Dynamic Programming Applied to Large Circular Arrays Thinning

In conventional arrays, improving angular resolution requires larger aperture which demands more number of elements. On the other hand, array thinning is an efficient method of achieving narrow beamwidth (high angular resolution) with fewer number of elements. Reducing the number of elements results in reducing weight, cost, hardware complexity, and energy consumption. In this paper, a novel dynamic programming algorithm of array thinning with the objective of reducing sidelobe levels (SLLs), desired for large circular arrays, is proposed. The circular array is partitioned into annular rings, and the objective of the optimization problem is to determine the number of active elements in each ring. Then, active elements of the rings are selected. Although optimal array thinning is an NP-hard problem, converting the problem of selecting active elements into the number of active elements in each ring causes a huge reduction in computational complexity of the proposed algorithm that makes it affordable for large arrays. Moreover, beampatterns with very low SLLs are synthesized.