Ant Colony based hybrid approach for optimal compromise sum-difference patterns synthesis

Dealing with the synthesis of monopulse array antennas,many stochastic optimization algorithms have been used for the solutionof the so-called optimal compromise problem between sum anddifference patterns when sub-arrayed feed networks are considered.More recently, hybrid approaches, exploiting the convexity of thefunctional with respect to a sub-set of the unknowns (i.e., the sub-arrayexcitation coefficients) have demonstrated their effectiveness. In thisletter, an hybrid approach based on the ant colony optimization (ACO)is proposed. At the first step, the ACO is used to define the sub-arraymembership of the array elements, while, at the second step, thesub-array weights are computed by solving a convex programmingproblem.