Generalized Cyclic Algorithms for Designing Unimodular Sequence Sets with Good (Complementary) Correlation Properties

Abstract

Unimodular sequences with good correlation properties have attracted significant research interest due to their applications in several areas such as radar sensing and communications. In this paper, we address the problem of designing unimodular sequence sets with good correlation and complementary correlation properties using generalized cyclic algorithms for the minimization of weighted integrated sidelobe level (WISL) based metrics. The set of sequences are obtained by considering their complete second-order characterization, which has been proven to be beneficial for identification and sensing systems employing widely linear signal processing. Several numerical examples have been presented to illustrate the performance of the proposed algorithms.