ON THE IMPLEMENTATION OF THE STRIP SPECTRAL CORRELATION ALGORITHM FOR CYCLIC SPECTRUM ESTIMATION

PDF

Authors
  1. April, E.
Corporate Authors
Defence Research Establishment Ottawa, Ottawa ONT (CAN)
Abstract
This report discusses the implementation of one of the best digital cyclic spectrum (CS) algorithms derived so far, the Strip Spectral Correlation Algorithm (SSCA). Some theoretical background and a detailed description of the SSCA are provided. An Analysis of the SSCA is performed and an algorithm for mapping the SSCA output is formulated. The cyclic feature function (CFF) is defined as a means to detect the cyclic features from the SSCA. Results of the SSCA encoded in C are then reported. Three BPSK signals and two additive white Gaussian noise (AWGN) signals are used to verify the validity of the SSCA. Three-dimensional plots and two-dimensional plots of the CS and CFF respectively are presented to the reader. Finally, some benchmarks on a SUN computer for the SSCA are provided for reference. In brief, the CS and CFF estimated with the SSCA prove to be valuable tools for analyzing second-order cyclostationary communication signals and, by making extensive use of the FFT, to provide robust, reliable, and accurate results more efficiently than typical CS direct estimation methods.
Keywords
Cyclostationary;Spectral estimation;Cyclic features;Spectral correlation;Signal detection;Spectral analysis
Report Number
DREO-TN-94-2 — Technical Note
Date of publication
01 Mar 1994
Number of Pages
61
DSTKIM No
95-01020
CANDIS No
148648
Format(s):
Hardcopy;Document Image stored on Optical Disk

Permanent link

Document 1 of 1

Date modified: