plurality of time domain samples; applying a Fast Fourier Transform (FFT) to each time domain segment so as to obtain a corresponding frequency domain segment, each of the frequency domain segments including a plurality of frequency domain samples; processing both the time domain segments and the frequency domain segments using higher order statistics; classifying each segment as belonging to Class Signal or Class Noise; and for at least one segment that is classified as Class Signal, identifying at least one signal within said segment.