10386

9581

كارشناسي ارشد

مخابرات سيستم

اصفهان: دانشگاه صنعتي اصفهان، دانشكده برق و كامپيوتر

1394

دوازده، 81ص.: مصور، جدول، نمودار

احسان يزديان، علي اكبر تدين

1394/06/02

علي محمد دوست حسيني

1396/10/04

كتابنامه

برق و كامپيوتر

مهندسي برق و كامپيوتر

ID9581

به فارسي و انگليسي

Evaluation and Improvement of Subspace Algorithms for Direction of Arrival Estimation Mahmoud Ahmadi Bashkani mahmoud ahmadi@ec iut ac ir Department of Electrical and Computer Engineering Isfahan University of Technology Isfahan 84156 83111 Iran Degree Master of Science Language FarsiEhsan Yazdian Dr Supervisor yazdian@cc iut ac irAli Akbar Tadaion Dr Supervisor tadaion@yazd ac irAbstractDirection of arrival DOA estimation of signal sources is one of the most challenging and practical issues in many areassuch as wireless communications radar radio astronomy sonar and navigation In this thesis we investigate the directionof arrival estimation algorithms in array antennas Among these methods subspace based algorithms are most well knownfor good performance with respect to the computational complexity This thesis will focus on these algorithms especiallythe multiple signal classification MUSIC ESPRIT and Root MUSIC method These algorithms mainly use the maximumlikelihood estimation of the covariance matrix so called sample covariance matrix SCM It can be argued that the accuracyof direction of arrival estimation depends on the accuracy of the SCM estimation It is important to note that the samplecovariance matrix estimation is not accurate and reliable in many practical situations e g when the number of snapshots N and the number of antenna array elements M are both large and of the same order Under these conditions the randommatrix theory claims to make a more reasonable approximation to the distribution function of the eigenvalues of the SCM byanalyzing the behavior of this matrix in this asymptotic regime This thesis aims to improve the subspace based algorithmsunder the new asymptotic regime and the noise types with heavy tailed distributions such as impulsive noise conditions However the performance of the SCM and resulting the direction of arrival estimation degrade in non Gaussian noise Inthis thesis at the first we use the Marrona Estimator to improve the ESPRIT and Root MUSIC algorithms and the next weuse convex optimization methods to improve the DOA estimation algorithm G MUSIC by modifying the eigenvector andeigenvalue estimation of the sample covariance matrix under non Gaussian noise conditions Simulation results confirmthis performance improvement Key Words Direction of Arrival DOA MUSIC G MUSIC Impulsive Noise

احسان يزديان، علي اكبر تدين

علي محمد دوست حسيني