Abstract

In the framework of the synthesis of monopulse array antennas for search-and-track applications, the thesis focuses on the development and the analysis of a method based on the sub-arraying technique aimed at generating an optimal sum and compromise difference patterns through an excitation matching procedure. By exploiting some properties of the solution space, the synthesis problem is reformulated as a combinatorial one to allow a considerable saving of computational resources. Thanks to a graph-based representation of the solution space, the use of an efficient path-searching algorithm to speed-up the convergence of the procedure for the synthesis of large array antennas as well as the use of the Ant Colony Optimizer (ACO) to benefit of its hill-climbing properties in dealing with the non-convexity of the sub-arraying problem are considered. Moreover, a hybrid approach is developed to individually control the level of the secondary lobes. In particular, the sub-array configuration is determined at the first step by exploiting the knowledge of the optimum difference mode coefficients and in the second step, the sub-array weights are computed by means of a quadratic programming procedure. In the numerical validation, a set of representative examples concerned with both pattern matching problems and pattern-feature optimization are reported in order to assess the effectiveness and flexibility of the proposed approach. Comparisons with previously published results are reported and discussed, as well.