Physics-Informed Diffusion Model for Complex-Valued Radar Sea Clutter Generation

We propose a physics-informed diffusion framework for radar sea clutter generation with two key innovations: a novel component consistency mechanism that preserves intrinsic statistical relationships between real and imaginary parts of complex signals, and a comprehensive physics-guided diffusion approach that systematically integrates domain-specific priors. Our framework represents complex-valued signals through a two-channel diffusion process with a KL divergence-based constraint ensuring proper distributional alignment between real and imaginary components. To enhance physical fidelity, we develop a multi-prior guidance scheme that enforces essential domain knowledge throughout the diffusion process: Doppler spectral characteristics, power spectral density, local signal smoothness, and reference pattern matching. These physics-based priors continuously guide the generation process to maintain physical correctness while ensuring numerical stability. This systematic incorporation of physical properties and constraints into the diffusion model for sea clutter generation presents a novel contribution to physics-informed signal synthesis, enabling more realistic sea clutter generation for advanced radar applications.