Adaptive antenna subarraying using a weighted Butler matrix

An effective scheme for subarraying an antenna array is presented. The subarray technique uses a partitioned weighted Butler matrix transform where the partition is an adapting function of the geometry of the noise environment. After subarraying, the subarrayed outputs are adaptively weighted in such a way so as to maximize the output signal-to-noise ratio. It is shown that this technique effectively cancels sidelobe jamming without significantly degrading the signal-to-noise ratio that is possible if the entire array is used for adaptation. In addition it is shown that the effective reduction in dimensionality decreases the convergence time of the adapting weights and that the convergence time is independent of the array size.