基于声矢量传感器阵列的空速估计算法

研究了一种新型的空速测量方法。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声矢量传感器阵列的近场输出模型，模型的阵列流形矢量中包含了待估计的空速信息。在此基础上提出了一种基于多重信号分类(multiple signal classification, MUSIC)的空速估计（airspeed estimation,ASE）算法，该算法可用于对空速的高精度估计。为了降低计算复杂度，进一步提出了一种快速的空速估计（fast airspeed estimation, FASE）算法，该算法虽然在ASE的精度上不如MUSIC ASE算法，但无需谱搜索，具有更强的实时性。最后，对算法的估计性能进行分析，推导了ASE的克拉美〖CD*2〗罗界表达式。仿真实验验证了算法的有效性。

Airspeed estimation based on acoustic vector sensor array

A novel airspeed measuring method is proposed. According to the concept of effective sound velocity in the field of〖JP〗 atmospheric acoustics, the near field output model of acoustic vector sensor array is constructed in a stable air flow. Then a multiple signal classification algorithm for airspeed estimation (MUSIC ASE) is presented, which can be used to estimate the airspeed with a high degree of accuracy. To reduce the computational complexity, a fast airspeed estimation (FASE) algorithm is addressed. Though the estimation accuracy is not so high as the MUSIC ASE algorithm, the FASE method enable to avoid spectral peak search, and must be more stronger than the MUSIC ASE algorithm in real time. Finally, the performance of the proposed algorithms is analyzed, and a compact expression for the Cramér Rao bound on the estimation error of the airspeed is derived. Computer simulations are implemented to verify the efficacy of the proposed algorithms.