强噪声背景下车辆震动信号检测算法研究

Detection Algorithms for Vehicle Seismic Signals in Strong Noise Environment

针对强噪声背景下车辆震动信号检测问题,结合车辆震动信号特点,提出了2种检测算法:基于功率谱分布的检测算法和基于负熵的检测算法,并将小波去噪用于强噪声背景下地震动信号的提取。该算法与一般检测算法相比具有环境适应性强、检测准确率高和运算量小的特点,这些优点使得该算法更适用于能量受限、工作环境复杂的无线传感网络。仿真结果表明该算法具有很高的检测准确率。

To address the issue of detecting vehicle seismic signals in strong noise environment and combining with the characteristics of vehicle seismic signals, two signal detection algorithms based on power spectrum distribution and negentropy respectively are proposed. And wavelet denoising is used to extract the seismic signals. The algorithms described in this paper show better adaptability to environment, high detection accuracy and less computational complexity compared with common detection algorithms, which make the algorithms more adaptable to energy-limited and environment-complicated wireless sensor networks. Simulation results prove that the algorithms have high detection accuracy.