Mitigation of sparsely sampled nonstationary jammers for multi-antenna GNSS receivers
Yimin D. Zhang, Moeness G. Amin, Ben Wang
Abstract
In this paper, we address the suppression of frequency modulated jammers in a multi-sensor Global Navigation Satellite System (GNSS) receiver. In particular, we consider the case of sparsely sampled signals and compressed observations. In this case, applying conventional time-frequency (TF) analysis for jammer characterization produces noise-like artifacts which, if not properly considered, would obscure the jammer TF representation and lead to considerable errors in jammer signal estimation and excision. In the proposed approach, a multi-sensor data-dependent TF kernel is applied for effective mitigation of artifacts due to missing samples. Sparse reconstruction methods are then applied to obtain nonparametric instantaneous frequency estimation. We apply the continuous-structure aware Bayesian compressive sensing method to exploit the contiguous nature of the jammer TF signature, leading to enhanced localization and suppression.
BibTeX
@inproceedings{icassp2016_mitigationofspar,
title = {Mitigation of sparsely sampled nonstationary jammers for multi-antenna GNSS receivers},
author = {Yimin D. Zhang and Moeness G. Amin and Ben Wang},
booktitle = {ICASSP 2016},
year = {2016}
}