A wideband wavelet based estimator correlator and its properties

Leon H. Sibul, Lora G. Weiss

Research output: Contribution to journalArticle

6 Citations (Scopus)

Abstract

Maximum likelihood detectors of narrowband, non-stationary random echos in Gaussian noise can be efficiently implemented in the time-frequency domain. When the transmitted signals have large time-bandwidth products, the natural implementation of estimators and detectors is in the time-scale or wavelet transform domain. This paper presents a wideband wavelet transform domain implementation of an estimator-correlator (EC) detector and details the components of this processor, including weighted wavelet transforms and cascaded scattering functions. Key properties associated with this wavelet based wideband EC are also presented. The theoretical developments of the processor are based on group theory which provides a unified approach to detector development for both narrowband and wideband processors. The group theoretic concepts provide a powerful analysis tool for complex signal processing problems.

Original languageEnglish (US)
Pages (from-to)157-186
Number of pages30
JournalMultidimensional Systems and Signal Processing
Volume13
Issue number2
DOIs
StatePublished - Apr 1 2002

Fingerprint

Correlators
Correlator
Wavelets
Detector
Wavelet transforms
Wavelet Transform
Detectors
Estimator
Group theory
Gaussian Noise
Group Theory
Maximum likelihood
Maximum Likelihood
Frequency Domain
Signal Processing
Time Domain
Signal processing
Time Scales
Bandwidth
Scattering

All Science Journal Classification (ASJC) codes

  • Software
  • Signal Processing
  • Information Systems
  • Hardware and Architecture
  • Computer Science Applications
  • Artificial Intelligence
  • Applied Mathematics

Cite this

@article{c94774c30f3749788420c21b90d1a423,
title = "A wideband wavelet based estimator correlator and its properties",
abstract = "Maximum likelihood detectors of narrowband, non-stationary random echos in Gaussian noise can be efficiently implemented in the time-frequency domain. When the transmitted signals have large time-bandwidth products, the natural implementation of estimators and detectors is in the time-scale or wavelet transform domain. This paper presents a wideband wavelet transform domain implementation of an estimator-correlator (EC) detector and details the components of this processor, including weighted wavelet transforms and cascaded scattering functions. Key properties associated with this wavelet based wideband EC are also presented. The theoretical developments of the processor are based on group theory which provides a unified approach to detector development for both narrowband and wideband processors. The group theoretic concepts provide a powerful analysis tool for complex signal processing problems.",
author = "Sibul, {Leon H.} and Weiss, {Lora G.}",
year = "2002",
month = "4",
day = "1",
doi = "10.1023/A:1014488726761",
language = "English (US)",
volume = "13",
pages = "157--186",
journal = "Multidimensional Systems and Signal Processing",
issn = "0923-6082",
publisher = "Springer Netherlands",
number = "2",

}

A wideband wavelet based estimator correlator and its properties. / Sibul, Leon H.; Weiss, Lora G.

In: Multidimensional Systems and Signal Processing, Vol. 13, No. 2, 01.04.2002, p. 157-186.

Research output: Contribution to journalArticle

TY - JOUR

T1 - A wideband wavelet based estimator correlator and its properties

AU - Sibul, Leon H.

AU - Weiss, Lora G.

PY - 2002/4/1

Y1 - 2002/4/1

N2 - Maximum likelihood detectors of narrowband, non-stationary random echos in Gaussian noise can be efficiently implemented in the time-frequency domain. When the transmitted signals have large time-bandwidth products, the natural implementation of estimators and detectors is in the time-scale or wavelet transform domain. This paper presents a wideband wavelet transform domain implementation of an estimator-correlator (EC) detector and details the components of this processor, including weighted wavelet transforms and cascaded scattering functions. Key properties associated with this wavelet based wideband EC are also presented. The theoretical developments of the processor are based on group theory which provides a unified approach to detector development for both narrowband and wideband processors. The group theoretic concepts provide a powerful analysis tool for complex signal processing problems.

AB - Maximum likelihood detectors of narrowband, non-stationary random echos in Gaussian noise can be efficiently implemented in the time-frequency domain. When the transmitted signals have large time-bandwidth products, the natural implementation of estimators and detectors is in the time-scale or wavelet transform domain. This paper presents a wideband wavelet transform domain implementation of an estimator-correlator (EC) detector and details the components of this processor, including weighted wavelet transforms and cascaded scattering functions. Key properties associated with this wavelet based wideband EC are also presented. The theoretical developments of the processor are based on group theory which provides a unified approach to detector development for both narrowband and wideband processors. The group theoretic concepts provide a powerful analysis tool for complex signal processing problems.

UR - http://www.scopus.com/inward/record.url?scp=0036533637&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=0036533637&partnerID=8YFLogxK

U2 - 10.1023/A:1014488726761

DO - 10.1023/A:1014488726761

M3 - Article

AN - SCOPUS:0036533637

VL - 13

SP - 157

EP - 186

JO - Multidimensional Systems and Signal Processing

JF - Multidimensional Systems and Signal Processing

SN - 0923-6082

IS - 2

ER -