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Performance improvement of doa estimation by multiple signal classification techniques music using wavelet denoising
Dissertant
University
University of Technology
Faculty
-
Department
Department of Electrical Engineering
University Country
Iraq
Degree
Master
Degree Date
2009
English Abstract
Different methods to estimate Direction-Of-Arrival (DOA), Multiple Signal Classification (MUSIC) Techniques, Maximum likelihood (ML) Techniques and Estimation of Signal Parameter via Rotational Invariame Techniques (ESPRIT) This thesis studied Multiple Signal Classification (MUSIC) Techniques with many cases ( single, two and multi-sources), also studied Wavelet Denoting, by taking each Techniques alone and by using Wavelet Demising with Multiple Signal Classification (MUSIC) to performance the estimation of Direction-Of-Arrival (DOA) by reducing the noise for the received signal in the sensors with less noise signal.
For Wavelet Demising we used many basic function of wavelet like (Haar (dbl), Daubechies (dbN)f Symlets (symN), Coifiets (coifN), Biorthogonal (biorN).
The results yvhich studied for Multiple Signal Classification (MUSIC) Techniques by itself and the results for this Techniques by using Wavelet Demising with it had been compared, comparisons had been done for each case (one emitter, two or multi emitters ) to study the best results and for which type.
This thesis containing performance of estimation of Direction-Of-Arrival (DOA) with the idea that Wave, Denoting improves rhe Sjgna, noisy signal.
This proceeded to perform Wavelet Demising of the signal from each sensor of the array independently, prior to estimating the DOA.
Also, this thesis studied all the possibilities for each case, which dealing With Coherent and Non-Coherent signal, closely signal.
Ahoy by changing, he number of snapshots to find the effect of this changing on both Techniques by comparing it together.
This thesis has prayed that the sum of wavelet demising with MUSIC is high resolution than using the MUSIC technique only.
The results done by using a computer program "MATLAB- Version 7.0 to get a hitter estimation bisection-Of-Arrival (DOA).
Main Subjects
Topics
American Psychological Association (APA)
Muhammad, Muhammad Sami. (2009). Performance improvement of doa estimation by multiple signal classification techniques music using wavelet denoising. (Master's theses Theses and Dissertations Master). University of Technology, Iraq
https://search.emarefa.net/detail/BIM-305032
Modern Language Association (MLA)
Muhammad, Muhammad Sami. Performance improvement of doa estimation by multiple signal classification techniques music using wavelet denoising. (Master's theses Theses and Dissertations Master). University of Technology. (2009).
https://search.emarefa.net/detail/BIM-305032
American Medical Association (AMA)
Muhammad, Muhammad Sami. (2009). Performance improvement of doa estimation by multiple signal classification techniques music using wavelet denoising. (Master's theses Theses and Dissertations Master). University of Technology, Iraq
https://search.emarefa.net/detail/BIM-305032
Language
English
Data Type
Arab Theses
Record ID
BIM-305032