Synthesizing Uniform Amplitude Sparse Dipole Arrays With Shaped Patterns by Joint Optimization of Element Positions, Rotations and Phases

This paper presents a novel method for synthesizing sparse dipole arrays with shaped patterns by joint optimization of element positions, rotations and phases. Such joint optimization exploits maximum available degrees-of-freedom under the assumption of uniform amplitude excitations to improve the shaped power pattern synthesis performance, and it leads to a reduced number of elements and simpler feeding network without using unequal power dividers for the array. The copolarization (COP) and cross-polarization patterns for a rotated dipole array are derived in a 2-D case, and then the vectorial shaped pattern synthesis problem is formulated as finding the optimal solution by maximally approaching the desired COP pattern shape under multiple constraints on the sidelobe level (SLL) and cross-polarization level (XPL). In addition, an asymmetric mapping method is incorporated into the proposed joint optimization, so that the minimum element spacing constraint can be also used for the synthesis of planar sparse dipole arrays. The comprehensive learning particle swarm optimization (CLPSO) algorithm is adopted to optimize the element positions, rotation angles and phases. A set of synthesis experiments including linear and planar rotated dipole arrays with a different pattern shape requirements are conducted to validate the effectiveness and robustness of the proposed approach. Synthesis results show that the proposed approach can save about 17.24% – 55.86% elements as well as many unequal power dividers for test cases.