BOC-FPDNet: BOC First arrival Path Detection in Multipath Channel for GNSS Positioning

Binary Offset Carrier (BOC) modulation is used in the Global Navigation Satellite System (GNSS). Unlike Binary Phase Shift Keying (BPSK) in the Global Positioning System, BOC-modulated signals have side-peaks in the autocorrelation function (ACF) leading to positioning errors in multipath channels. This paper introduces a two-stage BOC first arrival path detection network (BOC-FPDNet). This includes side-peaks cancellation (SC) and multipath time delay estimation (MDE) for BOC modulation. The SC is a deep learning-based method that cancels side-peaks without added computational load or noise increase. The MDE uses Multi-head attention to extract ACF output features and consists of two heads, positive and negative sample detector, for time delay estimation. The effectiveness of BOC-FPDNet is demonstrated by comparing it to super-resolution and other deep learning detection techniques in various multipath channel simulations and real urban data. Results show BOC-FPDNet provides superior side-peak cancellation and accurate BOC-modulated signal detection.