STATISTICAL NEAR-FAR DETECTION TECHNIQUES FOR GNSS SNAPSHOT RECEIVERS

In indoor and dense urban environments, Global Navigation Satellite System (GNSS) receivers have to cope with extremely low received power levels. In these circumstances, GNSS receivers become vulnerable to adverse propagation effects such as near-far interference, where acquisition is affected by large cross-correlation peaks because signals from different satellites experience very different attenuation patterns. This translates into a degraded pseudoranges performance, and enters into conflict with the demand for improved positioning accuracy and integrity motivated by the widespread use of GNSS receivers in these scenarios. This paper presents novel low-complexity techniques for near-far detection in high-sensitivity GNSS receivers. These techniques exploit the statistical differences of the acquisition measurements in the presence and in the absence of near-far, and they outperform previously proposed detectors in terms of detection probability. A method to determine the detection threshold for a given probability of false alarm is also presented. Simulations for Galileo E1C signals are used to illustrate the enhanced performance of the proposed algorithms.