Gk. Yeung et Wa. Gardner, SEARCH-EFFICIENT METHODS OF DETECTION OF CYCLOSTATIONARY SIGNALS, IEEE transactions on signal processing, 44(5), 1996, pp. 1214-1223
Conventional signal processing methods that exploit cyclostationarity
for the detection of weak signals in noise require fine resolution in
cycle frequency for long integration time. Hence, in cases of weak-sig
nal detection and broadband search, problems in implementation, such a
s excessive computational complexity and storage and search arise. Thi
s paper introduces two new search-efficient methods of cycle detection
, namely the autocorrelated cyclic autocorrelation (ACA) and the autoc
orrelated cyclic periodogram (ACP) methods. For a given level of perfo
rmance reliability, the ACA and ACP methods allow much larger resoluti
on width in cycle frequency to be used in their implementations, compa
red to the conventional methods of cyclic spectral analysis. Thus, the
amount of storage and search can be substantially reduced. Analyses o
f the two methods, performance comparison, and computer simulation res
ults are presented.