Improving the performance of Unitary ESPRIT via pseudo-noise resampling

A new pseudo-noise resampling technique is proposed to mitigate the effect of outliers in Unitary ESPRIT. Our algorithm improves the performance of Un itary ESPRIT in unreliable situations, where the so-called reliability test has a failure. For this purpose, we exploit a pseudo-noise resampling of a failed Unitary ESPRIT estimator with a censored selection of "successful" resamplings recovering the nonfailed outputs of the reliability test.