基于关联维数迭代局部投影算法的装甲目标声信号去噪研究

Noise Reduction of Acoustic Signals from Armored Vehicles Based on CDBI-LPM

为了抑制装甲目标声信号中包含的噪声成分,消除其对信号特征提取的不利影响,针对局部投影法中邻域半径选取困难的问题,提出了一种基于关联维数迭代的局部投影算法(CDBILPM)。对典型混沌系统Lorenz序列分别叠加不同噪声水平的高斯白噪声,得到信噪比为20 d B和10 d B的含噪信号,运用本算法对其进行去噪仿真实验。结果证明,本算法不仅简化了计算量,而且可以使Lorenz系统的动力结构得到良好的恢复。应用本算法对坦克和轮式装甲车两类装甲目标的实际声信号进行去噪处理,样本信号的噪声强度显著下降,关联维数减小,信号序列的吸引子结构由杂乱变得有序,说明了本算法可有效消除非线性信号中所含噪声。

A correlation dimension-based iteration-local projective method（ CDBI-LPM） is proposed to reduce the noise in the acoustic signals from the armored vehicles and eliminate the harmful effects on feature extraction. 20 d B and 10 d B（ SNR） noisy signals are obtained by adding the different Gaussian white noises to the Lorenz sequence of a typical chaos system. The noise reduction simulation results show that the proposed method not only reduces the amount of computation,but also efficiently recovers the dynamic structure of Lorenz system. The application of the method in the noise reduction of actual acoustic signals from tanks and wheeled armored vehicles shows that the noise intensities of sample signals are significantly reduced,the correlation dimensions decrease,and the disorder attractor structures of the signal series get order as well. This indicates that the proposed method could efficiently reduce the noise in the nonlinear signals.