Joint 2D-DOA and Carrier Frequency Estimation Technique Using Nonlinear Kalman Filters for Cognitive Radio
The problem of jointly estimating carrier frequencies and their corresponding two-dimension direction of arrivals (DOA) of band-limited source signals is considered in this paper for cognitive radio. The main problem of estimating carrier frequencies spread over a wideband spectrum is the requiremen...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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IEEE
2017-01-01
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| Series: | IEEE Access |
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| Online Access: | https://ieeexplore.ieee.org/document/8091116/ |
| _version_ | 1819168499179716608 |
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| author | Samar Elaraby Heba Y. Soliman Heba M. Abdel-Atty Mohamed A. Mohamed |
| author_facet | Samar Elaraby Heba Y. Soliman Heba M. Abdel-Atty Mohamed A. Mohamed |
| author_sort | Samar Elaraby |
| collection | DOAJ |
| description | The problem of jointly estimating carrier frequencies and their corresponding two-dimension direction of arrivals (DOA) of band-limited source signals is considered in this paper for cognitive radio. The main problem of estimating carrier frequencies spread over a wideband spectrum is the requirement of high sampling rates. Thus, the Kalman filters are applied in the spatial domain instead of the temporal domain in the proposed algorithm to relax hardware complexity. The proposed algorithm exploits both the azimuth and elevation angles instead of a single DOA to increase the spatial capacity. Two approaches are proposed using two different types of nonlinear Kalman filter: extended Kalman filter (EKF) and unscented Kalman filter (UKF). Using simulations, the factors that affect the performance of both the filters are discussed. Scaling the estimated parameters to the same range and the proper tuning and initialization of the filters are crucial factors to prevent the filter divergence. Although UKF is supposed to have a better performance than EKF, reducing the inter-element spacing of the employed arrays and the proper filter initialization can make EKF approach the performance of UKF. On the other hand, UKF suffers from high processing time. Overall, both filters are able to converge to the true values of the unknown parameters using a number of relaxed analog-to-digital converters equal to the number of the array elements in the employed arrays. However, the approaches can detect a number of source signals higher than one-third of the total number of the array elements. |
| first_indexed | 2024-12-22T19:04:34Z |
| format | Article |
| id | doaj.art-9d75faa67f054bae9d06893e85804645 |
| institution | Directory Open Access Journal |
| issn | 2169-3536 |
| language | English |
| last_indexed | 2024-12-22T19:04:34Z |
| publishDate | 2017-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj.art-9d75faa67f054bae9d06893e858046452022-12-21T18:15:51ZengIEEEIEEE Access2169-35362017-01-015250972510910.1109/ACCESS.2017.27682218091116Joint 2D-DOA and Carrier Frequency Estimation Technique Using Nonlinear Kalman Filters for Cognitive RadioSamar Elaraby0https://orcid.org/0000-0002-7959-1100Heba Y. Soliman1Heba M. Abdel-Atty2Mohamed A. Mohamed3Electrical Engineering Department, Faculty of Engineering, Port Said University, Port Said, EgyptElectrical Engineering Department, Faculty of Engineering, Port Said University, Port Said, EgyptElectrical Engineering Department, Faculty of Engineering, Port Said University, Port Said, EgyptElectronics and Communication Engineering Department, Faculty of Engineering, Mansoura University, Mansoura, EgyptThe problem of jointly estimating carrier frequencies and their corresponding two-dimension direction of arrivals (DOA) of band-limited source signals is considered in this paper for cognitive radio. The main problem of estimating carrier frequencies spread over a wideband spectrum is the requirement of high sampling rates. Thus, the Kalman filters are applied in the spatial domain instead of the temporal domain in the proposed algorithm to relax hardware complexity. The proposed algorithm exploits both the azimuth and elevation angles instead of a single DOA to increase the spatial capacity. Two approaches are proposed using two different types of nonlinear Kalman filter: extended Kalman filter (EKF) and unscented Kalman filter (UKF). Using simulations, the factors that affect the performance of both the filters are discussed. Scaling the estimated parameters to the same range and the proper tuning and initialization of the filters are crucial factors to prevent the filter divergence. Although UKF is supposed to have a better performance than EKF, reducing the inter-element spacing of the employed arrays and the proper filter initialization can make EKF approach the performance of UKF. On the other hand, UKF suffers from high processing time. Overall, both filters are able to converge to the true values of the unknown parameters using a number of relaxed analog-to-digital converters equal to the number of the array elements in the employed arrays. However, the approaches can detect a number of source signals higher than one-third of the total number of the array elements.https://ieeexplore.ieee.org/document/8091116/2D-DOA estimationcognitive radioextended Kalman filterspectrum sensingunscented Kalman filter |
| spellingShingle | Samar Elaraby Heba Y. Soliman Heba M. Abdel-Atty Mohamed A. Mohamed Joint 2D-DOA and Carrier Frequency Estimation Technique Using Nonlinear Kalman Filters for Cognitive Radio IEEE Access 2D-DOA estimation cognitive radio extended Kalman filter spectrum sensing unscented Kalman filter |
| title | Joint 2D-DOA and Carrier Frequency Estimation Technique Using Nonlinear Kalman Filters for Cognitive Radio |
| title_full | Joint 2D-DOA and Carrier Frequency Estimation Technique Using Nonlinear Kalman Filters for Cognitive Radio |
| title_fullStr | Joint 2D-DOA and Carrier Frequency Estimation Technique Using Nonlinear Kalman Filters for Cognitive Radio |
| title_full_unstemmed | Joint 2D-DOA and Carrier Frequency Estimation Technique Using Nonlinear Kalman Filters for Cognitive Radio |
| title_short | Joint 2D-DOA and Carrier Frequency Estimation Technique Using Nonlinear Kalman Filters for Cognitive Radio |
| title_sort | joint 2d doa and carrier frequency estimation technique using nonlinear kalman filters for cognitive radio |
| topic | 2D-DOA estimation cognitive radio extended Kalman filter spectrum sensing unscented Kalman filter |
| url | https://ieeexplore.ieee.org/document/8091116/ |
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