Wavelet transform techniques for time varying propagation and scattering characterization

Leon H. Sibul; Michael J. Roan; Kenneth L. Hillsley

Wavelet transform techniques for time varying propagation and scattering characterization

Leon H. Sibul, Michael J. Roan, Kenneth L. Hillsley

Mechanical Engineering

Research output: Contribution to journal › Conference article › peer-review

4 Scopus citations

Abstract

It is shown that linear time varying (LTV) propagation and scattering channels are efficiently characterized by wideband spreading functions that can be estimated using continuous wavelet transforms (CWT). We show that the CWT domain characterization of LTV propagation channels leads naturally to a wavelet domain implementation of maximum likelihood detectors of multi-highlight objects whose echos are distributed in range and time-scale.

Original language	English (US)
Pages (from-to)	1644-1649
Number of pages	6
Journal	Conference Record of the Asilomar Conference on Signals, Systems and Computers
Volume	2
State	Published - 1998
Event	Proceedings of the 1998 32nd Asilomar Conference on Signals, Systems & Computers. Part 1 (of 2) - Pacific Grove, CA, USA Duration: Nov 1 1998 → Nov 4 1998

All Science Journal Classification (ASJC) codes

Signal Processing
Computer Networks and Communications

Cite this

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title = "Wavelet transform techniques for time varying propagation and scattering characterization",

abstract = "It is shown that linear time varying (LTV) propagation and scattering channels are efficiently characterized by wideband spreading functions that can be estimated using continuous wavelet transforms (CWT). We show that the CWT domain characterization of LTV propagation channels leads naturally to a wavelet domain implementation of maximum likelihood detectors of multi-highlight objects whose echos are distributed in range and time-scale.",

author = "Sibul, {Leon H.} and Roan, {Michael J.} and Hillsley, {Kenneth L.}",

year = "1998",

language = "English (US)",

volume = "2",

pages = "1644--1649",

journal = "Conference Record of the Asilomar Conference on Signals, Systems and Computers",

issn = "1058-6393",

publisher = "IEEE Computer Society",

note = "Proceedings of the 1998 32nd Asilomar Conference on Signals, Systems & Computers. Part 1 (of 2) ; Conference date: 01-11-1998 Through 04-11-1998",

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T1 - Wavelet transform techniques for time varying propagation and scattering characterization

AU - Sibul, Leon H.

AU - Roan, Michael J.

AU - Hillsley, Kenneth L.

PY - 1998

Y1 - 1998

N2 - It is shown that linear time varying (LTV) propagation and scattering channels are efficiently characterized by wideband spreading functions that can be estimated using continuous wavelet transforms (CWT). We show that the CWT domain characterization of LTV propagation channels leads naturally to a wavelet domain implementation of maximum likelihood detectors of multi-highlight objects whose echos are distributed in range and time-scale.

AB - It is shown that linear time varying (LTV) propagation and scattering channels are efficiently characterized by wideband spreading functions that can be estimated using continuous wavelet transforms (CWT). We show that the CWT domain characterization of LTV propagation channels leads naturally to a wavelet domain implementation of maximum likelihood detectors of multi-highlight objects whose echos are distributed in range and time-scale.

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UR - http://www.scopus.com/inward/citedby.url?scp=0032268021&partnerID=8YFLogxK

M3 - Conference article

AN - SCOPUS:0032268021

SN - 1058-6393

VL - 2

SP - 1644

EP - 1649

JO - Conference Record of the Asilomar Conference on Signals, Systems and Computers

JF - Conference Record of the Asilomar Conference on Signals, Systems and Computers

T2 - Proceedings of the 1998 32nd Asilomar Conference on Signals, Systems & Computers. Part 1 (of 2)

Y2 - 1 November 1998 through 4 November 1998

ER -

Wavelet transform techniques for time varying propagation and scattering characterization

Abstract

All Science Journal Classification (ASJC) codes

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