Improvements in DOA estimation by array interpolation in non-uniform linear arrays

Yaşar, Temel Kaya
In this thesis a new approach is proposed for non-uniform linear arrays (NLA) which employs conventional subspace methods to improve the direction of arrival (DOA) estimation performance. Uniform linear arrays (ULA) are composed of evenly spaced sensor elements located on a straight line. ULA's covariance matrix have a Vandermonde matrix structure, which is required by fast subspace DOA estimation algorithms. NLA differ from ULA only by some missing sensor elements. These missing elements cause some gaps in covariance matrix and Vandermonde structure is lost. Therefore fast subspace DOA algorithms can not be applied in this case. Linear programming methods and array interpolation methods can be used to solve this problem. However linear programming is computationally expensive and array interpolation is angular sector dependent and requires the same number of sensor in the virtual array. In this thesis, a covariance matrix augmentation method is developed by using the array interpolation technique and initial DOA estimates. An initial DOA estimate is obtained by Toeplitz completion of the covariance matrix. This initial DOA estimates eliminates the sector dependency and reduces the least square mapping error of array interpolation. A Wiener formulation is developed which allows more sensors in the virtual array than the real array. In addition, it leads to better estimates at low SNR. The new covariance matrix is used in the root-MUSIC algorithm to obtain a better DOA estimate. Several computer simulations are done and it is shown that the proposed approach improves the DOA estimation accuracy significantly compared to the same number of sensor ULA. This approach also increases the number of sources that can be identifed.


Dense depth map estimation for object segmentation in multi-view video
Çığla, Cevahir; Alatan, Abdullah Aydın; Department of Electrical and Electronics Engineering (2007)
In this thesis, novel approaches for dense depth field estimation and object segmentation from mono, stereo and multiple views are presented. In the first stage, a novel graph-theoretic color segmentation algorithm is proposed, in which the popular Normalized Cuts 59H[6] segmentation algorithm is improved with some modifications on its graph structure. Segmentation is obtained by the recursive partitioning of the weighted graph. The simulation results for the comparison of the proposed segmentation scheme w...
Improvements to neural network based restoration in optical networks
Türk, Fethi; Bilgen, Semih; Department of Electrical and Electronics Engineering (2008)
Performance of neural network based restoration of optical networks is evaluated and a few possible improvements are proposed. Neural network based restoration is simulated with optical link capacities assigned by a new method. Two new improvement methods are developed to reduce the neural network size and the restoration time of severed optical connections. Cycle based restoration is suggested, which reduces the neural network structure by restoring the severed connections for each optical node, iterativel...
Tracker-aware detection : a theoretical and an experimental study
Aslan, Murat Şamil; Saranlı, Afşar; Department of Electrical and Electronics Engineering (2009)
A promising line of research attempts to bridge the gap between detector and tracker by means of considering jointly optimal parameter settings for both of these subsystems. Along this fruitful path, this thesis study focuses on the problem of detection threshold optimization in a tracker-aware manner so that a feedback from the tracker to the detector is established to maximize the overall system performance. Special emphasis is given to the optimization schemes based on two non-simulation performance pred...
Modelling of X-Band electromagnetic wave propagation
Pelgur, Ali; Koç, Seyit Sencer; Department of Electrical and Electronics Engineering (2007)
Calculation of electromagnetic wave propagation over irregular terrain is an important problem in many applications such as coverage calculations for radars or communication links. Many different approaches to this problem may be found in the literature. One of the most commonly used methods to solve electromagnetic boundary value problems is the Method of Moments (MoM). However, especially at high frequencies, the very large number of unknows required in the MoM formulation, limits the applicability of thi...
Investigation of music algorithm based and wd-pca method based electromagnetic target classification techniques for their noise performances
Ergin, Emre; Sayan, Gönül; Department of Electrical and Electronics Engineering (2009)
Multiple Signal Classification (MUSIC) Algorithm based and Wigner Distribution-Principal Component Analysis (WD-PCA) based classification techniques are very recently suggested resonance region approaches for electromagnetic target classification. In this thesis, performances of these two techniques will be compared concerning their robustness for noise and their capacity to handle large number of candidate targets. In this context, classifier design simulations will be demonstrated for target libraries con...
Citation Formats
T. K. Yaşar, “Improvements in DOA estimation by array interpolation in non-uniform linear arrays,” M.S. - Master of Science, Middle East Technical University, 2006.