Effect of Constraining a Limited Number of Slant Ionospheric Corrections in PPP and an Improved Partial Tight-Constraining Algorithm

Abstract

With external ionospheric corrections, precise point positioning solutions can be augmented with proper constraints, enabling fast convergence and high-precision positioning performance. However, there are two main issues in user algorithms. First, the contribution of the number of applied ionospheric corrections to positioning performance is not clear to users. For instance, in low-cost sensors where computation resources are limited, applying too many corrections from the server will possibly cause a slow response. Second, the determination of constraining strength for corrections from different satellites remains challenging. Therefore, this article evaluates the effect of the number of ionospheric corrections on positioning errors and convergence time, and proposes an improved tight-constraining algorithm for partially reliable corrections. Static and simulated kinematic positioning results confirm that the more corrections applied, the better the positioning performance. However, the positioning accuracy only has limited improvements when several corrections are already applied, especially in the north direction. The proposed method reduces static positioning root-mean-square errors by 43.4%, 26.9%, and 32.1% in the east, north, and up directions, respectively, compared to solutions without constraint. In simulated kinematic results, the convergence time is further shortened by 7.7%, 4.8%, and 2.5% for the east, north, and up directions, respectively, compared to cases where all corrections are applied.

Jiahuan Hu

Postdoctoral Fellow

Research interests include GNSS precise point positioning, PPP-RTK, atmospheric modeling, and smartphone precise positioning.

Yao Shi

Research Assistant

Research interests include PPP ambiguity resolution data processing and machine learning applications in GNSS.