Frequency diverse array 3D-SAR imaging method based on compressed sensing

The hardware design of phased array three-dimension synthetic aperture radar (SAR) system based on wideband transmission signals is complicated, and the received signals are difficult to separate. By applying the frequency diverse array (FDA) to 3D-SAR, each array element only needs to transmit a single frequency signal to obtain wideband observation performance, which greatly reduces the hardware requirements of system. However, due to the space-frequency sparseness of FDA echo signals, the resolution is limited and the sidelobes of radar images are relatively high when using the back projection (BP) algorithm based on matched filtering. To solve this problem, this paper proposes a random frequency diverse array 3D-SAR imaging method based on compressed sensing (CS). The array elements in the tangent-track and the observation positions in the along-track are selected randomly and sparsely to realize two-dimensional sparse sampling of echo data. In the imaging part, orthogonal matching pursuit (OMP) algorithm is used to reconstruct the scattering coefficient of targets. Simulation and experimental results show that CS method not only reduces the data processing amount of FDA-3D-SAR system during imaging, but also effectively suppresses the sidelobes of radar images, and the imaging quality is significantly improved. By using the compressed sensing algorithm, FDA-3D-SAR can accurately reconstruct the information of space targets when the echo is sparse, which verifies the rationality and effectiveness of the proposed method.