###
工程科学与技术:2021,53(4):200-208
←前一篇   |   后一篇→
本文二维码信息
码上扫一扫!
空域抽样与相干因子融合的超声阵列自适应波束形成算法
(江苏大学 机械工程学院,江苏 镇江 212013)
Adaptive Beamforming Algorithm for Ultrasonic Array with the Combination of Spatial Sampling and Coherence Factor
(School of Mechanical Eng., Jiangsu Univ., Zhenjiang 212013, China)
摘要
图/表
参考文献
相似文献
本文已被:浏览 1002次   下载 313
投稿时间:2021-04-02    修订日期:2021-06-15
中文摘要: 针对超声成像中自适应波束形成算法计算效率低的问题,提出了一种基于空域抽样与相干因子融合的自适应波束形成算法。该算法通过分析阵列数据波束图,推导出不同阵元数目下的最大抽取因子,将阵列中所有阵元接收的数据按最大抽取因子进行空域等间隔抽样,得到阵元稀疏后的回波数据,减少了采集数据量。将空域抽样数据输入波束形成器,计算其协方差矩阵,再将协方差矩阵构造为Toeplitz矩阵,结合最小方差原理从构造的Toeplitz矩阵计算出抽样数据的自适应加权值,并引入相干因子对自适应加权值进行修正,以突出抽样数据中的有效信息,抑制干扰成份。在使用不对等数据信息和使用空域抽样数据成像的情况下,采用该算法、最小方差算法和融合相干因子的最小方差算法分别对裂纹和横通孔缺陷仿真成像。结果表明:在数据信息不对等时,在成像质量上,该算法介于另外两种算法之间;在成像时间上,与另外两种算法相比,该算法的成像时间平均减少85%以上。在相同的空域抽样数据下,在成像质量上,该算法成像效果优于其他算法;在成像时间上,与另外两种算法相比,该算法的成像时间平均减少65%以上。
Abstract:In order to solve the problem of low computational efficiency of adaptive beamforming algorithms in ultrasonic imaging, an adaptive beamforming algorithm for ultrasonic array with the combination of spatial sampling and coherence factor was proposed. The maximum decimation factor with different numbers of array elements was deduced according to the beam pattern. The sparse echo data was obtained by spatially sampling the whole array element data using the maximum decimation factor. Therefore, the amount of data used for beamforming was greatly reduced. Taking the spatial sampling data as the input of a beamformer and constructing the covariance matrix as Toeplitz matrix, the adaptive weights of the sampling data were obtained according to the principle of minimum variance. Then, the adaptive weights were modified by introducing the coherence factor to highlight the effective information of the sampling data. Under the case of unequal data and spatial sampling data, the proposed algorithm, minimum variance algorithm and minimum variance algorithm combined with coherence factor were used to simulate the imaging of cracks and cross-drilled holes respectively. The results show that: for unequal data, the imaging quality of the proposed algorithm is between the other two algorithms; in terms of imaging time, compared with the other two algorithms, the average imaging time of the proposed algorithm is reduced by more than 85%. For the same spatial sampling data, the imaging quality of the proposed method is better than the other algorithms; in terms of imaging time, compared with the other two algorithms, the average imaging time of the proposed algorithm is reduced by more than 65%.
文章编号:202100276     中图分类号:TH878    文献标志码:
基金项目:国家自然科学基金项目(51375217)
作者简介:第一作者:宋寿鹏(1967-),男,教授,博士.研究方向:智能检测与信息处理.E-mail:songshoupeng@126.com
引用文本:
宋寿鹏,李棋.空域抽样与相干因子融合的超声阵列自适应波束形成算法[J].工程科学与技术,2021,53(4):200-208.
SONG Shoupeng,LI Qi.Adaptive Beamforming Algorithm for Ultrasonic Array with the Combination of Spatial Sampling and Coherence Factor[J].Advanced Engineering Sciences,2021,53(4):200-208.