CORC  > 清华大学
基于遗传算法的二维随机型稀疏阵列的优化研究
霍健 ; 杨平 ; 施克仁 ; 张伟 ; HUO Jian ; YANG Ping ; SHI Keren ; ZHANG Wei
2010-06-08 ; 2010-06-08
关键词TB559
其他题名Optimal design of random sparse 2-D arrays based on genetic algorithm
中文摘要为了解决二维相控阵列及与之匹配的三维超声成像系统过于复杂的问题,提出了一种基于遗传算法的随机型稀疏阵列的优化设计方法。在这种方法中,首先根据横向分辨率的要求确定参考阵列的尺寸及加权分布,然后根据对比分辨率的要求确定稀疏阵列相对于参考阵列的稀疏率,最后利用遗传算法优化确定阵元的分布形式。通过连续波理论和基于空间冲激响应的脉冲场模型对这种稀疏阵列的声学特性进行了分析,分析结果表明,优化设计的随机型稀疏阵列具有良好的特性,它与参考阵列有几乎相等的主瓣宽度,而且不产生栅瓣,虽然其旁瓣高度与参考阵列相比略有提升,但经遗传算法优化后仍能满足高质量成像的要求。; In order to limit complexity of the 2-D phased array and its 3-D ultrasound imaging system, a optimal design method of random sparse 2-D arrays based on genetic algorithm is developed. Firstly, the aperture size and the element weights of the array reference is pre-determined according to spatial resolution. Secondly, the sparse ratio is determined according to contrast resolution and the sparse array is designed by randomly removing a fraction of the original set of elements from the 2-D array reference. Consequently, the distribution of the reserved element is optimized by the use of the genetic algorithm to achieve acceptable acoustic properties. The acoustic characteristic of the sparse arrays is analyzed through continuous wave theory and pulse ultrasound field model based on the spatial impulse response. Results show that sparse arrays based on genetic algorithm have a good overall performance. The main-lobe is practically unaffected by the random removal of elements, and grating lobes are avoided in these arrays, but the average side-lobe level increases a little. However, it can satisfy the needs for the high-quality ultrasound imaging when the sparse array is optimized using the genetic algorithm.
语种中文 ; 中文
内容类型期刊论文
源URL[http://hdl.handle.net/123456789/48287]  
专题清华大学
推荐引用方式
GB/T 7714
霍健,杨平,施克仁,等. 基于遗传算法的二维随机型稀疏阵列的优化研究[J],2010, 2010.
APA 霍健.,杨平.,施克仁.,张伟.,HUO Jian.,...&ZHANG Wei.(2010).基于遗传算法的二维随机型稀疏阵列的优化研究..
MLA 霍健,et al."基于遗传算法的二维随机型稀疏阵列的优化研究".(2010).
个性服务
查看访问统计
相关权益政策
暂无数据
收藏/分享
所有评论 (0)
暂无评论
 

除非特别说明,本系统中所有内容都受版权保护,并保留所有权利。


©版权所有 ©2017 CSpace - Powered by CSpace