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In traditional federated receiver, all the tracking channels work independently, and there is no interaction among them. However, in vectorized receiver, stronger channels aid others in their tracking. Such architecture makes a receiver to be of interest for positioning in urban canyons and harsh environments. On the other hand, the combination of GPS and GLONASS as the only augmented global constellations is utilized to increase the availability of the receivers which is defined as the percentage of the epochs with enough number of tracked satellites for solving the positioning equation. We report about the software implementation of a GPS-combined-GLONASS Vectorized Receiver (GGVR) and performance assessment of this architecture in signal attenuation and blocking incidents. We also compare the GGVR performance with a GPS-combined-GLONASS Federated Receiver (GGFR). Experimental tests in different case studies are included. The results show that in the static blocking situation, the GGVR can reacquire the signal immediately after the momentary outage while the GGFR must return to acquisition stage. For two dynamic case studies, one in a suburban road and one in an urban canyon, the position results on the road are the same, but in an urban environment, the GGFR has only 88% availability in contrast to 100% availability of the GGVR.

Snapshot techniques are based on computing a position using only a set of digital signal samples captured over some milliseconds. Existing techniques require, in addition to the satellite ephemerides, a rough knowledge of the position and/or time at which the snapshot was captured. We propose a new method to instantaneously compute a snapshot position and time solution without any reference time or position. The method is based on the addition of a fifth unknown to the instantaneous Doppler equations, which accounts for a time difference between the reference time and the measurement time. Using this new system of equations at different initialization times separated by some hours, time uncertainties of days or weeks can be solved. The algorithm has been implemented in a snapshot GPS software receiver in MATLAB, proving that position accuracies of a few meters with time uncertainties of several weeks can be obtained in a few seconds.