A Comparison Between Different Discrete Ambiguity Domain Definitions in Stochastic Time-Frequency Analysis
Author
Summary, in English
The ambiguity domain plays a central role in estimating the time-varying spectrum and in estimating the covariance function of nonstationary random processes in continuous time. For processes in discrete time, there exist different definitions of the ambiguity domain, but it is well known that neither of these definitions perfectly resembles the usefulness of the continuous ambiguity domain. In this paper, we present some of the most frequently used definitions of the ambiguity domain in discrete time: the Claasen-MecklenbrÄuker, the Jeong-Williams, and the Nuttall definitions. For the first time, we prove their equivalence within some necessary conditions and we present theorems that justify their usage.
Department/s
- Mathematical Statistics
- Statistical Signal Processing Group
Publishing year
2009
Language
English
Pages
868-877
Publication/Series
IEEE Transactions on Signal Processing
Volume
57
Issue
3
Document type
Journal article
Publisher
IEEE - Institute of Electrical and Electronics Engineers Inc.
Topic
- Probability Theory and Statistics
Keywords
- Ambiguity domain
- covariance function estimation
- Claasen-Mecklenbräuker
- discrete-time discrete-frequency
- Nuttall
- Jeong–Williams
- nonstationary random processes
- time-frequency analysis
Status
Published
Research group
- Statistical Signal Processing Group
ISBN/ISSN/Other
- ISSN: 1053-587X