Analysis of multicomponent polynomial phase signals
While the theory of estimation of monocomponent polynomial phase signals is well established, the theoretical and methodical treatment of multicomponent polynomial phase signals (mc-PPSs) is limited. In this paper, we investigate several aspects of parameter estimation for mc-PPSs and derive the Cra...
| Main Authors: | , |
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| Format: | Journal Article |
| Published: |
IEEE Signal Processing Society
2007
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| Online Access: | http://hdl.handle.net/20.500.11937/31850 |
| _version_ | 1848753498660798464 |
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| author | Pham, DucSon Zoubir, A. |
| author_facet | Pham, DucSon Zoubir, A. |
| author_sort | Pham, DucSon |
| building | Curtin Institutional Repository |
| collection | Online Access |
| description | While the theory of estimation of monocomponent polynomial phase signals is well established, the theoretical and methodical treatment of multicomponent polynomial phase signals (mc-PPSs) is limited. In this paper, we investigate several aspects of parameter estimation for mc-PPSs and derive the Crameacuter-Rao bound. We show the limits of existing techniques and then propose a nonlinear least squares (NLS) approach. We also motivate the use the Nelder-Mead simplex algorithm for minimizing the nonlinear cost function. The slight increase in computational complexity is a tradeoff for improved mean square error performance, which is evidenced by simulation results. |
| first_indexed | 2025-11-14T08:25:28Z |
| format | Journal Article |
| id | curtin-20.500.11937-31850 |
| institution | Curtin University Malaysia |
| institution_category | Local University |
| last_indexed | 2025-11-14T08:25:28Z |
| publishDate | 2007 |
| publisher | IEEE Signal Processing Society |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | curtin-20.500.11937-318502017-09-13T15:56:36Z Analysis of multicomponent polynomial phase signals Pham, DucSon Zoubir, A. While the theory of estimation of monocomponent polynomial phase signals is well established, the theoretical and methodical treatment of multicomponent polynomial phase signals (mc-PPSs) is limited. In this paper, we investigate several aspects of parameter estimation for mc-PPSs and derive the Crameacuter-Rao bound. We show the limits of existing techniques and then propose a nonlinear least squares (NLS) approach. We also motivate the use the Nelder-Mead simplex algorithm for minimizing the nonlinear cost function. The slight increase in computational complexity is a tradeoff for improved mean square error performance, which is evidenced by simulation results. 2007 Journal Article http://hdl.handle.net/20.500.11937/31850 10.1109/TSP.2006.882085 IEEE Signal Processing Society fulltext |
| spellingShingle | Pham, DucSon Zoubir, A. Analysis of multicomponent polynomial phase signals |
| title | Analysis of multicomponent polynomial phase signals |
| title_full | Analysis of multicomponent polynomial phase signals |
| title_fullStr | Analysis of multicomponent polynomial phase signals |
| title_full_unstemmed | Analysis of multicomponent polynomial phase signals |
| title_short | Analysis of multicomponent polynomial phase signals |
| title_sort | analysis of multicomponent polynomial phase signals |
| url | http://hdl.handle.net/20.500.11937/31850 |