基于声传感器线性阵列的气流速度估计算法

Air velocity estimation algorithm based on acoustic sensor linear array

研究了一种基于声传感器线性阵列的新型气流速度测量方法。通过引入大气声学中的有效声速概念,建立了稳定气流作用下各阵元的接收模型,由此建立了声传感器线性阵列的近场输出模型。根据子空间正交原理,提出了一种基于多重信号分类(MUSIC)的气流速度估计(MUSIC—AVE)算法,此算法可实现对气流速度的高精度估计。为了降低计算复杂度,进一步提出了一种快速的气流速度估计(FAVE)算法,此算法虽然在估计精度上不如MUSIC—AVE算法,但无需谱搜索,具有更强的实时性。推导了气流速度估计的克拉美—罗界(CRB)表达式。仿真实验验证了提出算法的有效性。

A novel measuring method for air velocity using acoustic sensor linear array is researched. According to the concept of effective sound velocity in the field of atmospheric acoustics,receiving model for each element is established in stable air flow,so near-field output model for acoustic sensor linear array is constructed. A multiple signal classification algorithm for air velocity estimation（ MUSIC—AVE） is proposed,MUSIC—AVE can be used to estimate air velocity with high precision. To reduce computational complexity,a fast air velocity estimation（ FAVE） algorithm is proposed. Although the estimation precision of FAVE is not so high as the MUSIC-AVE algorithm,it doesn ＇t need spectral search,and has stronger real-time property. Cramér-Rao bound（ CRB）expression for estimation on air velocity is derived. Computer simulation experiment verifies effectiveness of the proposed algorithms.