مقاله Quadratically Constrained Beamforming Applied to UCA با word
مقاله Quadratically Constrained Beamforming Applied to UCA با word دارای 6 صفحه می باشد و دارای تنظیمات در microsoft word می باشد و آماده پرینت یا چاپ است
فایل ورد مقاله Quadratically Constrained Beamforming Applied to UCA با word کاملا فرمت بندی و تنظیم شده در استاندارد دانشگاه و مراکز دولتی می باشد.
این پروژه توسط مرکز مرکز پروژه های دانشجویی آماده و تنظیم شده است
توجه : در صورت مشاهده بهم ریختگی احتمالی در متون زیر ،دلیل ان کپی کردن این مطالب از داخل فایل ورد می باشد و در فایل اصلی مقاله Quadratically Constrained Beamforming Applied to UCA با word،به هیچ وجه بهم ریختگی وجود ندارد
بخشی از متن مقاله Quadratically Constrained Beamforming Applied to UCA با word :
سال انتشار: 1391
محل انتشار: بیستمین کنفرانس مهندسی برق ایران
تعداد صفحات: 6
نویسنده(ها):
Mohsen Askari – Shiraz University
Mahmood Karimi – Shiraz University
چکیده:
Uncertainty in direction of arrival (DOA) of desired signal may degrade performance of minimum variance distortionless response (MVDR) beamformer severely. In this paper wefocus on an optimum beamformer which is robust to DOA errors and developed the beamformer to uniform circular arrays (UCA).Like traditional optimum beamformers, this beamformer must minimize the output power. Furthermore, in this beamformer, two extra constraints are imposed. These constraints force thebeamformer to have gains greater than unity in two angles. In fact, we assume that DOA of desired signal is unknown, butit lies in the interval between two angles that we build our constraints. The diagonal loading method is used to make thebeamformer gain to exceed unity in the interval between the two angles. The loading factor is calculated using a numericalalgorithm. Complexity of this beamformer is the same as MVDRbeamformer. Simulation results obtained for UCA show that the proposed beamformer has a good performance compared to linearly constrained minimum variance (LCMV) beamformer, traditional diagonal loading (DL) method, and extended diagonalloading method. Also it is shown that performance of the beamformer is robust against errors caused by estimating the autocorrelation matrix.
