Multidimensional polynomial phase estimation
An estimation method is presented for polynomial phase signals, i.e., those adopting the form of a complex exponential whose phase is polynomial in its indices. Transcending the scope of existing techniques, the proposed estimator can handle an arbitrary number of dimensions and an arbitrary set of...
| Autores: | , , |
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| Tipo de recurso: | artículo |
| Estado: | Versión publicada |
| Fecha de publicación: | 2025 |
| País: | España |
| Institución: | Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya) |
| Repositorio: | Recercat. Dipósit de la Recerca de Catalunya |
| OAI Identifier: | oai:recercat.cat:10230/71167 |
| Acceso en línea: | http://hdl.handle.net/10230/71167 http://dx.doi.org/10.1109/OJSP.2025.3577503 |
| Access Level: | acceso abierto |
| Palabra clave: | Polynomial phase signal Estimation theory Cramer-Rao bound Minimum mean-square error Phase wrapping Phase ambiguity Signal reconstruction Circular averaging |
| Sumario: | An estimation method is presented for polynomial phase signals, i.e., those adopting the form of a complex exponential whose phase is polynomial in its indices. Transcending the scope of existing techniques, the proposed estimator can handle an arbitrary number of dimensions and an arbitrary set of polynomial degrees along each dimension; the only requirement is that the number of observations per dimension exceeds the highest degree thereon. Embodied by a highly compact sequential algorithm, this estimator is efficient at high signal-to-noise ratios (SNRs), exhibiting a computational complexity that is strictly linear in the number of observations and at most quadratic in the number of polynomial terms. To reinforce the performance at low and medium SNRs, where any phase estimator is bound to be hampered by the inherent ambiguity caused by phase wrappings, suitable functionalities are incorporated and shown to be highly effective. |
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