Sparse linear sensor arrays: analysis of recent coarray based arrays and array design for nonlinear processing

Epçaçan, Erdal
In this thesis, sparse linear sensor arrays have been studied. The study of sparse arrays in this work can be considered under two main headings: Analysis and comparison of recently proposed coarray based arrays, and the adaptation of the nonlinear apodization method for linear arrays and its use in sparse linear array design. Recently proposed coarray-based sparse arrays are designed with closed form structures without the need for any optimization and have much higher degrees of freedom (DOF) than a uniform linear array with the same number of sensors. DOF gives the number of targets that can be resolved. In this thesis, the analysis and comparison of the most known of these arrays have been made by considering the accuracy in direction of arrival, DOF, resolution in direction of arrival and mutual coupling. The aim is to reveal the advantages, disadvantages, and aspects accompanying the increased DOF. As a result of the simulations, it can be concluded that the increase in the DOF and in the resolution of direction of arrival is mainly provided by the enlarged array aperture. On the other hand, the effective use of the enlarged array aperture and no need of any optimization are superiority of these methods. Nonlinear apodization has been used to solve the trade off between sidelobe level and mainlobe width. In this method, it is aimed to suppress sidelobe levels without increasing the mainlobe width. In this thesis, a variant of nonlinear apodization has been adapted to the spatial domain and it is used in beamforming. One of the most common problems in the design of sparse arrays is the increase in the sidelobe level and/or the emergence of grating lobes while narrowing the mainlobe width. Considering the success of the nonlinear apodization method in this topic, a sparse linear array design method using nonlinear apodization and the genetic algorithm is proposed.


Filik, Tansu; Tuncer, Temel Engin (2008-07-23)
In this study, isotropic V-shaped uniform and nonuniform arrays are considered. An isotropic array has the same value for the Cramer-Rao bound (CRB) for all direction of arrival (DOA) angles. The conditions for isotropic V-shaped arrays are presented and closed form expressions for V-shaped uniform and nonuniform arrays are found. These expressions return the V-angle for the array. Therefore, given the number of sensors and sensor displacements, isotropic performance V-angle can be found easily. V-shaped ar...
TRACEMIN Fiedler A Parallel Algorithm for Computing the Fiedler Vector
Manguoğlu, Murat; Saied, Faisal; Sameh, Ahmed (null; 2010-06-25)
The eigenvector corresponding to the second smallest eigenvalue of the Laplacian of a graph, known as the Fiedler vector, has a number of applications in areas that include matrix reordering, graph partitioning, protein analysis, data mining, machine learning, and web search. The computation of the Fiedler vector has been regarded as an expensive process as it involves solving a large eigenvalue problem. We present a novel and efficient parallel algorithm for computing the Fiedler vector of large graphs bas...
Collaborative Direction of Arrival estimation by using Alternating Direction Method of Multipliers in distributed sensor array networks employing Sparse Bayesian Learning framework
Nurbas, Ekin; Onat, Emrah; Tuncer, Temel Engin (2022-10-01)
In this paper, we present a new method for Direction of Arrival (DoA) estimation in distributed sensor array networks by using Alternating Direction Method of Multipliers (ADMM) in Sparse Bayesian Learning (SBL) framework. Our proposed method, CDoAE, has certain advantages compared to previous distributed DoA estimation methods. It does not require any special array geometry and there is no need for inter -array frequency and phase matching. CDoAE uses the distributed ADMM to update the parameter set extrac...
Analysis Window Length Selection For Linear Signal Models
Yazar, Alper; Candan, Çağatay (2015-05-19)
A method is presented for the selection of analysis window length, or the number of input samples, for linear signal modeling without compromising the model assumptions. It is assumed that the signal of interest lies in a known linear space and noisy samples of the signal is provided. The goal is to use as many signal samples as possible to mitigate the effect of noise without violating the assumptions on the model. An application example is provided to illustrate the suggested method.
Investigation of tightly coupled arrays for wideband applications
Arda, Kaan; Dural Ünver, Mevlüde Gülbin; Department of Electrical and Electronics Engineering (2020-10)
This thesis aims to provide in depth research on tightly coupled dipole arrays to be used in ultrawideband apertures applications. First, operation principles of tightly coupled dipole arrays are investigated. Starting from the Wheeler’s current sheet aperture concept, some calculations on bandwidth and impedance concepts are conducted. B.A. Munk’s addition to the concept, use of capacitive elements between adjacent dipoles, are introduced. Array unit cell is modeled using equivalent circuit approach,...
Citation Formats
E. Epçaçan, “Sparse linear sensor arrays: analysis of recent coarray based arrays and array design for nonlinear processing,” Ph.D. - Doctoral Program, Middle East Technical University, 2021.