| 多频带期望值最大声信号时延估计EI北大核心CSCD |
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| 引用本文： | 朱文龙,印明,佟建飞,陈志菲,鲍明,朱小婷,许耀华.多频带期望值最大声信号时延估计EI北大核心CSCD[J].声学学报,2022,47(6):856-866. |
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| 作者姓名： | 朱文龙 印明 佟建飞 陈志菲 鲍明 朱小婷 许耀华 |
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| 作者单位： | 1 安徽大学电子信息工程学院 合肥 230601; |
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| 基金项目： | 国家自然科学基金项目(11774379)资助 |
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| 摘 要： | 通过分析复杂环境中不同频带声信号时延估计的差异,提出多频带期望值最大时延估计方法。为了使各频带之间无重叠,该方法采用独立分带划分声信号不同频带,然后计算各频带广义互相关函数,并对子带广义互相关函数建立最大似然模型,最后利用期望值最大算法将多维优化转为一维优化的迭代式,获得最优子带广义互相关函数,在此基础上估计声信号的时延信息。数据仿真和实际实验结果表明,多频带期望值最大化时延估计相较常规时延估计有效估计值的百分比提升了10%,并将最优频带互相关函数应用到该定位算法中,在网格间距为0.3 m时,得到的峰值区域汇聚更明显,定位效果更好。
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| 关 键 词： | 时延估计 多频带 声信号 广义互相关 信号时延 互相关函数 最大似然 定位效果 |
| 收稿时间： | 2021-11-29 |
Estimation of time delay of multi-band expectation value maximization acoustic signal |
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| Affiliation: | 1 College of Electronic Information Engineering, Anhui University;2 Key Laboratory of Noise and Vibration Research, Chinese Academy of Sciences Beijing 100190;3 Sichuan Jiuzhou Electric Appliance Group Co. LTD JiuzhouZhongke Acoustics Joint Laboratory Chengdu 621000 |
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| Abstract: | By analyzing the difference of time delay estimation of acoustic signals in different frequency bands in complex environment, a multi-band expectation value maximization time delay estimation method is proposed. In order to ensure that there is no overlap between the frequency bands, the signal frequency band is divided independently. We calculate the respective generalized cross-correlation of each sub-band, and then establish the maximum likelihood model for each generalized cross-correlation. The iterative solution of transforming multi-dimensional optimization into one-dimensional optimization using the expectation value maximization algorithm is derived to obtain the optimal sub-band generalized cross-correlation function, and the time delay information of the acoustic signal is estimated on this basis. The data simulation and actual experimental results show that this algorithm increases the percentage of the effective estimation value by 10% compared with the conventional delay estimation. In the application of steering response power, when the grid is 0.3 m. The obtained peak area convergence is more obvious, and the localization effect is better. |
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