Myriad non‐linearity for GNSS robust signal processing

The robustness of standard correlation‐based Global Navigation Satellite System (GNSS) signal processing can be significantly improved by pre‐processing the input samples with a zero‐memory non‐linearity (ZMNL). A paradigm for the design of ZMNLs is provided by the M‐estimator framework where heavy‐tailed probability density functions (pdfs) are used to model the impairments affecting the input samples. The myriad non‐linearity, obtained considering a Cauchy pdf, is analysed for the acquisition and tracking of GNSS signals in the presence of pulsed interference. The impact of the myriad non‐linearity is theoretically characterised and Monte Carlo simulations are used to support theoretical findings. Finally, real GNSS signals collected in the presence of jamming are processed: the myriad non‐linearity provides a significant performance improvement with respect to standard GNSS signal processing which is unable to acquire and track the samples affected by interference.