基于多尺度小波分解FDR的激光预警系统信息数据校正  

Based on Multi-scale Wavelet Decomposition FDR Information and Data Correction for Laser Warning System

作　　者：鲁旭涛[1] 李静[2] 杨泽辉[3] 

机构地区：[1]中北大学信息与通信工程学院,太原030051 [2]中北大学计算机与控制工程学院,太原030051 [3]山西省财政税务专科学校,太原030024

出　　处：《火力与指挥控制》2014年第3期27-30,共4页Fire Control & Command Control

基　　金：国家自然科学基金(青年科学基金)资助项目(51305409)

摘　　要：为了使激光预警系统可以实时、精确地捕获来袭激光的特征信息,降低虚警与漏警的发生,提高系统的信噪比成为研究的重点。为了准确判断来袭激光的光谱信息,针对不合作激光信号而言,提高信噪比的方法就集中的体现在采用信息技术对各种噪声、干扰的抑制和消除等方法上。设计了基于多尺度小波分解及错误假设检验算法的信噪比优化模型。根据小波降噪原理,对来袭激光信号做多尺度分解,再采用错误假设检验算法完成了小波降噪系数的阈值选取。实验结果显示,采用该种技术降噪后系统信噪比提高到64.22 dB,其相应的波长分辨率为2 nm,相比没有滤波和仅用传统滤波算法的实验数据,有了明显的改观,系统抗干扰能力显著增强。In order to make the laser warning system with real-time,accurately capture the characteristic information of the incoming laser,minimizes false alarm and missed alarm occurred, improving the signal-to-noise ratio of the system become the focus of the study. In order to accurately determine the spectral information of the incoming laser,to uncooperative laser signal,improved the signal-to-noise ratio is reflected in the use of information technology for all kinds of noise,interference suppression and elimination methods. Designed optimization model based on multi-scale wavelet decomposition and signal-to-noise ratio of the error hypothesis testing algorithm. According to the principle of wavelet noise reduction, incoming laser signal with multi-scale decomposition, FDR（False Discovery Rate） algorithm to complete the wavelet noise reduction coefficient threshold. Experimental results show that, used by the technical noise reduction system signal-to-noise ratio improved to 64.22 dB. The corresponding wavelength resolution of 2 nm,filtering and only traditional filtering algorithm compared to experimental data,has been significantly improved,significantly enhanced anti-jamming capability.

关 键 词：激光预警系统 多尺度小波分解 错误假设检验 系统信噪比 

分 类 号：TP911[自动化与计算机技术]