GPS, Galileo and Glonass L1 signal detection algorithms based on bandpass sampling techniques

This paper proposes two GNSS signal detection front-end algorithms for GNSS receivers, thus saving valuable resources in chasing signals that are not available. These algorithms can also be used to develop a fast multi-signal GNSS software receiver. With the planed completion of Galileo and Glonass CDMA systems, a GNSS receiver can take advantage of these and GPS signals to aid localization in bad reception areas such as urban-canyons. Such receivers deploy all available resources to find signals even when signals are not available. This paper proposes two approaches that can rapidly detect, in a single view, any GNSS signal power present. The first approach analysis the three signals excitations to a nonlinear bandpass sampling (BPS) receiver that folds these three signals, with their harmonics, to their first Nyquist zone (FNZ). Then, it analyzes their behavior model based on a Volterra algorithm to obtain kernels of these three GNSS signals, if available. Because all three GNSS signals are transmitted with the same carrier frequency, the second approach filters out the right-side/lobe of the Glonass signal and the left-side/lobe of the Galileo signal. This will enable none overlapped folding, based on BPS, of these two signals with the 3
^rd
GPS harmonic in FNZ. These approaches make any GNSS receiver well-informed of available signals, and so devote appropriate resources to acquire and track available signals only. Matlab simulation results prove these two approaches and show that much valuable overall processing time, especially on Smartphones, can be saved by adopting these approaches.