Abstract
The performance of a global navigation satellite system (GNSS) receiver can be significantly degraded in the presence of pulsed interference and jamming. In this study, the authors leverage on tools from robust statistics to enhance the receiver performance, with jamming signals treated as outliers to the nominal, interference-free model. Particularly, the signal samples are pre-processed with a zero-memory non-linearity (ZMNL), which limits the impact of pulsed inference in a principled way. A possible approach for the design of such ZMNL is provided by the M-estimator framework when the noise at the receiver input is modelled with a heavy-tailed distribution. This approach is adopted in this study and the complex signum non-linearity is analysed. This ZMNL is obtained by considering a complex Laplacian noise. This choice is discussed and analysed in the context of GNSS receivers under jamming. The impact of the complex signum non-linearity is theoretically analysed under nominal conditions, that is, in the absence of interference. Theoretical results are supported by Monte Carlo simulations. Real GNSS signals, collected in the presence of jamming, are used to demonstrate the advantages brought by the complex signum non-linearity. Theoretical and experimental results demonstrate the benefits of the proposed approach.
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