JET: Joint Error Information Theoretic Criterion for Multichannel Compressive Sampling Systems

This brief proposes a joint error information theoretic criterion (JET) assisted blind calibration method for multichannel compressive sampling systems under complete blindness. Addressing gain-phase errors and mutual coupling, we first estimate these errors, then leverage an information theoretic criterion (ITC) to estimate signal sparsity, enabling blind calibration and signal reconstruction. An optimal ITC penalty term is derived through joint error model analysis. Simulation and hardware experiments validate the method’s effectiveness. Simulation experiments and hardware experiments confirm that our method achieves over 99.9% accuracy in sparsity estimation within the range [0-0.5] of gain-phase errors and mutual coupling errors.