文档介绍：IEEE TRANSACTIONS ON ANTENNAS AND PROPAGATION, VOL. 52, NO. 3, MARCH 2004 771
Particle Swarm Optimization Versus ic
Algorithms for Phased Array Synthesis
Daniel W. Boeringer and Douglas H. Werner, Senior Member, IEEE
Abstract—Particle swarm optimization is a recently invented
high-performance optimizer that is very easy to understand and
implement. It is similar in some ways to ic algorithms or evo-
lutionary algorithms, but requires putational bookkeeping
and generally only a few lines of code. In this paper, a particle
swarm optimizer is implemented pared to a ic
algorithm for phased array synthesis of a far-field sidelobe notch,
using amplitude-only, phase-only, plex tapering. The
results show that some optimization scenarios are better suited
to one method versus the other (., particle swarm optimization
performs better in some cases while ic algorithms perform
better in others), which implies that the two methods traverse the
problem hyperspace differently. The particle swarm optimizer
shares the ability of the ic algorithm to handle arbitrary
nonlinear cost functions, but with a much simpler implementation
it clearly demonstrates good possibilities for widespread use in
ic optimization.
Index Terms—Antenna pattern synthesis, antenna radiation pat-
tern synthesis, ic algorithms, optimization methods, phased
arrays.
I. INTRODUCTION
A. Parti