Reconfigurable Array Beampattern Synthesis via Conceptual Sensor Network Modeling and Computation
Xuan Zhang, Junli Liang, Xuhui Fan, Guoyang Yu, Hing Cheung So
Abstract
Reconfigurable array radiates multiple patterns with only a single array via designing multiple excitation vectors with common magnitudes for the same element-index excitation elements, so as to guarantee phase-only control. To tackle this problem, this article proposes a new reconfigurable array beampattern synthesis method. First, we borrow the concept of sensor network consensus computation and model the synthesis problem as a sensor network computation problem via imitating a virtual (conceptual) multinode sensor network, where each “node” corresponds to an individual beampattern synthesis task. More specifically, these “nodes” with the same number as those of radiated patterns share a set of common excitation magnitudes, which results in a special magnitude-consensus computation problem in the imitated sensor network. Then, via locally computing the excitation in each “node” and exchanging current computation results with neighboring “nodes,” all “nodes” obtain the magnitude-consensus excitations after the “network” is stable. Numerical examples are provided to demonstrate the validity and faster convergence speed of the proposed method.