基于HHT的UWB生物雷达回波信号处理技术研究

发布时间：2018-04-30 08:43

本文选题：超宽带生物雷达 + HHT变换　；参考：《第四军医大学》2012年硕士论文

【摘要】：超宽带生物雷达由于其具有良好的距离分辨力、穿透能力和抗干扰性能等优点,广泛应用于灾害救援、反恐斗争等场合。生物雷达在实际应用中,由于雷达发射的电磁波要穿透废墟或障碍物照射到人体目标然后产生反射,反射的雷达回波信号中包含大量的杂波和噪声,携带的人体生命信息非常微弱。因此为了获取有用的生命体信息,必须采取噪声抑制方法以去除噪声,保留有用信息。本课题组前期采用了傅里叶变换方法滤除高频噪声,保留低频有用生命体信息,但是生物雷达探测到的生命特征信号属于非平稳信号,不满足傅里叶变换方法要求的信号平稳性假设,同时傅里叶变换不具有时频分析的局域性,去噪的同时使信号的突变部分变得平滑,可能损失了突变位置携带的重要信息。针对以上情况,本研究引入了以HHT变换为基础的噪声抑制方法,将UWB雷达回波信号经EMD分解为表征不同时间特征尺度的IMF分量,找出IMF分量中噪声占主导模态与信号占主导模态的分界点,提取噪声占主导模态部分中的有用信号成分,将其与信号占主导模态部分的IMF分量相加重构出去噪后的雷达回波信号。本研究主要完成了以下三个方面的工作： 1、对HHT变换进行了研究,分析了其瞬时频率、固有模态函数及Hilbert谱分析等概念的意义,并对其在应用中的优缺点进行了讨论。 2、完成了HHT变换核心步骤EMD分解算法的编写,并对经过预处理后的UWB雷达回波信号进行了EMD分解,对分解得到的IMF分量的能量分布进行了分析,根据其是否出现能量极小值点选择了不同的方法对其进行处理,最终能有效去除高频噪声,保留低频有用信息。 3、将基于HHT变换的去噪结果与原经0.5Hz低通滤波器去噪的结果进行了对比,发现该方法不仅有效地去除了高频噪声,同时保留了信号中的突变部分的细节信息。本研究主要创新点在于： 1、将HHT变换的方法引入到UWB生物雷达回波信号处理中,首次应用于人体呼吸信号的提取。 2、针对雷达回波信号信噪比的高低差异,分别采用了基于IMF分量能量分析的方法与基于噪声与信号自相关函数特性差异的分析方法,都能达到去除高频噪声的目的。为了更完整的保留信号中的细节信息,对噪声占主导模态部分还采用了类似于小波软阈值去噪的方法,提取了该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.

【学位授予单位】：第四军医大学
【学位级别】：硕士
【学位授予年份】：2012
【分类号】：TN957.51;R318.0

【参考文献】