Parameter Estimation of Composite Continuous Wave Signals in the Presence of Non-Gaussian noise
El-Bakly, A., Fouda, A., Abdelkawy, E. (2010). Parameter Estimation of Composite Continuous Wave Signals in the Presence of Non-Gaussian noise. EKB Journal Management System, 7(7th International Conference on Electrical Engineering ICEENG 2010), 1-11. doi: 10.21608/iceeng.2010.32981
Ahmed El-Bakly; Abd Elmonem E. Fouda; Ezz. Eldin Abdelkawy. "Parameter Estimation of Composite Continuous Wave Signals in the Presence of Non-Gaussian noise". EKB Journal Management System, 7, 7th International Conference on Electrical Engineering ICEENG 2010, 2010, 1-11. doi: 10.21608/iceeng.2010.32981
El-Bakly, A., Fouda, A., Abdelkawy, E. (2010). 'Parameter Estimation of Composite Continuous Wave Signals in the Presence of Non-Gaussian noise', EKB Journal Management System, 7(7th International Conference on Electrical Engineering ICEENG 2010), pp. 1-11. doi: 10.21608/iceeng.2010.32981
El-Bakly, A., Fouda, A., Abdelkawy, E. Parameter Estimation of Composite Continuous Wave Signals in the Presence of Non-Gaussian noise. EKB Journal Management System, 2010; 7(7th International Conference on Electrical Engineering ICEENG 2010): 1-11. doi: 10.21608/iceeng.2010.32981

Parameter Estimation of Composite Continuous Wave Signals in the Presence of Non-Gaussian noise

The International Conference on Electrical Engineering
Article 34, Volume 7, 7th International Conference on Electrical Engineering ICEENG 2010, May 2010, Page 1-11  XML PDF (126.3 K)
Document Type: Original Article
DOI: 10.21608/iceeng.2010.32981
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Authors
Ahmed El-Bakly1; Abd Elmonem E. Fouda2; Ezz. Eldin Abdelkawy3
1Arab Academy for Science & Navy.
2Modern Academy.
3Military Technical College.
Abstract
An algorithm for estimation of the amplitudes and phases of composite Continuous Wave (CW) signals is considered. The signals are contaminated with non-Gaussian noise. The considered noise model is the most commonly exist in communication applications. The developed algorithm for estimating the amplitudes and phases of composite CW signals is based on the Expectation Maximization (EM) algorithm. The most feature of the developed algorithm is that it reduces the complicated multiparameters optimization required when using the ML approach. The complexity of the algorithm is essentially unaffected by increasing the number of composite signals. Simulation experiment is performed to illustrate the performance of the developed algorithm.
Keywords
spectral analysis; Expectation Maximization
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