Optimization of the difference patterns for monopulse antennas by a hybrid real/integer-coded differential evolution method

Abstract

The optimization of difference patterns of monopulse antennas is considered. The synthesis problem is recast as an optimization problem by defining a suitable cost function. In particular. in this paper, the cost function is based on constraints on the side-lobe levels. A subarray configuration is adopted and the excitations of the difference pattern are approximately determined. The optimization problem is efficiently solved by a differential evolution algorithm, which is able to contemporarily handle real and integer unknowns. Numerical results are reported concerning classical array configurations previously considered in the literature

Excitation matching procedure for sub-arrayed monopulse arrays with maximum directivity

“…They consider optimization techniques [4]- [8] as well as excitation matching methods [3] [9]. Although optimization techniques can be simply adapt to optimize one or more (at the price of higher computational complexity) pattern features, the major part of the contributions have taken into account the minimization of the SLL [4]- [6] [8]. Only in [7], the approach previously presented in [6] was extended to maximize the directivity of the compromise pattern.…”

“…Although optimization techniques can be simply adapt to optimize one or more (at the price of higher computational complexity) pattern features, the major part of the contributions have taken into account the minimization of the SLL [4]- [6] [8]. Only in [7], the approach previously presented in [6] was extended to maximize the directivity of the compromise pattern. Within this framework, the Contiguous Partition Method (CP M) [9] has shown its effectiveness and versatility in determining a "best compromise" difference pattern close as much as possible to the optimum in the Dolph-Chebyshev sense [10] (i.e., narrowest first null beamwidth and largest normalized difference slope on the boresight for a specified sidelobe level) [9] as well as the optimization of some pattern features (e.g., SLL [11]).…”

Directivity Optimization in Planar Sub-Arrayed Monopulse Antenna

“…Since the available space is limited and because of the need of simple feed networks, an ever growing interest has been devoted to subarraying strategies [4][5][6][7][8][9]. In such a case, a set of excitations (either the sum or one difference) is fixed to the optimum, while the others are obtained by clustering the array elements into sub-arrays and weighting each of them.…”

“…To obtain good radar performances, the compromise solution should guarantee narrow beamwidth and low sidelobe levels (SLLs), high directivity, and deep normalized slope at boresight. Unfortunately, such requirements are incommensurable and the synthesis of compromise solutions has usually dealt with only the minimization of the SLLs [4][5][6][7][8][9][10] for a given beamwidth. Other studies concerned with linear arrays have also considered the maximization of the directivity [11].…”

Optimization of difference pattern features in sub-arrayed monopulse antennas through and excitations matching procedure

“…In order to solve such a problem, different approaches have been proposed. Analytically technique [5] (Excitation Matching Method EMM), or optimization approaches [6] [7] or hybrid approaches [8]. Whatever the method, the attention has been mainly focused on the searching of the pattern with the lower SLL.…”