Joint Design of SAR Waveform and Imaging Filter Based on the Signal-to-clutter-plus-noise Ratio Criterion

To address the critical issue of weak-target imaging performance in Synthetic Aperture Radar (SAR), this paper proposes a method for jointly designing the SAR waveform and imaging filter based on the Signal-to-Clutter-plus-Noise Ratio (SCNR) criterion. The method first establishes a joint optimization model aimed at maximizing the SCNR. This model comprehensively considers constant modulus constraints, mainlobe peak constraints, sidelobe levels, and target scattering uncertainty, resulting in a nonconvex, multiconstrained optimization problem with a max-min structure. To solve this problem, this paper develops a sequential alternating optimization framework that decomposes the original problem into two subproblems: waveform design and filter design. A strategy combining the epigraph transformation with the majorization-minimization algorithm is employed to handle the nonconvex fractional objective function and constraints. Auxiliary variables are introduced to extend the feasible region, thereby guaranteeing feasibility at the initial iteration. A penalty term that increases progressively with the number of iterations is then incorporated, ultimately forcing the auxiliary variables to approach zero and thereby enabling the solution of the original problem. The convergence and computational complexity of the proposed algorithm are also analyzed. Experimental results demonstrate that, compared with traditional linear frequency-modulated signals with identical parameters, the joint design scheme exhibits pronounced performance advantages in simulated, semi-physical, and field scenarios. The proposed method improves the SCNR of SAR images by more than 3.2 dB, providing an engineering-feasible approach for enhancing the detection and imaging performance of SAR systems for weak targets.