A New Subarray Partition Method for Generating Arbitrary Shaped Beam Patterns

The design of traditional phased array is complex and the cost of it is high, therefore the traditional phased array technology is gradually unable to meet the increasingly diverse application demands. To address this issue, emerging techniques like subarray partitioning have recently gained prominence, offering new hope and possibilities in the field of phased arrays. This article explores how to optimize phased array systems using subarray partitioning techniques to cater to the expanding application requirements. A method is proposed that defines element excitations and corresponding subarray weighting coefficients through two nested iterative loops. The outer loop employs conventional beamforming methods and intelligent optimization algorithms to determine a user-defined fully populated array’s reference excitation set. Multiple sets of different combinations of element excitations are obtained using the Schelkunoff unit circle and basic algebraic theory. The inner loop focuses on synthesizing optimal subarray layouts and their respective subarray excitation coefficients using the K-means clustering algorithm, aiming to achieve a beam pattern closest to the reference array. Validation against the K-means optimization method in terms of beam pattern approximation, excitation matching cost function, and pattern matching cost function confirms the effectiveness of the proposed approach.