Research On Method And Technique Of Ultra-wideband Through-the-wall Radar Imaging

Ultra-wideband through-wall-radars(TWRs)that can detect objects behind the obstacles by utilizing the penetration ability of low-frequency-band EM wave,are playing an important role in a variety of military and civilian applications,such as urban operation,special operation,anti-terrorism and rescue.However,confined by the real practice,TWRs usually work in the city environment,thus the time and space of observation are limited.Besides,because of the power attenuation when EM penetrating in the wall,the signal-to-clutter-ratio(SCR)is very small.Meanwhile,the phenomenons,i.e,refraction,multi-reflection and velocity slowing,obscure the target imaging and shift their imaging positions.As a result,the resolution is largely deteriorated and the imaging quality is severely affected.To improve the imaging quality,the dissertation fist starts on the medium transmitting model.Aiming at the above mentioned problems,the dissertation presents its works as follows: the improved through-the-wall imaging method,moving target imaging and ghost mitigation,through-the-wall refocusing imaging,and wall clutter mitigation.By using these proposed methods and techniques,the imaging quality and SCR is improved.The main work and contributions of this dissertation are as follows:Fist,the transmitting echo is derived comprehensivly considering the signal style,wall effects,signal transmitting channels and polarization styles.Echo characteristics are further compared by considering the system mode,polarization style,and scanning mode.The constructed mode and derived conclusions are very helpful for further algorithm research and system design.Then,aimed at the problems about gratelobes,sidelobes and ghost,the imaging method performance and processing flow are improved in several aspects.Considering the requirement and system modes,the existing imaging methods are compared,and the basic imaging method for this dissertation is determined.Considering the algorithm performance in real practice,the processing flow of the method is improved.A binary detection is introduced to improve the coherence factor based imaging algorithm.The improved method has satisfying performance in gratelobes and sidelobes mitigation,which is suitable for the imaging scene combing with powerful and weak targets.Besides,aiming at the target obscured problem in an enclosed environment,an echo model for extended target is constructed,and consequently a moving extended target imaging flow is designed,which mitigates the ghosts caused by the traditional differential imaging processing.The target imaging quality is improved.Aiming at the wall compensation problem,first,by utilizing the position information of association target,a multiarray refocusing method is proposed,which can compensate wall effects fast especially in the building detection applications.Then,for wall compensation in single array applications,a constant transmitting-wave-vector angle spatial-spectrum refocusing method is proposed.The method adopts spatial spectrum compensation to replace the time domain compensation.As a result,the computation burden is simplified without deteriorating the algorithm precision.Besides,the wall clutter is constructed for monostatic mode and bistatic mode,respectively.The difference between wall clutter and target echo is compared in time,space and frequency domain.The effects of array topology on the correlation among echoes are analyzed.A principle of symmetry-channel is proposed,and consequently,a space symmetry based wall clutter mitigation algorithm is proposed.Then,according to the derived signal model,imaging characteristics of the wall and target are concluded.An antenna planes based wall clutter mitigation algorithm is proposed.These two algorithms can mitigate wall clutter,and are helpful for the further array and system design in real practice.Additionally,aimed at the wall clutter problems,the drawbacks of the existing decomposition method are further analyzed and modified.The modified method adopts the imaging quality as the merit,and introduces the feedback scheme to evaluate the imaging quality.The experimental processing results show that the modified method can fulfill the dimension estimation for wall clutter subspace,and improve the algorithm performance in wall clutter mitigation.