Abstract
The high-order ambiguity function (HAF) was introduced for the estimation of polynomial-phase signals (PPS) embedded in noise. Since the HAF is a nonlinear operator, it suffers from noise-masking effects and from the appearance of undesired cross terms and, possibly, spurious harmonics in the presence of multicomponent (me) signals. The product HAF (PHAF) was then proposed as a way to improve the performance of the HAF in the presence of noise and to solve the ambiguity problem. In this correspondence we derive a statistical analysis of the PHAF in the presence of additive white Gaussian noise (AWGN) valid for high sisgnalto-noise ratio (SNR) and a finite number of data samples. The analysis is carried out in detail for single-component PPS but the multicomponent case is also discussed. Error propagation phenomena implicit in the recursive structure of the PHAF-based estimator are explicitly taken into account. The analysis is validated by simulation results for both singleand multicomponent PPS's.
| Original language | English (US) |
|---|---|
| Pages (from-to) | 343-356 |
| Number of pages | 14 |
| Journal | IEEE Transactions on Information Theory |
| Volume | 45 |
| Issue number | 1 |
| DOIs | |
| State | Published - 1999 |
| Externally published | Yes |
Keywords
- High-order ambiguity function
- Parameter estimation
- Polynomial-phase signals
ASJC Scopus subject areas
- Information Systems
- Computer Science Applications
- Library and Information Sciences