摘要
针对红外探测系统目标识别时漏报警与误触发的问题,基于小波分析理论,对转动探测系统输出的红外信号进行小波去噪处理。构造适用于本系统红外信号去噪处理的阈值函数,通过计算分析与实验验证,采用4层coif小波基函数分解效果最佳。本文构造的阈值函数较传统软、硬阈值函数信噪比(SNR)提高17.52%~34.5%,均方误差(MSE)减小16.15%~20.77%,在不丢失原始波形信息的前提下,使无车辆目标时输出波形平坦、有目标时输出波形光滑,为后期实现车辆目标的识别提供理论依据。
This study aims to solve the fault alarm problem in recognition of vehicle targets using infrared detection systems based on the theory of wavelet analysis. The wavelets are used to denoise the output infrared signal from rotation detection system. Therefore, it is important to create a new threshold function suitable for denoising infrared signals in this system. The computational analysis and experimental verification reveal that the four-layer “coif” offers the best wavelet decomposition. Here, the SNR increases by 17.52%-34.5% and the MSE decreases by 16.15%-20.77% compared to the traditional soft & hard threshold function. Moreover, the output waveforms with and without the vehicle target are smooth and flat, respectively. It provides a theoretical basis for accomplishing vehicle target recognition later.
作者
朱文斌
雷秉山
雷志勇
ZHU Wenbin;LEI Bingshan;LEI Zhiyong(School of Electronic Information Engineering,Xi'an Technological University,Xi'an 710021,China;School of Mechatronic Engineering,Xi'an Technological University,Xi'an 710021,China)
出处
《红外技术》
CSCD
北大核心
2018年第11期1047-1051,共5页
Infrared Technology
基金
西安工业大学科研创新团队建设计划资助
关键词
小波分析
红外探测
转动探测系统
红外信号去噪处理
wavelet analysis
infrared detection
rotation detection system
infrared signal denoising