飞机起落架噪声源定位的压缩感知算法

目前针对飞机起落架噪声源定位的研究方法主要是将麦克风阵列与波束成形算法相结合。常规波束成形（CBF）算法在计算时存在主瓣宽度过宽、结果易受旁瓣影响的问题。高级波束成形算法在计算时效率较差，有时会有违背物理现象的假声源出现。提出了一种将正交匹配追踪（OMP）算法与奇异值分解（SVD）相结合的起落架噪声源定位的OMP-SVD压缩感知算法。在消声实验室内进行飞机起落架噪声源定位试验，将OMP-SVD算法、CBF算法和OMP算法在不同频率下获得的结果进行对比。试验结果表明：①与OMP算法相比，OMP-SVD算法在不同频率下均能准确定位出起落架主声源；②与CBF算法相比，OMP-SVD算法显著提高了分辨率。

Compressive sensing algorithm for sound source location of aircraft landing gear

At present, source location of aircraft landing gear is investigated mainly by combining microphone arrays with beamforming algorithms. The Conventional BeamForming (CBF) method has the drawbacks that the main lobe is too wide and the computation result is susceptible to sidelobes. For the advanced beamforming algorithm, the computing time is too long, and false sound sources sometimes occur. This paper presents a new method, which combines the Orthogonal Matching Pursuit (OMP) algorithm with Singular Value Decomposition (SVD), to locate the noise source of the landing gear. Experiments are conducted in the anechoic chamber, the results obtained by three different methods at different frequencies are compared. The experimental results show that compared with the OMP algorithm, the OMP-SVD algorithm can locate the main sources of the landing gear at different frequencies accurately; compared with the CBF algorithm, the OMP-SVD algorithm can improve the resolution significantly.