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超宽带雷达回波信号微动特征识别研究

Research for UWB-Radar’echo Signal and Recognition Methods about Life’s Microwaving Characteristic

【作者】 何永波

【导师】 王绪本;

【作者基本信息】 成都理工大学 , 固体地球物理学, 2009, 硕士

【摘要】 中国是世界上大陆地震最活跃。地震灾害最严重的国家之一。如何最大限度地减轻地震及各类灾害损失,抢救被压。埋人员,有效地减少人员伤亡,是减轻灾害损失的首要任务,也是最能体现出减灾实效和社会显示度的关键环节之一。国内外多次大震后抢救生命的事实证明:对压埋人员抢救愈及时。快速,救生。救活的可能性愈大。因此,为确保在紧急救援中用最短的时间找到被困人员,开展先进的生命救助探测与定位方法研究具有十分重要的意义。从原理上讲,电磁雷达探测方法应该是弥补人工搜索。光学设备观察。红外/热成像。声波。振动探测设备。搜索犬等的有效方法。超宽带雷达探生技术(UWB-Radar for life s detection)是近几十年发展起来的一种探测特定目标的有效探测手段。超宽带雷达生命探测技术就是利用生命探测雷达发射电磁波穿过墙壁等遮挡介质,探测墙壁外面或其它非金属覆盖物下面人的生命信息利用雷达进行生命探测。实际上,生命探测雷达就是通过检测人体生命活动所引起的各种微动,从这些微动中得到人的移动。体动。呼吸。心跳等生命信号,从而辩识障碍物后有无生命体。近年来随着超宽带雷达技术的发展,超宽带雷达探测仪与其他探生仪器相比,有着许多方法无法比拟的优势,比如分辨率高。探测条件简单。操作便捷。经济快速等优点,得到了广泛的研究和应用。因此,开展超宽带雷达探测技术的研究对灾害搜救。反恐战争。伤员探测。经济发展等都有十分重要的意义。本文完成的主要工作可归纳为如下几个方面:第一部分:主要介绍了基于电磁波探测原理的雷达探生仪及其他类型的探生仪,阐述了各自的工作原理,比较了各自的优缺点并突出了超宽带雷达探测的优点。第二部分:主要设计了超宽带雷达人体探测物理实验方案,并对实验雷达回波信号数据进行必要的预处理及处理。同时,利用能量积分算法原理,编制滑动时窗函数,提取出含有人的生命微动特征信号,并利用小波变换和时频分析方法,对其信号进行去噪和频谱分析,提取出代表人体生命特征的频谱。同时,利用最佳时窗的起始值进行有效的人体定位。第三部分:主要利用MUSIC算法,借助呼吸心跳谐波公式,建立呼吸信号模型,并对含有多目标信息的雷达回波信号进行识别提取,达到在复杂环境下多个目标体信号识别的仿真目的。

【Abstract】 In China, the earthquake is very active, the earthquake disaster is serious. How to greatly decrease these disaster lose, rescue the pressed and the buries, reduce the personnel casualty effectively, is the most important task, also is the key link of which can mostly manifest the disaster reduction actual effect and the society reveals the indication. The fact about rescue the lives in big quakes of the domestic and the foreign countries proved that, more promptly to rescue the buries, more lives may be saved. Therefore, for find the stranded people within the shortest time in the urgent rescue, it has extremely vital significance to carry out the advanced life rescue and location research.By theory says, the electromagnetic detection method should be a complement of the manual search, the optical device observation, the infrared/thermal imagery, the sound wave, the vibration sensor, the search dog and so on effective method, The ultra-wide band radar(UWB-Radar)sounding technology is an effective survey method for probe some specific goal which develops just in the nearly several dozens years. In recent years, along with the ultra-wide band technology development, the ultra-wide band radar obtained the extensive research and the application. UWB-radar technology of detect life is to detect the launch of life through the walls by using radar, such as electromagnetic shielding medium, detection of the outside walls or other non-metallic cover of lives following the radar information of detecting life.In fact, life’s radar detectiong is through the detection of human life caused by a variety of fretting, such as mobile, physical activities, respiration and heart rate signals, and so on,then,to identified any obstacles life. Therefore, develops the research of the ultra-wide band radar has extremely vital significance both for the disaster search and rescue and the economical development. This article’s prime task may induce into the following several aspects:The first part: Mainly introduced the exploration of health- meters which based on the electromagnetic wave principle and other microwave human being-detection systems , elaborated their work principle, compared with their good and bad point’s.The second part: Mainly has designed the testing plan about human body probe with the ultra-wide band radar, and has carried on some pretreatment and processing to the empirical datum. It has used the energy integral principle and the design of glide window box number to withdraw the human’s life characteristic signal, and to take denoising and spectrum analysis from signal by using wavelet transform and time-frequency analysis method, in order to extract the representative features of the spectrum of human life. And it has carried on the effective localization.The third part: Mainly has established the breath signal model with the MUSIC algorithm and the aid of the breath palpitation overtone formula, also it has carried on the recognition of the multi-objective signal, achieved the multi-objective recognition’s simulation goal.

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