Date

2010

Author

Filik, Tansu

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In this thesis, two-dimensional (2-D) direction-of-arrival (DOA) estimation problem is considered. Usually, DOA estimation is considered in one dimension assuming a fixed elevation angle. While this assumption simplifies the problem, both the azimuth and elevation angles, namely, the 2-D DOA estimates are required in practical scenarios. In this thesis, planar array structures are considered for 2-D DOA estimation. In this context, V-shaped arrays are discussed and some of the important features of these arrays are outlined. A new method for the design of V-shaped arrays is presented for both isotropic and directional beam patterns. The design procedure is simple and can be applied for both uniform and nonuniform V-shaped sensor arrays. Closed form expressions are presented for the V-angle in order to obtain isotropic angle performance. While circular arrays have the isotropic characteristics, V-shaped arrays present certain advantages due to their large aperture for the same number of sensors and inter-sensor distance. The comparison of circular and V-shaped arrays is done by considering the azimuth and elevation Cramer-Rao Bounds (CRB). It is shown that V-shaped and circular arrays have similar characteristics for the sensor position errors while the uniform isotropic (UI) V-array performs better when there is mutual coupling and the sources are correlated. In the literature, there are several techniques for 2-D DOA estimation. Usually, fast algorithms are desired for this purpose since a search in two dimensions is a costly process. These algorithms have a major problem, namely, the pairing of the azimuth-elevation couples for multiple sources. In this thesis, a new fast and effective technique for this purpose is proposed. In this technique, a virtual array output is generated such that when the ESPRIT algorithm is used, the eigenvalues of the rotational transformation matrix have the 2-D angle information in both magnitude and phase. This idea is applied in different scenarios and three methods are presented for these cases. In one case, given an arbitrary array structure, array interpolation is used to generate the appropriate virtual arrays. When the antenna mutual coupling is taken into account, a special type of array structure, such as circular, should be used in order to apply the array interpolation. In general, the array mutual coupling matrix (MCM) should have a symmetric Toeplitz form. It is shown that the 2-D DOA performance of the proposed method approaches to the CRB by using minimum number of antennas in case of mutual coupling. This method does not require the estimation of the mutual coupling coefficients. While this technique is effective, it has problems especially when the number of sources increases. In order to improve the performance, MCM is estimated in the third approach. This new approach performs better, but it cannot be used satisfactorily in case of multipath signals. In this thesis, the proposed idea for fast 2-D DOA estimation is further developed in order to solve the problem when mutual coupling and multipath signals jointly exist. In this case, real arrays with some auxiliary sensors are used to generate a structured mutual coupling matrix. It is shown that the problem can be effectively solved when the array structure has a special form. Specifically, parallel uniform linear arrays (PULA) are employed for this purpose. When auxiliary sensors are used, a symmetric banded Toeplitz MCM is obtained for the PULA. This allows the application of spatial smoothing and ESPRIT algorithm for 2-D DOA estimation. The proposed algorithm uses triplets and presents closed form paired 2-D DOA estimates in case of unknown mutual coupling and multipath signals. Several simulations are done and it is shown that the proposed array structure and the method effectively solve the problem.

Subject Keywords

Electrical and Electronics Engineering.

URI

http://etd.lib.metu.edu.tr/upload/3/12611841/index.pdf
https://hdl.handle.net/11511/19722

Collections

Graduate School of Natural and Applied Sciences, Thesis