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中国物理学会期刊

基于最差性能优化的运动声源稳健聚焦定位识别方法研究

CSTR: 32037.14.aps.60.064301

Robust localization and identification method of moving sound sources based on worst-case performance optimization

CSTR: 32037.14.aps.60.064301
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  • 基于被动合成孔径原理,提出了一种具有高稳健性的运动声源高分辨聚焦定位识别方法.该方法采用综合优化手段,通过矢量最大似然聚焦定位算法生成虚拟阵列坐标及数据矩阵,进而利用基于最差性能优化的稀疏虚拟阵列聚焦算法,获取稳健的高分辨定位识别效果.理论及仿真研究表明,该方法对于非匀速运动以及与基阵存在运动倾角的复杂情况具有较强的适用性,聚焦空间谱表现出更大的动态范围、更为尖锐的聚焦峰尺度以及更强的背景噪声起伏压制能力.湖上试验进一步验证,在高分辨最小方差信号无畸变响应法(MVDR)聚焦算法动态范围仅为3.5 dB的相

     

    Based on the passive synthetic aperture principle, a new robust high-resolution focused array signal processing method of moving sound source localization and identification is proposed in this paper. By means of the integrated optimization, this method generates the coordinates of a virtual array and the data matrix through the vector maximum likelihood focused algorithm, then utilizes the sparse virtual array focused algorithm based on the worst-case performance optimization to obtain the robust high-resolution localization and recognition effects. The theory and the simulation analysis show that this method is applicable to the complex experimental situations such as non-uniform motion and tipsy array, and the focused spatial spectrum indicates the greater dynamic range, the sharper focused peak, and the stronger ability to suppress the fluctuations of the background noise. The higher robustness and better results of this proposed method are verified in the lake experiment. Under the same experimental condition, the dynamic range of high-resolution MVDR focused algorithm is only 3.5dB, however, it can reach 50 dB by the proposed method.

     

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