Research On High Resolution Imaging Algorithm Of Terahertz CSAR

Terahertz CSAR has the characteristics of high operating frequency band,short synthetic aperture time,and high resolution.It can detect target areas of interest all day and all weather under various complex environmental conditions.It is widely used in military,mapping,early warning and other important fields.Due to the special trajectory of terahertz CSAR and the large amount of echo data of terahertz CSAR,the traditional SAR imaging algorithm is no longer applicable.In order to meet the ever-changing practical needs of terahertz CSAR,it is of great significance to carry out research on highresolution imaging algorithms based on terahertz CSAR.The main work of thesis includes the following aspects:1.Starting from the basic principles of terahertz CSAR imaging,the echo signal expression is derived based on the terahertz CSAR imaging scene,and two pulse compression techniques of matched filtering and frequency modulation are analyzed.Then the imaging resolution formula of terahertz CSAR is summarized.Finally,two representative terahertz CSAR imaging algorithms are introduced,and the two algorithms are compared and analyzed in terms of imaging quality and imaging efficiency.2.Aiming at the requirement of terahertz CSAR for high-resolution real-time imaging of the target area,the traditional PFA algorithm is improved,and a highresolution imaging algorithm for terahertz CSAR based on PCS is proposed.The algorithm uses PCS principle to replace the interpolation operation in PFA algorithm,and compensates the quadratic phase error introduced by the plane-wavefront approximation in PFA algorithm in blocks according to the maximum phase error tolerance range of the scene.Compared with the traditional PFA algorithm,the improved algorithm effectively improves the imaging efficiency,and at the same time removes the geometric distortion and defocus phenomenon in the PFA imaging results.And the effectiveness of the algorithm is verified by simulation data and measured data.3.In view of the problems of large amount of echo data,high signal sampling rate and side-lobe interference in the actual imaging process of terahertz CSAR,a terahertz CSAR high-resolution imaging algorithm based on two-dimensional compressive sensing is proposed.Starting from the echo signal after terahertz CSAR defrequency modulation,study the sparse representation of the imaging scene,propose a sparse base matrix construction method that matches the echo signal,and establish a random observation based on the motion model of the echo signal collected by the terahertz CSAR Matrix,and then use the compressive sensing reconstruction algorithm to complete the sparse reconstruction of the target scene.This algorithm effectively reduces the pressure of terahertz CSAR signal acquisition and storage,and reduces the impact of side lobes on resolution in imaging results.Finally,the PFA algorithm,the compressive sensing radar reconstruction algorithm based on Fourier basis and the proposed algorithm are compared by combining the simulation data and the measured data,and the feasibility and advantages of the proposed algorithm are verified.