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Investigation of the CLEAN deconvolution method for use with Late Time Response analysis of multiple objects

机译:CLEAN解卷积方法与多个对象的后期响应分析一起使用的研究

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This paper investigates the application of the CLEAN non-linear deconvolution method to Late Time Response (LTR) analysis for detecting multiple objects in Concealed Threat Detection (CTD). When an Ultra-Wide Band (UWB) frequency radar signal is used to illuminate a conductive target, surface currents are induced upon the object which in turn give rise to LTR signals. These signals are re-radiated from the target and the results from a number of targets are presented. The experiment was performed using double ridged horn antenna in a pseudo-monostatic arrangement. A Vector network analyser (VNA) has been used to provide the UWB Frequency Modulated Continuous Wave (FMCW) radar signal. The distance between the transmitting antenna and the target objects has been kept at 1 metre for all the experiments performed and the power level at the VNA was set to 0dBm. The targets in the experimental setup are suspended in air in a laboratory environment. Matlab has been used in post processing to perform linear and non-linear deconvolution of the signal. The Wiener filter, Fast Fourier Transform (FFT) and Continuous Wavelet Transform (CWT) are used to process the return signals and extract the LTR features from the noise clutter. A Generalized Pencil-of-Function (GPOF) method was then used to extract the complex poles of the signal. Artificial Neural Networks (ANN) and Linear Discriminant Analysis (LDA) have been used to classify the data.
机译:本文研究了CLEAN非线性反卷积方法在隐式威胁检测(CTD)中用于检测多个对象的后期响应(LTR)分析中的应用。当使用超宽带(UWB)频率雷达信号照亮导电目标时,会在物体上感应出表面电流,进而产生LTR信号。这些信号从目标被重新辐射,并呈现了多个目标的结果。实验是使用双脊喇叭天线以拟单静态布置进行的。矢量网络分析仪(VNA)已用于提供UWB调频连续波(FMCW)雷达信号。对于所有执行的实验,发射天线与目标物体之间的距离一直保持在1米之内,并且VNA的功率水平设置为0dBm。实验装置中的目标物在实验室环境中悬浮在空气中。 Matlab已用于后期处理中,以执行信号的线性和非线性解卷积。维纳滤波器,快速傅立叶变换(FFT)和连续小波变换(CWT)用于处理返回信号并从杂波中提取LTR特征。然后使用通用功能铅笔(GPOF)方法提取信号的复数极点。人工神经网络(ANN)和线性判别分析(LDA)已用于对数据进行分类。

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