DocumentCode :
2248099
Title :
Polynomial order reducing property of lattice filters in detection of linear FM signals
Author :
Kahaei, M.H. ; Deriche, M. ; Boashash, B.
Author_Institution :
Signal Process. Res. Centre, Queensland Univ. of Technol., Brisbane, Qld., Australia
Volume :
3
fYear :
1997
fDate :
9-12 Sep 1997
Firstpage :
1382
Abstract :
Order-reduction techniques have already been successfully applied to the detection of linear FM signals in white noise. In this paper, reflection coefficients of adaptive lattice filters are used, in a new aspect, to reduce the order of input polynomial phase FM signals. This concept is then used to detect chirp signals in white noise. To define an appropriate hypothesis problem for the transformed signals in the first adaptive reflection coefficient, its statistical behaviour is experimentally investigated. It is shown that for small confidence intervals, the relevant probability density function for the transformed signal can be assumed Gaussian
Keywords :
Gaussian noise; adaptive filters; adaptive signal detection; chirp modulation; frequency modulation; lattice filters; polynomials; reduced order systems; white noise; Gaussian signal; adaptive lattice filters; adaptive reflection coefficient; chirp signals; confidence intervals; detection; hypothesis problem; input polynomial phase FM signals; linear FM signals; order-reduction techniques; polynomial order reducing property; probability density function; reflection coefficients; statistical behaviour; transformed signal; transformed signals; white noise; Acoustic reflection; Gaussian noise; Lattices; Nonlinear filters; Polynomials; Signal detection; Signal generators; Signal processing; Signal to noise ratio; White noise;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Information, Communications and Signal Processing, 1997. ICICS., Proceedings of 1997 International Conference on
Print_ISBN :
0-7803-3676-3
Type :
conf
DOI :
10.1109/ICICS.1997.652216
Filename :
652216
Link To Document :
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