Penetrating Radar Autofocusing Imaging Technology

In the process of urbanization,the buildings on the ground are densely distributed,and the walls are staggered to form a large number of enclosed and obscured spaces.The underground space is complex and wide,and there are a large number of unknown spaces to be explored and investigated.Both behind the wall and underground belong to non-line-of sight areas.As a non-destructive active detection means,penetrating radar can detect and image the hidden areas through electromagnetic waves penetrating layered media.The ultra-wideband two-dimensional MIMO radar array has flexible control,higher imaging resolution and stronger penetration performance.It can obtain multi-target information in three-dimensional space,and has been widely used in penetration imaging in recent years.The layered characteristics of the penetrating scene make the electromagnetic wave have complex reflection and refraction effects in the propagation,resulting in target offset and image blur in the imaging results.Therefore,it is necessary to refocus the imaging results according to the medium parameters.However,the parameters of building wall and soil are usually unknown,which brings great challenges to the focusing processing of penetration imaging.Therefore,an autofocusing imaging method is proposed to independently correct the target position and improve the image focusing quality when the medium parameters are unknown.This paper focuses on the autofocusing imaging method of Ultra Wide Band(UWB)MIMO radar.The main work is summarized as follows:1.Aiming at the problems of low efficiency and poor real-time performance of traditional autofocusing methods,an image filter autofocusing imaging algorithm for MIMO radar is proposed.Firstly,the refraction model of MIMO Radar in twodimensional plane is established and the refraction compensation factor is derived.This step avoids the calculation of refraction points and improves the calculation efficiency.Then,by analyzing the spatial spectral relationship of MIMO radar,the spatial spectral form of refraction compensation is derived,and finally the image filter in spatial spectral domain is obtained.This method only needs to perform the original imaging once,and the subsequent correction process is performed in the spatial spectrum domain,which significantly reduces the computing time by reducing the number of imaging.Simulation and experimental results verify the feasibility and stability of the method.2.In order to solve the problem that two-dimensional imaging cannot truly reflect the position of the target in three-dimensional space,a channel-level MIMO radar threedimensional image filter self-focusing imaging algorithm is proposed.Firstly establish the refraction model of MIMO radar in 3D space,analyze the 3D spatial spectrum relationship of MIMO radar,introduce the elevation dimension information of the array and imaging point in the incidence angle estimation of refraction compensation,consider the influence of the elevation difference in the three-dimensional space,and finally deduced 3D image filter in the spatial spectral domain.In this method,the autofocusing process is decomposed into multiple Single Input Single Output(SISO)channels for processing respectively,and the sub images are summed to obtain the final autofocusing results.Simulation and measured experiments verify the feasibility and stability of this method.3.Aiming at the problem of large amount of calculation of channel-level image filter,a subarray-level autofocusing imaging algorithm of MIMO radar 3D image filter is proposed.Firstly,a 3D spatial refraction model based on rotation matrix is established.According to the characteristics of transceiver array,MIMO is divided into multiple groups of Single Input Multiple Output(SIMO)forms.The transceiver process of each group of channels is rotated to the same elevation plane through spatial rotation,and the 3D refraction compensation problem is transformed into 2D.And then modify the spatial spectrum wave number to obtain a 3D image filter based on a small number of SIMO channels.By reducing the number of channels and using the variable step search method,the autofocusing efficiency of 3D space is improved.Comparing the channel-level image filter method with this method,the simulation and measured data show that the latter has higher operation efficiency and better focusing effect.