Product high-order ambiguity function for multicomponentpolynomial-phase signal modeling
Barbarossa, S.
Scaglione, A.
Giannakis, G.B.
INFOCOM Dept., Rome Univ.;
This paper appears in: Signal Processing, IEEE Transactions on
Publication Date: Mar 1998
Volume: 46,
Issue: 3
On page(s): 691-708
ISSN: 1053-587X
References Cited: 37
CODEN: ITPRED
INSPEC Accession Number: 5861185
Digital Object Identifier: 10.1109/78.661336
Current Version Published: 2002-08-06
Abstract
Parameter estimation and performance analysis issues are studied
for multicomponent polynomial-phase signals (PPSs) embedded in white
Gaussian noise. Identifiability issues arising with existing approaches
are described first when dealing with multicomponent PPS having the same
highest order phase coefficients. This situation is encountered in
applications such as synthetic aperture radar imaging or propagation of
polynomial phase signals through channels affected by multipath and is
thus worthy of a careful analysis. A new approach is proposed based on a
transformation called product high-order ambiguity function (PHAF). The
use of the PHAF offers a number of advantages with respect to the
high-order ambiguity function (HAF). More specifically, it removes the
identifiability problem and improves noise rejection capabilities.
Performance analysis is carried out using the perturbation method and
verified by simulation results
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