Statistical test applied to detect distortions of GNSS signals

Abstract

The extremely low power of Global Navigation Satellite System (GNSS) signals makes them vulnerable to disturbances and interference from external sources. These induce distortions on the correlation function that reflect upon a degraded pseudoranges measurement and poor positioning accuracy. On the other hand, the wide spread use of GNSS receivers in critical applications demands for improved performance in terms of positioning accuracy and integrity. This paper proposes a new algorithm based on the statistical testing of post-correlation measurements to detect signal distortions and to prevent degradations in the receiver positioning performance. The application of statistical tests to GNSS is not yet deeply investigated, but some recent works already show good performance when Goodness of Fit (GoF) tests are applied to raw signal samples to detect interference. The paper presents a quality monitoring algorithm, based on the application of a statistical testing, known as sign test, applied to the post correlation stage of a GNSS receiver. Promising results are obtained to detect distortions in the correlation shape, for two different harsh environments, i.e., with the presence of interference sources and under a spoofing attack. The main advantages of the proposed method are the low complexity, the indipendence from the type of disturbance and the possibility of its application to any GNSS modulation.