In view of some short comings

such as the premature convergence and bad local optimal searching capability in traditional intelligence methods for pattern synthesis

a novel algorithm is proposed based on quantum particle swarm optimization(QPSO) with probability amplitude coding of quantum bits

which is designed by use of stagnation detection and selective variation in particles and is applied in the pattern synthesis of array anttenas.The simulation results show its high performance in the pattern synthesis of array anttenas with multi-null and low sidelobe restrictions

and in addition

the algorithm proposed is superior to neighborhood particle swarm optimization(NPSO)and immune clonal selection algorithm(ICSA)in optimization accuracy and operation speed

and it has very good generalization capability.