Adaptive antenna techniques for smart antennas and radar systems

This dissertation deals with three problems in the area of adaptive array processing for smart antenna and radar systems. First, the equivalent isotropically radiated power (EIRP) degradation due to random position errors in the location of the antenna elements in an array is derived through the expected value and standard deviation of the EIRP. The minimum tolerance of the array elements is presented by means of the relationship between the EIRP degradation and a standard deviation or the uniform bound of the probability distribution. Using this tolerance, the output signal to interference and noise ratio (SINR) is examined in the framework of adaptive processing using the direct data domain least squares (D 3 LS) approach. Also, it is applied to Space-Time Adaptive Processing (STAP). Then, a technique is presented on how to enhance the received signals in a near field multi-input multi-output (MIMO) environment where beam forming is not possible. This is done through the use of adaptivity on transmit. The methodology is to select a set of weights adapted to each receiver to be applied to each transmitting antenna so that the transmitted signal at the carrier frequency may be directed to a particular receiver location while simultaneously minimizing the received signal strengths at other receiver locations. Numerical simulations have been made to illustrate the novelty of the proposed approach. As a final topic, to choose the proper number of virtual array elements consisting of isotropic omni-directional point radiators operating in free space starting from a real array for direction of arrival (DOA) estimation and adaptive processing is derived from an arbitrary shaped nonuniformly spaced conformal array operating with mutual coupling effects using a single snapshot of the data. The number of elements in the virtual array is determined by using the singular value decomposition (SVD) of a real array manifold and the concept of interpolation. The transformation matrix is computed using the virtual array manifold and the real array manifold. Numerical simulations have been made to illustrate the accuracy of the proposed approach. The direction of arrival (DOA) of the signals using the Matrix Pencil method and the direct data domain least squares (D 3 LS) adaptive processing is estimated in evaluating the complex amplitude of the signal incident on a hemispherical array