Implementation of Advanced Carrier Tracking Algorithm Using Adaptive-Extended Kalman Filter for GNSS Receivers

Abstract

Use of Global Navigation Satellite Systems (GNSS) receivers for real-time applications has improved significantly all over the world. The main problem with the designed receivers is their failure to function under harsh environmental conditions because of the structured phase-locked loop (PLL) architecture. One of the most critical phenomena that cause signal degradation in GNSS receiver is ionospheric scintillations, which create disturbances in amplitude and phase of the received signal. The problem in signal acquisition and tracking, even in the severe canonical fades (deep amplitude fading correlated with reference to half cycle phase jumps), can be mitigated using robust and adaptive carrier tracking algorithms. The autoregressive exogenous modeling parameters are useful in estimating the amplitude and phase scintillations. The proposed adaptive-extended Kalman filter (AEKF) approach works as an effective carrier tracking algorithm maintaining a balance in dual problems faced by PLL-based receivers, i.e., (estimation versus mitigation) and (dynamics versus noise reduction) tradeoff. The developed AEKF algorithm performed well for synthetic Cornell scintillation monitor data and for Global Positioning System L1 PRN 12 data collected around 21.30 H (local time) on October 24, 2012, in Rio de Janeiro, Brazil, with GNSS Software Navigation Receiver.