基于短时傅里叶时频分析的声信号盲分选仿真系统研究
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摘要
为优化声信号盲分选仿真系统的实时性以及分选精度,研究了一种基于短时傅里叶时频分析(Short Time Fourier Time Frequency Analyze, STF-TF)的声信号盲分选算法,用于改善系统分选精度。该方法在信号的时频平面投影相交的情况下,能够实现声信号分选算法功能。仿真实验表明:在欠定条件下,当源信号数目与接收天线数目相差为1时分选效果最佳。利用SystemVue仿真平台建立了多声传感器条件下信号盲分选系统,并结合透明计算原理提出了适用于该系统的高实时性结构。
In order to improve the ability of real-time and separation accuracy, a blind separation algorithm based on time-frequency(TF) analysis of short time Fourier transformation is proposed, and the problems of underdetermined sound signal sorting can be solved effectively. The proposed method avoids some of the drawbacks, relaxes the assumption by allowing the sources to be TF-non-disjoint to a certain extent, and the algorithm can be achieved in the condition of TF-non-disjoint. This method was successfully applied to sound signal sorting system; the time domain waves of signals can be got; and the whole signal sorting process can be accomplished. In the simulation experiments, the performance and applications in different SNR conditions of proposed method were discussed. The simulation results verify the feasibility and superiority.
In order to improve the ability of real-time and separation accuracy, a blind separation algorithm based on time-frequency(TF) analysis of short time Fourier transformation is proposed, and the problems of underdetermined sound signal sorting can be solved effectively. The proposed method avoids some of the drawbacks, relaxes the assumption by allowing the sources to be TF-non-disjoint to a certain extent, and the algorithm can be achieved in the condition of TF-non-disjoint. This method was successfully applied to sound signal sorting system; the time domain waves of signals can be got; and the whole signal sorting process can be accomplished. In the simulation experiments, the performance and applications in different SNR conditions of proposed method were discussed. The simulation results verify the feasibility and superiority.
引文
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[4]李新波,李晓清,刘国军,等.用于声矢量阵列波达方向估计的四元数最小范数法[J].光学精密工程,2014,22(7):1969-1975.LI Xinbo,LI Xiaoqing,LIU Guojun,et al.Quaternion Min-norm Algorithm for DOA Estimation with Acoustic Vector Sensor Array[J].Optics and Precision Engineering,2014,22(7):1969-1975.
[5]王志峰,冯杰,高鹏,等.基于无限声阵列的目标定位系统设计[J].电声技术,2015,39(3):44-47.WANG Zhifeng,FENG Jie,GAO Peng,et al.Design of Acoustic Source Localization System Using Wireless Acoustic Array[J].Audio Engineering,2015,39(3):44-47.
[6]虞飞,陶建武,钱立林,等.基于声矢量传感器阵列的空速估计算法[J].系统工程与电子技术,2015,37(5):1060-1065.YU Fei,TAO Jianwu,QIAN Lilin,et al.Airspeed Estimation Based on Acoustic Vetor Sensor Array[J].Systems Engineering and Electronics,2015,37(5):1060-1065.
[7]Zhang Xinyu,Li Yang,Yang Xiaopeng,et al.A Novel Monopulse Technique for Adaptive Phased Array Radar[J].Sensor(S1424-8220),2017,17(12):116.
[8]LI Chengjie,ZHU Lidong,XIE Anhong,et al.A Novel Blind Source Separation Algorithm and Performance Analysis of Weak Signal against Strong Interference in Passive Radar Systems[J].International Journal of Antennas and Propagation(S1687-5869),2016,2016:1-10.
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[11]Iglesias V,Grajal J,Royer P,et al.Real-time Low-complexity Automatic Modulation Classifier for Pulsed Radar Signals[J].IEEE Trans.Aerospace and Electronic Systems(S1687-5869),2015,51(1):108-126.