Rfıd Bazlı Navigasyon Sistem Algoritmalarının Karşılaştırılmaları ve Entegrasyonu

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2016

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Department of Electrical & Electronics Engineering
Department of Electrical and Electronics Engineering (EE) offers solid graduate education and research program. Our Department is known for its student-centered and practice-oriented education. We are devoted to provide an exceptional educational experience to our students and prepare them for the highest personal and professional accomplishments. The advanced teaching and research laboratories are designed to educate the future workforce and meet the challenges of current technologies. The faculty's research activities are high voltage, electrical machinery, power systems, signal and image processing and photonics. Our students have exciting opportunities to participate in our department's research projects as well as in various activities sponsored by TUBİTAK, and other professional societies. European Remote Radio Laboratory project, which provides internet-access to our laboratories, has been accomplished under the leadership of our department with contributions from several European institutions.

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Bu tezin ana çalışma konusu, farklı konum hesaplama algoritmalarını kullanarak, küçük ölçekli bina içi uygulamarında kullanılmak üzere hareket halindeki bir nesnenin konumunu bulmak ve bu nesneyi takip edebilmeyi ortaya koymaktadır. Bu tez çalışmasında kullanılmak üzere, RFID sistem görüş menzil problemi olmadığından dolayı tercih edilmiş ve pasif bir RFID etiketi hem batarya tüketimi hem de gerçek zamanlı uygulamalar için daha kullanışlı olaması sebebiyle seçilmiştir. Üç farklı konum hesaplama algoritmaları olan Üçgenleme, Ağırlık Merkezli Konumlandırma ve Bayes Karar Algoritması araştırılmış ve birbirleriyle karşılaştırılmıştır. Bayes Karar Algoritması ayrıca Kalman filtre ile entegre edilmiştir. Bu tez çalışmasında hareketli bir nesnenin anlık konumunu bulabilmek için, elektromanyetik teori ve RF bilgisinin yanı sıra sinyal işleme ile ilgili bilgileri içermektedir.
The main subject of this thesis study reveals localization finding of a mobile object for small scale indoor environment by using several different location estimation algorithms. The RFID system is preferred to use in the thesis due to non line of sight problem and the passive RFID tag was chosen for both in saving in battery consumption and being more practical in real time application. Three different location estimation algorithms were searched and compared each other as follows: Triangulation, Weighted Centroid Localization (WCL) and Bayes Decision Rule. Bayes Decision Rule is also integrated with Kalman filter. The study requires signal processing techniques with electromagnetic theories and radio frequency (RF) knowledges for finding the current position of the mobile object.

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Elektrik ve Elektronik Mühendisliği, Bayes Kestirim Yöntemi, Bayes teorisi, Bayes yaklaşımı, Electrical and Electronics Engineering, Bayes yöntemi, Bayes Estimation Method, Bina içi haberleşme, Bayes theory, Bayes approach, Hedef konumlandırma, Bayesian method, Indoor communication, Kalman filtre, Target localization, Kapalı ortam, Kalman filter, Indoor, Sınıfsal konum, Class position

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