基于稀疏协方差矩阵迭代的单快拍气流速度估计算法

该文研究基于声传感器阵列的单快拍气流速度估计问题。首先，根据声波在亚音速和超音速气流中的传播特性，针对特定的测量装置，建立了声传感器线性阵列的输出模型。在此基础上，提出一种稀疏协方差矩阵迭代的单快拍(Sparse Covariance Matrix Iteration with a Single Snapshot, SCMISS)气流速度估计算法，与其他稀疏估计方法相比，该文提出的SCMISS算法无需正则化参数选择，计算量更低，具有更强的实时性，且只需单快拍采样数据就可对亚音速和超音速气流速度进行统一估计。最后，为了评价所提算法的估计性能，推导了气流速度估计的克拉美-罗界(Cramr-Rao Bound, CRB)表达式。仿真实验验证了该算法的有效性。

Single Snapshot Airspeed Estimation Based on Sparse Covariance Matrix Iteration

The issue of single snapshot airspeed estimation is researched based on acoustic sensor array. According to the propagation property of acoustic waves in subsonic and supersonic air current, the output model of acoustic sensor array is constructed for a given measuring equipment. Then an airspeed estimation algorithm based on Sparse Covariance Matrix Iteration with a Single Snapshot (SCMISS) is presented. SCMISS has several unique features not shared by other sparse estimation methods: it does not require the user to make any difficult selection of regularization parameters, and it has lower computational complexity and better real-time. What is more, the proposed algorithm can be applied to both subsonic and supersonic circumstances with single snapshot measurement. Finally, a compact expression for the Cramr-Rao Bound (CRB) on the estimation error of airspeed is derived to evaluate the performance of the proposed algorithm. Simulations are implemented to show the effectiveness of SCMISS.