Abstract
When particle swarm optimization (PSO) is used to optimize antenna array pattern, all particles are always initialized randomly, but here a new initialization method are presented to improve PSO optimizer convergence. On the basis of desired pattern the corresponding aperture weights are solved by analytical techniques which can to a great extent ensure that these weights are efficient estimations of the current optimum particle initial values. Then they are assigned to a particle as initial values, but all other particles of the swarm are still initialized randomly. Except this new initialization step nothing is changed in the standard PSO optimizer. The simulation results prove that this new optimizer converges faster and deeper than the standard PSO especially in more complicated optimization problems. So the presented new PSO optimizer is more effective and can achieve better optimized solutions which can meet the specifications well.
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Zhang, S., Chou, Y., Wei, X., Deng, Z. (2019). Modified PSO Optimizer for Arrays Pattern Optimization by Efficient Estimations of the Optimum Particle Initial Values. In: Liang, Q., Mu, J., Jia, M., Wang, W., Feng, X., Zhang, B. (eds) Communications, Signal Processing, and Systems. CSPS 2017. Lecture Notes in Electrical Engineering, vol 463. Springer, Singapore. https://doi.org/10.1007/978-981-10-6571-2_163
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DOI: https://doi.org/10.1007/978-981-10-6571-2_163
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