TENG Yu-peng,SHI Zhao,QUAN Yu,et al.The Effect of Particle Swarm Optimization for Beam-forming[J].Journal of Chengdu University of Information Technology,2016,(01):22-28.
粒子群优化算法对波束形成的效果分析
- Title:
- The Effect of Particle Swarm Optimization for Beam-forming
- 文章编号:
- 2096-1618(2016)01-0022-07
- Keywords:
- meteorological sounding techniques; atmospheric remote sensing; phased array radar; particle swarm optimi- zation; array antenna; radiation pattern
- 分类号:
- TN958. 92
- 文献标志码:
- A
- 摘要:
- 相控阵雷达的优势之一便是按照一定的幅度、相位或者间距对阵元进行加权后在理论上可得到任意形 状的远场方向图。但是,由于所需控制的参数之间存在互相作用,导致其分布特性复杂,致使相控阵雷达波束形成 性能受限。以粒子群优化算法为代表的智能算法解决了在特定场合无法利用数学解析推导加权项分布的难题。 通过仿真,对粒子群算法在波束形成上的效果进行分析,讨论在不同变量空间下的粒子群算法优化对于波束的性 能影响,并对诸多设计细节提出建议。仿真实验结果表明:基于粒子群算法的相位加权不能单独应用于方向图优 化。幅度加权收敛速度快,可以较好地完成优化,适合于自适应性的应用场合。幅、相混合加权对于宽波束赋形性 能较好,但是收敛速度较慢。
- Abstract:
- One of the advantages of phased array radar is that any shape of far field radiation pattern can be obtained the- oretically by weighting the array element according to certain amplitude, phase, or distance. However, due to the inter- actions between the parameters, distribution character is more complex, these limit the performance of phased array ra- dar. Represented by particle swarm optimization algorithm of intelligent algorithm solve the problem that mathematical derivation can't be use to weighted items distribution in particular occasions. The effect on the particle swarm algorithm in beam-forming and different weighted forms of PSO is analyzed by simulation in this article. At the same time, the de- sign suggestions are put forward. The simulation experiment results show that the phase weighted algorithm based on par- ticle swarm optimization can't apply to pattern optimization independently. The amplitude weighted algorithm accelerates the rate of convergence, with better performance in optimization, suitable for self-adaption applications. The mixing weighted algorithm of amplitude and phrase has better performance on shaping the wide beam but with a slow rate of con- vergence. Key words
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备注/Memo
收稿日期:2016-02-06 基金项目:国家自然科学基金资助项目(41505031)