Off-grid array geometry optimization with quantized phase excitations for beampattern synthesis

Array geometry optimization has long been a critical research focus in the field of array signal processing, as it exerts a profound impact on both the implementation cost and operational performance of array antenna systems. Furthermore, in the practical engineering implementation of array antennas, phase excitations are usually restricted to discrete values. Aiming at the scenario of quantized phase excitations, this paper proposes a Taylor interpolation-based off-grid array geometry optimization framework to improve the performance of array geometry optimization. On the basis of this optimization framework, in addition to synthesizing sparse arrays, this paper also utilizes the off-grid optimization characteristic of element positions to minimize the mainlobe width of the radiation pattern under discrete phase excitations for the first time, achieving equally favorable performance as similar algorithms under continuous phase excitations. Relying on the mathematical properties of quantized phases themselves, it breaks through the minimum requirement of existing algorithms on phase quantization bits. Simulation experiments in the paper verify the advantages of the proposed method.