Statistical analysis of split spectrum processing

Abstract

This work provides a statistical analysis of Split Spectrum Processing (SSP) performance in detecting multiple targets. The investigation is performed under two conditions: (i) known a priori target spectra (i.e., center frequency and bandwidth) which, in turn, identifies the optimal spectral range for processing, and (ii) adaptively obtaining the processing frequencies using group delay moving entropy. The group delay moving entropy (GDME) method was introduced to select the optimal frequency regions for SSP when detecting multiple targets. The effectiveness of this technique is statistically demonstrated in this paper. The performance is measured in terms of Normalized Signal-to-Noise Ratio and probability of target detection. SSP with known target information yields a slightly higher probability of detection compared to SSP using GDME, while both cases achieve comparable SNR enhancement. SSP results were compared to the optimal bandpass filter performance and shown to be superior.