摘要
针对MEMS水听器采集的数据"淹没"在强噪声场中的问题,提出采用LMS自适应噪声对消与Fourier变换滤波相结合的组合算法实现MEMS水听器的信噪分离。在信号频率已知的情况下,设计了一种自适应噪声对消和Fourier变换滤波组合算法的滤波器,对提取后的信号与理想信号做性能对比。仿真实验表明:该组合算法在-15 dB的强噪声场中仍有较高的分辨精度和提取效果,对搜寻类似于"黑匣子"等情况比较适宜,并将设计的滤波器用于中北汾机测试实验的信噪分离中,结果验证了该算法具有良好的高效性和实用性。
In the light of the problem of MEMS hydrophone data“submerged” in strong noise field,the combination filter of LMS adaptive noise cancellation and Fourier transform filtering is proposed. The filter algorithm is applied to MEMS hydrophone signal and noise separation. When the frequency of signal is given,the combination filter algo-rithm is used for signal extraction and the ideal signal performance comparison. Simulation results show that the effect of extraction resolution in strong noise field of-15 dB is higher in the algorithm. The algorithm can be used to search similar to the “black box” case. The filter is used to separate signal and noise in the Fen machine test of North University of China. The results show that the algorithm is efficient and Practicability.
出处
《传感技术学报》
CAS
CSCD
北大核心
2014年第11期1477-1481,共5页
Chinese Journal of Sensors and Actuators
基金
国家自然科学基金项目(61275120)
