Zhang Xiaoyong, Zhang Guojun, Shang Zhenzhen, Zhu Shan, Chen Peng, Wang Renxin, Zhang Wendong
State Key Laboratory of Dynamic Testing Technology, North University of China, Taiyuan 030051, China.
Department of Intelligence and Automation, Taiyuan University, Taiyuan 030032, China.
Micromachines (Basel). 2021 Feb 8;12(2):168. doi: 10.3390/mi12020168.
The principle of acoustic energy flux detection method using a single micro electromechanical system (MEMS) vector hydrophone is analyzed in this paper. The probability distribution of acoustic energy flux and the weighted histogram algorithm are discussed. Then, an improved algorithm is proposed. Based on the algorithm, the distribution range of the energy is obtained by a sliding window, the energy center of gravity in the range is considered as the result of direction of arrival (DOA) estimation, and it is proved to be the maximum likelihood estimation of the target direction. The simulation results show that, with the signal to noise ratio (SNR) from -10 dB to 10 dB, the root mean square error (RMSE) of the improved algorithm is reduced by 47.8% on average, and is more accurate in the presence of interference. The experimental results of lake test are consistent with the theory analysis and simulation results.
本文分析了基于单微机电系统（MEMS）矢量水听器的声能流检测方法原理。讨论了声能流的概率分布和加权直方图算法。然后，提出了一种改进算法。基于该算法，通过滑动窗口获取能量分布范围，将该范围内的能量重心作为波达方向（DOA）估计结果，并证明其为目标方向的最大似然估计。仿真结果表明，在信噪比（SNR）从-10 dB到10 dB的情况下，改进算法的均方根误差（RMSE）平均降低了47.8%，在存在干扰时更准确。湖泊试验的实验结果与理论分析和仿真结果一致。
