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 language | English (US) |
|---|---|
| Pages (from-to) | 157-186 |
| Number of pages | 30 |
| Journal | Multidimensional Systems and Signal Processing |
| Volume | 13 |
| Issue number | 2 |
| DOIs | |
| State | Published - Apr 1 2002 |
Fingerprint
All Science Journal Classification (ASJC) codes
- Software
- Signal Processing
- Information Systems
- Hardware and Architecture
- Computer Science Applications
- Artificial Intelligence
- Applied Mathematics
Cite this
}
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 journal › Article
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 -