This paper presents an iterative algorithm for detecting and estimating specular components (SCs) and the dense component (DC) in single-input—multiple-output (SIMO) ultra-wide-band (UWB) multipath channels. The algorithm super-resolves SCs in the delay-angle-of-arrival domain and estimates the parameters of a parametric model of the delay-angle power spectrum characterizing the DC. Channel noise is also estimated. The design is inspired by the sparse Bayesian learning (SBL) framework, incorporating a threshold condition to determine whether a candidate SC should be retained or pruned. The threshold is adapted using extreme-value analysis to ensure a prescribed probability of detecting spurious SCs. Synthetic and real channel measurement data demonstrate the algorithm's effectiveness, showing accurate detection and estimation of SCs even when their separation is below the Rayleigh resolution limit. The algorithm outperforms state-of-the-art super-resolution channel estimators in terms of robustness in estimating closely spaced SC amplitudes.This paper presents an iterative algorithm for detecting and estimating specular components (SCs) and the dense component (DC) in single-input—multiple-output (SIMO) ultra-wide-band (UWB) multipath channels. The algorithm super-resolves SCs in the delay-angle-of-arrival domain and estimates the parameters of a parametric model of the delay-angle power spectrum characterizing the DC. Channel noise is also estimated. The design is inspired by the sparse Bayesian learning (SBL) framework, incorporating a threshold condition to determine whether a candidate SC should be retained or pruned. The threshold is adapted using extreme-value analysis to ensure a prescribed probability of detecting spurious SCs. Synthetic and real channel measurement data demonstrate the algorithm's effectiveness, showing accurate detection and estimation of SCs even when their separation is below the Rayleigh resolution limit. The algorithm outperforms state-of-the-art super-resolution channel estimators in terms of robustness in estimating closely spaced SC amplitudes.