Beam Pattern Optimization Via Unequal Ascending Clusters

Abstract

In this paper, two different architectures based on completely and sectionally clustered arrays are proposed to improve the array patterns. In the wholly clustered arrays, all elements of the ordinary array are divided into multiple unequal ascending clusters. In the sectionally clustered arrays, two types of architectures are proposed by dividing a part of the array into clusters based on the position of specific elements. In the first architecture of sectionally clustered arrays, only those elements that are located on the sides of the array are grouped into unequal ascending clusters, and other elements located in the center are left as individual and unoptimized items (i.e. uniform excitation). In the second architecture, only some of the elements close the center are grouped into unequal ascending clusters, and the side elements were left individually and without optimization. The research proves that the sectionally clustered architecture has many advantages compared to the completely clustered structure, in terms of the complexity of the solution. Simulation results show that PSLL in the side clustered array can be reduced to more than −28 dB for an array of 40 elements. The PSLL was −17 dB in the case of a centrally clustered array, whereas the complexity percentage in the wholly clustered array method was 12 .5 %, while the same parameter for the partially clustered array method equaled 10%.

Keywords

• beam pattern
• clustered array
• genetic algorithm
• sidelobe