Radio-Frequency Interference Suppression Under Amplitude and Phase Distortions via Spectral Flatness

Radar systems in practical environments are often affected by radio-frequency interference, which is commonly mitigated by spatial cancellation using auxiliary antennas. However, the use of auxiliary antennas inevitably introduces frequency-dependent amplitude and phase distortions between antennas, degrading signal synthesis and suppression performance. Existing calibration methods usually rely on prior measurements or explicit parameter estimation, making them sensitive to model mismatch, especially in multi-interference scenarios with spectral overlap. This letter proposes a spectral flatness measure (SFM)-based method for distortion compensation and interference suppression. The received signal is decomposed into subbands, where distortions are approximated as locally constant and compensated independently, and all parameters are jointly optimized via a genetic algorithm using the SFM criterion. The method requires no prior information or external calibration signals and achieves robust interference suppression. Simulation and experimental results validate its effectiveness in real interference environments.