The Estimation and Tracking of Frequency
Many electronic and acoustic signals can be modelled as sums of sinusoids and noise. However, the amplitudes, phases and frequencies of the sinusoids are often unknown and must be estimated in order to characterise the periodicity or near-periodicity of a signal and consequently to identify its source. This book presents and analyses several practical techniques used for such estimation. The problem of tracking slow frequency changes over time of a very noisy sinusoid is also considered. Rigorous analyses are presented via asymptotic or large sample theory, together with physical insight. The book focuses on achieving extremely accurate estimates when the signal to noise ratio is low but the sample size is large. Each chapter begins with a detailed overview, and many applications are given. Matlab code for the estimation techniques is also included. The book will thus serve as an excellent introduction and reference for researchers analysing such signals.
- Very detailed summary of the field (methods for measuring periodicity of signals)
- Contains Matlab code for implementing the techniques discussed
- Many applications treated
Reviews & endorsements
"This book...can be useful to both statisticians and signal processing people." Pham Dinh Tuan, Mathematical Reviews
"The book does what it sets out to do, and by restricting its scope, is able to focus in-depth on specific aspects of the problem...This book fulfils a role I think primarily as a high-quality expository monograph...It is a nicely presented exposition of one strand of the frequency estimation story, and it is pleasing to see a book devoted to this subject." International Journal of Robust and Nonlinear Control
Product details
January 2013Paperback
9781107412859
280 pages
254 × 178 × 15 mm
0.49kg
Available
Table of Contents
- Preface
- 1. Introduction
- 2. Statistical and probabilistic methods
- 3. The estimation of a fixed frequency
- 4. Techniques derived from ARMA modelling
- 5. Estimation using Fourier coefficients
- 6. Tracking frequency in low SNR conditions
- 7. Other estimation techniques
- References
- Appendix. Matlab programs
- Author index
- Subject index.