Abstract
In this study, intelligent hybrid computing techniques are developed using variants of genetic algorithms (GAs) to estimate jointly direction of arrival and amplitude of electromagnetic plane waves. Fitness evaluation function is formulated for parameter estimation model by exploiting the approximation theory in mean square sense based on error between the desired and estimated responses. Optimization of design variables of the model is carried out with hybrid schemes through variant of GAs integrated with sequential quadratic programming for rapid refinement. Proposed schemes are applied to number of electromagnetic plane waves impinging on uniform linear array from different directions with different amplitudes. Comparison of the results is done with true parameters of the system in order to evaluate the performance of the algorithms. Monte-Carlo simulations for the design approaches are carried out to analyze their strength in terms of estimation accuracy, robustness against noise, convergence and proximity effects.
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Appendix: Detailed results for all twelve variants of GA and GASQP in case of all three scenarios of the problem for each noise variances are presented in Appendix A, B and C of “Appendix.docx” file, which is available as an online supplementary material on the web site of the journal (DOCX 368 kb)
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Akbar, S., Raja, M.A.Z., Zaman, F. et al. Design of Bio-inspired Heuristic Techniques Hybridized with Sequential Quadratic Programming for Joint Parameters Estimation of Electromagnetic Plane Waves. Wireless Pers Commun 96, 1475–1494 (2017). https://doi.org/10.1007/s11277-017-4251-y
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DOI: https://doi.org/10.1007/s11277-017-4251-y