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Empirical optimization is an algorithm for the optimization of antenna array performance under realistic conditions, accounting for the effects of mutual coupling and scattering between the elements of the array and the nearby environment. The algorithm can synthesize optimum element spacings and optimum element excitations. It is applicable to arrays of various element types having arbitrary configurations, including phased arrays, conformal arrays and nonuniformly spaced arrays. The method is based on measured or calculated element-pattern data, and proceeds in an iterative fashion to the optimum design. A novel method is presented in which the admittance matrix representing an antenna array, consisting of both active and passive elements, is extracted from the array's element-pattern data. The admittance-matrix formulation incorporated into the empirical optimization algorithm enables optimization of the location of both passive and active elements. The methods also provide data for a linear approximation of coupling as a function of (nonuniform) element locations, and for calculation of element scan impedances. Computational and experimental results are presented that demonstrate the rapid convergence and effectiveness of empirical optimization in achieving realistic antenna array performance optimization.