An Efficient Heuristics Search for Binary Sequences with Good Aperiodic Autocorrelations

摘要

This paper presents a memtic algorithm (MA) search for binary sequences with good aperiodic autocorrelation properties. The MA consists of an evolutionary programming framework and a local improvement procedure. The evolutionary programming searches the space of feasible, locally optimal solutions only. An efficient k-opt local search algorithm produces local optima with great efficiency. In most cases, the proposed MA can find out binary sequences which have higher merit factor and less peak sidelobe level than others known results reported by now.