In response to the issue of harmonic data anomalies affecting harmonic impedance estimation, a method based on improved rank regression is proposed, building upon the foundation of rank estimation. This method utilizes harmonic data sampled from the point of common coupling, treating harmonic impedance as regression parameters. Initially, the least squares method is employed to solve for regression parameters. Subsequently, Bayesian optimization is applied to refine these parameters. The optimized parameters are then incorporated into the rank estimation function derived from the residual rank matrix for weighted iteration. The final calculation results are determined through this iterative process. Simulation analysis demonstrates that this method can effectively mitigate the impact of outliers, yielding more accurate harmonic impedance values.