Bayesian Filtering Approaches for Unambiguous BOC Tracking under Weak Signal Conditions

Binary Offset Carrier (BOC) is a robust modulation proposed for Galileo and modernized GPS signals. Its auto-correlation function (ACF) is characterized by a narrow main lobe and multiple side lobes. BOC modulated signals suffers from ambiguous tracking because of the possibility of side-peak locking. This paper introduces two Bayesian-based algorithms that provide an unambiguous BOC tracking without compromising the advantages of the BOC modulation. The characteristics of the ACF are utilized in the design. The first algorithm is based on Extended Kalman filtering (EKF), while the second algorithm employs an optimal Bayesian filtering approach. Two delay lock loops (DLL) are implemented. The first DLL operates around the locked-on peak to refine the code delay estimate; its discriminator function is based on the narrow main lobe of the ACF. The measurements are taken from early and late correlators located within the locked-on lobe. The second DLL is designed to operate on the whole ACF coverage to detect any bias toward a side peak. The design is based on detecting the correct shape of the ACF. The output of the second DLL is processed to indicate the location of the main peak. The processed output is added to the output of the first DLL to accurately align the replica code with the received code. Each of the two tracking algorithms is integrated with a carrier tracking algorithm to complete the tracking module. The performance of the tracking algorithms are evaluated using simulated L1B and L1C Galileo signals.