Abstract
Parameter estimation for a class of nonstationary signal models is addressed. The class contains combination of a polynomial-phase signal (PPS) and a frequency-modulated (FM) component of the sinusoidal or hyperbolic type. Such signals appear in radar and sonar applications involving moving targets with vibrating or rotating components. A novel approach is proposed that allows us to decouple estimation of the FM parameters from those of the PPS, relying on properties of the multilag high-order ambiguity function (ml-HAF). The accuracy achievable by any unbiased estimator of the hybrid FM-PPS parameters is investigated by means of the Cramér-Rao lower bounds (CRLB's). Both exact and large sample approximate expressions of the bounds are derived and compared with the performance of the proposed methods based on Monte Carlo simulations.
| Original language | English (US) |
|---|---|
| Pages (from-to) | 363-377 |
| Number of pages | 15 |
| Journal | IEEE Transactions on Signal Processing |
| Volume | 47 |
| Issue number | 2 |
| DOIs | |
| State | Published - 1999 |
Bibliographical note
Funding Information:Manuscript received January 27, 1997; revised August 21, 1998. This work was supported by the Office of Naval Research under Grant N00014-93-1-0485. The associate editor coordinating the review of this paper and approving it for publication was Prof. James Bucklew.
Keywords
- Ambiguity function
- Performance bounds
- Signal modeling
- Sonar radar