本文選題：超寬帶生物雷達 + HHT變換　； 參考：《第四軍醫(yī)大學》2012年碩士論文

【摘要】：超寬帶生物雷達由于其具有良好的距離分辨力、穿透能力和抗干擾性能等優(yōu)點,廣泛應(yīng)用于災(zāi)害救援、反恐斗爭等場合。生物雷達在實際應(yīng)用中,由于雷達發(fā)射的電磁波要穿透廢墟或障礙物照射到人體目標然后產(chǎn)生反射,反射的雷達回波信號中包含大量的雜波和噪聲,攜帶的人體生命信息非常微弱。因此為了獲取有用的生命體信息,必須采取噪聲抑制方法以去除噪聲,保留有用信息。 本課題組前期采用了傅里葉變換方法濾除高頻噪聲,保留低頻有用生命體信息,但是生物雷達探測到的生命特征信號屬于非平穩(wěn)信號,不滿足傅里葉變換方法要求的信號平穩(wěn)性假設(shè),同時傅里葉變換不具有時頻分析的局域性,去噪的同時使信號的突變部分變得平滑,可能損失了突變位置攜帶的重要信息。針對以上情況,本研究引入了以HHT變換為基礎(chǔ)的噪聲抑制方法,將UWB雷達回波信號經(jīng)EMD分解為表征不同時間特征尺度的IMF分量,找出IMF分量中噪聲占主導(dǎo)模態(tài)與信號占主導(dǎo)模態(tài)的分界點,提取噪聲占主導(dǎo)模態(tài)部分中的有用信號成分,將其與信號占主導(dǎo)模態(tài)部分的IMF分量相加重構(gòu)出去噪后的雷達回波信號。 本研究主要完成了以下三個方面的工作： 1、對HHT變換進行了研究,分析了其瞬時頻率、固有模態(tài)函數(shù)及Hilbert譜分析等概念的意義,并對其在應(yīng)用中的優(yōu)缺點進行了討論。 2、完成了HHT變換核心步驟EMD分解算法的編寫,并對經(jīng)過預(yù)處理后的UWB雷達回波信號進行了EMD分解,對分解得到的IMF分量的能量分布進行了分析,根據(jù)其是否出現(xiàn)能量極小值點選擇了不同的方法對其進行處理,最終能有效去除高頻噪聲,保留低頻有用信息。 3、將基于HHT變換的去噪結(jié)果與原經(jīng)0.5Hz低通濾波器去噪的結(jié)果進行了對比,發(fā)現(xiàn)該方法不僅有效地去除了高頻噪聲,同時保留了信號中的突變部分的細節(jié)信息。 本研究主要創(chuàng)新點在于： 1、將HHT變換的方法引入到UWB生物雷達回波信號處理中,首次應(yīng)用于人體呼吸信號的提取。 2、針對雷達回波信號信噪比的高低差異,分別采用了基于IMF分量能量分析的方法與基于噪聲與信號自相關(guān)函數(shù)特性差異的分析方法,都能達到去除高頻噪聲的目的。為了更完整的保留信號中的細節(jié)信息,對噪聲占主導(dǎo)模態(tài)部分還采用了類似于小波軟閾值去噪的方法,提取了該部分中含有的有用信息。
[Abstract]:Because of its good distance resolution, penetration ability and anti-jamming performance, ultra wideband biological radar is widely used in disaster relief, anti terrorism and other occasions. In practical application, biological radar is used in the actual application, because the electromagnetic wave emitted by radar must penetrate the ruins or obstacles to the human target and produce reflection, reflected radar back. A lot of clutter and noise are included in the wave signal, and the human life information is very weak. Therefore, in order to obtain useful information of life body, noise suppression method must be adopted to remove noise and retain useful information.
The Fu Liye transform method is used to filter the high frequency noise and retain the useful life body information of low frequency, but the life characteristic signal detected by the biological radar belongs to the nonstationary signal, and it does not satisfy the assumption of the signal smoothness required by the Fu Liye transform method. At the same time, the Fu Liye transform does not have the locality of the time frequency analysis, and the noise de-noising is the same. When the abrupt part of the signal is smooth, it may lose the important information carried by the mutation position. In this study, the noise suppression method based on the HHT transform is introduced. The UWB radar echo signal is decomposed into the IMF component of the characteristic scale of different time by EMD, and the noise in the IMF component is found to be the dominant mode and the signal. In the demarcation point of the dominant mode, the useful signal components of the dominant modal part are extracted from the noise, which is combined with the IMF component of the dominant modal part of the signal to restructure the radar echo signal after the noise.
This research mainly completed the following three aspects:
1, the HHT transformation is studied, and the significance of its instantaneous frequency, inherent modal function and Hilbert spectrum analysis are analyzed, and the advantages and disadvantages of it in the application are discussed.
2, the HHT transform core step EMD decomposition algorithm is completed, and the pre processed UWB radar echo signal is decomposed by EMD, and the energy distribution of the decomposed IMF component is analyzed. According to whether it appears the minimum point of energy, the different methods are used to deal with it, and the high frequency noise can be effectively removed. Retain low frequency useful information.
3, the results of denoising based on HHT transform are compared with that of the original 0.5Hz low pass filter. It is found that the method not only effectively removes the high frequency noise, but also preserves the details of the abrupt part of the signal.
The main innovation of this study is:
1, the HHT transform method is introduced into the UWB biechoic echo signal processing, and is applied to the extraction of human respiration signal for the first time.
2, according to the difference of the signal to noise ratio of the radar echo signal, the method based on the IMF component energy analysis and the analysis method based on the characteristic difference of the autocorrelation function based on noise and signal can be used to remove the high frequency noise. In order to retain the detailed information in the signal, the noise in the dominant modal part is also adopted. A method similar to wavelet soft threshold denoising is used to extract useful information contained in this part.

【學位授予單位】：第四軍醫(yī)大學
【學位級別】：碩士
【學位授予年份】：2012
【分類號】：TN957.51;R318.0

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