Design and Simulation of Sidelobe Suppression Filters Using Second-Order Cone Programming

In this paper, we investigate the design and simulation of sidelobe suppression filters utilizing second-order cone programming (SOCP). We provide detailed explanations on designing filters using m-sequences and mismatch filters, while accounting for gain processing loss. The implementation involves formulating the optimization problem as SOCP constraints and solving it using convex optimization techniques. Key algorithmic components include generating pseudo-random m-sequences through shift registers and designing mismatch filters to minimize peak sidelobe levels. Additionally, we discuss critical concepts and techniques related to this filter design, including computational efficiency analysis and trade-offs between mainlobe width and sidelobe suppression. Through comprehensive research and analysis, we demonstrate improved understanding and practical application of this design approach, achieving enhanced performance in real-world scenarios. MATLAB code snippets illustrate the use of cvx toolbox for SOCP formulation and filter coefficient optimization.