Clutter Suppression Technique For Through-the-wall Radar Imaging

Through-wall radar?Through-the-wall-radar,TWR?imaging is widely used in various fields,which makes the TWR system toward the multi-channel,multi-polarization,multi-channel and high resolution direction.With the mass increasing data collection capacity,domestic and foreign scholars have put forward the compressed sensing theory and apply it to TWR imaging.However,under the condition of strong clutter,the performance of compressed sensing theory imaging algorithm will fell sharply.In addition,how to effectively remove the reflected wave from the steel bars inside the wall and improve the ability to image and recognize the target behind the wall of the TWR system has become an urgent problem to be solved.The thesis takes a deep research to alleviate the two problems above.Based on compressed sensing theory TWR sparse microwave imaging technique using the priori information that the detection scenario with sparse,can greatly reduce the sampling rate of echo signals,reduce the data acquisition capacity of the system and realize the accurate-high-resolution imaging to the detect targets.However,in the actual measurement process,the TWR imaging performance decreases sharply due to the strong wall reflection wave.In view of the above problems,by exploiting the low-rank property of the wall reflection signal and sparsity property of the observed scene,clutter suppression technique based on low rank and sparsity constraint for TWR system is proposed.The proposed imaging method exploits the singular value soft-thresholding and ₁l norm minimization technique to perform iteration to solve the low rank and sparsity constraint optimization problem.It adopts compressive sensing framework to achieve the accurate imaging reconstruction of targets behind the wall in the presence of strong wall reflection signal.The imaging results of simulation data and experimental data have verified the effectiveness and validity of the proposed imaging algorithm.The traditional TWR clutter suppression methods including background cancel,mean and the subspace projection.But these algorithms are only for the uniform wall clutter suppression,in practice,because of the existence of steel bars and utility pipes in the wall,the traditional methods are no longer applicable to eliminate the reflected signals of the wall internal structure.According to the above problems,considering the low-rank property of the reflection wave signals from the steel bars in the wall and the sparsity characteristic of the echo from the targets behind the wall,this paper puts forward an algorithm based on low-rank and sparse representation for TWR clutter suppression.The algorithm is solved by solving the optimization problem of the combination of nuclear norm and ₁l norm.The simulation results has verified the algorithm can effectively remove wall clutter from internal steel bars or utility pipes.