Design of Eight-Phase Sequences using Modified Particle Swarm Optimization for Spread Spectrum and Radar Applications

Abstract

For a multiple access communication system and radar system, it is desirable to have a set of sequences such that each sequence has a peaky autocorrelation and each pair of sequence has a negligible cross-correlation as possible. Peakyness of the auto-correlation of a sequence is measured in terms of its discrimination, which is to be maximized. The negligibility of a cross-correlation is judged based on the energy in the cross-correlation which is to be minimized. Obtaining such sequences is a combinatorial problem for which many global optimization algorithms like genetic algorithm, particle swarm optimization algorithm, simulated annealing algorithm were reported in the literature. In this paper a Modified Particle Swarm Optimization (MPSO) Algorithm is being designed to achieve these sequences. The MPSO Algorithm is a combination of the Hamming Scan Algorithm (HAS) and Particle Swarm Optimization (PSO) and has the fast convergence rate of Hamming Scan and global minima convergence of Particle Swarm Optimization. Eight-phase sequences of lengths varying from 40 to 300 have been synthesized using MPSO and synthesized sequence sets achieved have better values of the above two properties compared with the literature.