Seyrek doğrusal sensör dizinleri: Güncel coarray tabanlı dizinlerin analizi ve doğrusal olmayan işleme için dizin tasarımı

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.