Research On Impulse Through-the-wall Radar Imaging Method Based On One-bit Compressive Sensing

The through-the-wall radar based on the impulse system has the advantages of fast measurement speed,strong anti-interference ability,strong penetration ability,and high resolution.However,the amount of data collected during the imaging of the impulse through-the-wall radar is too large,resulting in abnormal data quantification and transmission difficult.In this paper,one-bit compressed sensing is applied to the field of impulse through-the-wall radar imaging to minimize the amount of imaging data while ensuring accurate imaging.The main research contents of this paper are as follows:(1)In-depth study of one-bit compressed sensing theory,the binary iterative hard threshold algorithm(BIHT)is applied to the field of impulse through-the-wall radar imaging.In the simulation experiment,the imaging results of the BIHT algorithm and the traditional back projection algorithm(BP)are compared.The results show that the one-bit compressed sensing imaging quality using the BIHT algorithm is better,and the amount of data required for imaging is much smaller Traditional BP imaging.(2)Aiming at the two-level block sparsity of impulse through-the-wall radar signals,a one-bit compressed sensing imaging method for impulse through-the-wall radar based on two-level block sparsity is proposed.The proposed imaging method uses the Enhanced Binary Iterative Hard Threshold(E-BIHT)algorithm to accurately reconstruct the scene,and the two-level block sparsity is applied to the radar imaging process to improve the imaging of clustered targets quality.The simulation experiment results show that the proposed imaging method has a higher SNR of the imaging reconstruction result compared with the imaging method using the BIHT algorithm,and has a better imaging performance for clustered targets.(3)Aiming at the multi-view impulse through-the-wall radar measurement model,an impulse through-the-wall radar one-bit compressed sensing imaging method based on Multiple Measurement Vectors(MMV)is proposed.The proposed imaging method performs multiple sets of independent one-bit compressed sensing measurements,and centrally transmits the measured values to a data fusion center(FC)for processing,and uses a centralized binary iterative hard threshold(C-BIHT)algorithm to accurately reconstruct the reflection coefficient vector.The simulation experiment results show that the proposed imaging method can image the detection scene with high quality under different SNR.