基于小波变换的红外探测系统信号去噪

朱文斌; 雷秉山; 雷志勇

红外技术, 2018, 40 (11): 1047, 网络出版: 2018-12-18

基于小波变换的红外探测系统信号去噪

Signal Denoising of Infrared Detection System Based on Wavelet Transform

论文大纲

朱文斌 ^1,*雷秉山 ²雷志勇 ¹

作者单位

¹ 西安工业大学电子信息工程学院，陕西西安 710021

² 西安工业大学机电工程学院，陕西西安 710021

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

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。

Abstract

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.

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朱文斌, 雷秉山, 雷志勇. 基于小波变换的红外探测系统信号去噪[J]. 红外技术, 2018, 40(11): 1047. ZHU Wenbin, LEI Bingshan, LEI Zhiyong. Signal Denoising of Infrared Detection System Based on Wavelet Transform[J]. Infrared Technology, 2018, 40(11): 1047.

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