An Improved Deconvolution Algorithm for Time-Varying Phase Modulation Signals

Metasurfaces can modify radar echo characteristics by dynamically altering the phase of incident electromagnetic waves, thereby degrading radar signal processing performance. To understand modulation patterns and counteract novel electromagnetic interference, it is crucial to recover the time-varying phase modulation signals generated by metasurfaces. Therefore, this paper proposes an improved optimization-based deconvolution method. First, an optimization model is established by combining the least squares (LS) deconvolution principle with total variation constraints and imaginary part constraints. Then, the alternating minimization (AM), alternating direction method of multipliers (ADMM), and minimax (MM) frameworks are integrated to optimize the attenuation factor and modulation sequence. Finally, simulations validate the effectiveness of the improved method.