پديد آورنده :
قنبري، حامد
عنوان :
تخمين زاويه ورود در حضور عدم كاليبراسيون و آرايه ي معيوب با رويكرد يادگيري ديكشنري
مقطع تحصيلي :
كارشناسي ارشد
گرايش تحصيلي :
مخابرات سيستم
محل تحصيل :
اصفهان: دانشگاه صنعتي اصفهان، دانشكده برق و كامپيوتر
صفحه شمار :
دوازده، 91ص.: مصور، جدول، نمودار
يادداشت :
ص.ع. به فارسي و انگليسي
استاد راهنما :
احسان يزديان
استاد مشاور :
هادي زيّاني
توصيفگر ها :
يادگيري ديكشنري , زاويه‌يابي , كاليبراسيون , حسگر معيوب
استاد داور :
[محمود مدرس هاشمي]،[محمد مهدي نقش]
تاريخ ورود اطلاعات :
1396/05/31
رشته تحصيلي :
برق و كامپيوتر
دانشكده :
مهندسي برق و كامپيوتر
چكيده انگليسي :
Estimation of The Direction of Arrival InThe Presence of Non Calibration and Failed Sensor Using Dictionary Learning Approach Hamed Ghanbari July 30 2017 Department of Electrical and Computer Engineering Isfahan University of Technology Isfahan 84156 83111 Iran Degree M Sc Language Farsi Supervisor Dr Ehsan Yazdian Advisor Dr H ZayyaniAbstract Direction of Arrival DOA estimation is one of the important subjects in communication and radar systems and diversemethods have been suggested to address this problem These methods are divided into three main parts classical andsubspace and sparse signal processing based methods In The most of the sparse based methods it is needed to build acandidate dictionary of angles with high resolution to have an accurate DOA estimation However In the real world thesources are not necessarily located on the atoms of the dictionary which results in DOA estimation error Recently dictionarylearning is employed to address this issue The idea is using dictionary learning to adapt the angles of atoms according tothe observed signals In this research dictionary learning is studied and we extend the application of this idea to multiplesnapshot cases Another source of error in DOA estimation is the non calibrated arrays Employing dictionary learningapproach we also suggest a new method to combat degrading effects of non idealities of the array such as gain phase coupling and displacement errors In all of these applications the proposed method for updating the dictionary is based onparametric dictionary learning and we use simple gradient descent algorithm Array failure is another topic which has beenstudied in this research and a new algorithm is suggested to solve this problem We also generalize some of the results to thecase of wideband DOA estimation To show the superiority of the proposed algorithms in each part of the thesis varioussimulations are done in different scenarios with one or multiple snapshots Key Words Dictionary Learning DOA Estimation Calibration Array Failure
استاد راهنما :
احسان يزديان
استاد مشاور :
هادي زيّاني
استاد داور :
[محمود مدرس هاشمي]،[محمد مهدي نقش]
