Unmodeled-error-corrected stochastic assessment for a standalone GNSS receiver regardless of the number of tracked frequencies

Abstract

Appropriate stochastic modeling is crucial to Global Navigation Satellite System (GNSS) applications. However, traditional methods based on the zero baseline and ultra-short baseline cannot accurately estimate the stochastic characteristics of GNSS measurements of a complete receiving system, i.e., receiver, antenna, low-noise amplifier, and cable. We propose the unmodeled-error-corrected stochastic assessment methods that can be used for a standalone receiver regardless of the number of tracked frequencies. First, the raw observation equations considering the unmodeled errors are deduced based on the geometry-free or geometry-based model. Second, some parameters are chosen as the datum for rank deficiency elimination. Third, the multi-epoch parameterization is used to correct the unmodeled errors in the reparametrized observation model. Finally, the covariance component estimation can be applied to determine the variance components. Three different and representative measurement campaigns were conducted, including the low-cost board, integrated receiver, and smart phone. The results show that the proposed method based on a standalone receiver can assess the stochastic characteristics of GNSS measurements. Since the stochastic characteristics of different low-cost receivers share different patterns, and the noise from the internal antenna cannot be easily ignored, the proposed method is essential.