Abstract
Positioning solutions based on global navigation satellite systems remain vulnerable to local multipath and non-line-of-sight conditions, a challenge for autonomous systems that must operate reliably across diverse environments. To support context-aware navigation, we quantify pseudorange multipath effects across four environmental settings: canyon, urban, trees, and open sky. Given a known receiver position, the range-free double difference (RFDD) can be used to isolate multipath errors. We propose a refinement accounting for clock biases in a commercial off-the-shelf receiver, which otherwise distort geometric range estimates—a key input to the RFDD. Applying our method to data collected in Toulouse, France, we statistically analyze how multipath errors can be modeled as a function of carrier-to-noise ratio (C/N0) within each labeled environmental context. Histograms and the first four moments—mean, variance, skewness, and kurtosis—offer complementary perspectives, showing that the multipath component of the RFDD may be described by a chi-square-like distribution.
