採用瀰因演算法對非對稱之差異場型最佳化

Optimization of Asymmetrical Difference Pattern with Memetic Algorithm

楊松翰(Song-Han Yang)

指導教授 ： 江簡富

國立臺灣大學/電機資訊學院/電信工程學研究所/碩士(2013年)

https://doi.org/10.6342/NTU.2013.03129

摘要

本論文採用瀰因粒子群演算法進行非對稱之差異場型最佳化，可用於跟踪目標雷達。當線性陣列的場型左右峰值要求不對稱時，場型旁瓣亦成功降低，同時保持預期的峰對峰夾角與旁瓣差異。本論文考慮兩種初始條件: 均勻激發線性陣列和貝里斯激發線性陣列，亦比較粒子群演算法、基因演算法和傳統瀰因演算法的性能。

關鍵字

瀰因演算法 ； 差異場型 ； 最佳化

並列摘要

A memetic particle swarm optimization algorithm (MPSO) is applied to fine-tune the asymmetrical difference pattern of a linear array,
which is useful for tracking targets, for example, in radar applications.
The side-lobe level of the asymmetrical difference pattern with various peak differences has been successfully reduced,
while maintaining the intended squint angle and the side-lobe difference.
Conventional PSO, genetic algorithm (GA) and memetic GA (MGA) have also been applied to uniformly-excited and Bayliss linear arrays to compare their performance of optimization.

並列關鍵字

Memetic Algorithm ； Difference Pattern ； Optimization

參考文獻

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