改进MUSIC算法的超声波测风方法研究
Research on ultrasonic wind measurement method with improved MUSIC algorithm
唐心亮 1宋欣朔 1倪永婧1
作者信息
- 1. 河北科技大学 信息科学与工程学院,石家庄 050018
- 折叠
摘要
针对传统超声波测风装置测风精度不高、抗噪声能力弱,提出了一种改进多重信号分类(multiple signal clas-sification,MUSIC)算法的超声波测风方法.采用一种弧形6阵元超声波传感器阵列的测风结构,推导其阵列流型;在此基础上,添加小波阈值降噪算法提高信号信噪比,降低噪声信号协方差矩阵的秩;再使用PHAT加权广义互相关时延估计算法以提高时延估计的准确性,同时根据时延关系对传统MUSIC算法矢量矩阵进行改进;最后通过MU-SIC算法实现对风速风向的测量.理论分析与仿真结果表明:改进后的MUSIC算法具有较好的抗噪性能和较高的风参数测量精度,测量风速绝对误差达到0.15 m/s,风向绝对误差达到2°,可以应用于对风参数要求较高的场景.
Abstract
Traditional ultrasonic wind measurement devices suffer low wind measurement accuracy and weak noise resistance.To address these issues, this paper proposes an improved MUSIC (multiple signal classification) algorithm for ultrasonic wind measurement.With the improvement, a wind measurement structure of an arc-shaped 6-element ultrasonic array is adopted, and its array popularity is derived.Based on this, a wavelet threshold denoising algorithm is employed to extract high signal-to-noise ratio ultrasonic emission signals to reduce the rank of the covariance matrix.The PHAT weighted generalized cross correlation time delay estimation algorithm is employed to improve the accuracy of time delay estimation.Finally, the MUSIC algorithm is adopted to measure wind speed and direction.Our theoretical analysis and simulation results show the improved MUSIC algorithm has excellent noise resistance performance and high wind parameter measurement accuracy.The measurement wind speed error is below 0.15 m/s, and the wind direction error is below 1°.Thus, it has huge potentials in scenarios with high requirements for wind parameters.
关键词
阵列信号处理/MUSIC算法/小波阈值降噪/广义互相关/风速风向测量Key words
array signal processing/MUSIC algorithm/wavelet threshold denoising/generalized cross correlation/measurement of wind speed and direction引用本文复制引用
基金项目
河北省高等学校科学技术重点研究项目(ZD2020318)
河北省教育厅青年基金(QN2021066)
河北省教育厅青年基金(QN2023185)
出版年
2024
国家科技期刊平台
NSTL
万方数据