Robust Semiparametric DOA Estimation in non-Gaussian Environment
Signal Processing
2020-04-29 v1
Abstract
A general non-Gaussian semiparametric model is adopted to characterize the measurement vectors, i.e.\ the \textit{snapshots}, collected by a linear array. Moreover, the recently derived \textit{robust semiparametric efficient} -estimator of the data covariance matrix is exploited to implement an original version of the MUSIC estimator. The efficiency of the resulting -MUSIC algorithm is investigated by comparing its Mean Squared Error (MSE) in the estimation of the source spatial frequencies with the relevant Semiparametric Stochastic Cram\'{e}r-Rao Bound (SSCRB).
Cite
@article{arxiv.2004.13394,
title = {Robust Semiparametric DOA Estimation in non-Gaussian Environment},
author = {Stefano Fortunati and Alexandre Renaux and Frédéric Pascal},
journal= {arXiv preprint arXiv:2004.13394},
year = {2020}
}
Comments
This paper has been submitted to 2020 IEEE Radar Conference, Florence, Italy, September 21-25, 2020