本文研究了在输出数据缺失的情况下空气流动速度（简称空速）估计问题。根据声波在气流中传播原理，给出了声矢量传感器线性阵列的输出模型。基于各个传感器输出信号幅值的差异，提出了两种空速估计算法，并给出了随机扰动补偿方法。在此基础上，针对阵列输出数据缺失的情况，提出了输出数据相关矩阵重构方法。此方法能够减少数据缺失对估计算法性能的影响，使得在某些传感器失效的情况下，估计算法仍能正常工作。仿真实验表明：在系统存在随机扰动时，两种算法具有较好的估计性能；在输出数据缺失情况下，经过对输出数据相关矩阵的重新构造，两种算法仍能保持较好的估计性能。%The airspeed estimate problem in case of missing data is researched in this paper .According to the propagation principle of acoustic wave in air current ,the output model of an acoustic vector array is given .Two airspeed estimate algorithms are proposed based on the difference of output signal in amplitude of each sensor ,and a method compensating random perturbation is given .In case of missing array’s output data ,a new method for reconstructing correlation matrix of output data is proposed .Using this method ,the effect of missing data on the performance of airspeed estimate algorithms can be reduced .Thus ,the airspeed esti-mate algorithms are still valid in case that some sensors fail .Simulation results show two airspeed estimate algorithms have better performance in the presence of random perturbation .By reconstructing correlation matrix of output data ,two airspeed estimate algo-rithms can hold better performance in case of missing data .
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