Data-Replay Analysis of LAAS Safety during Ionosphere Storms

Abstract

As reported in [2,4,5], previous Stanford research has identified the potential for severe ionosphere spatial gradients to affect Local Area Augmentation System (LAAS) integrity. In previous work [1], real-time position-domain geometry screening was used to maximize LAAS availability in the presence of ionosphere anomalies by broadcasting an inflated value of ó vig so that the maximum-ionosphere-induced-error-invertical (MIEV) for all viable airborne “subset” geometries (subsets of the set of satellites visible to and approved by the LGF) is below a pre-determined safe limit. The results of this work are based on the LAAS ionosphere spatial-gradient “threat model” established and validated with ionosphere storm data observed from WAAS and IGS since 2000 [2,4]. This previous approach leads to marginal availability of the required integrity (95 to 99 percent) and does not give the higher availability that is desired (99.9 percent or higher). In this paper, data from the Ohio cluster of CORS stations on November 20, 2003 and the North Carolina cluster of CORS stations on October 29, 2003 from [6] are used to perform “data-replay” analysis for several independent station pairs with separations from 23 to 75 km. These separations are significantly further than the effective LAAS user-to-LGF separation at the CAT I decision height. Comparisons of the result of data-replay analysis with the result of worst-case simulation in the manner of [1] are made. The conclusion derived from these comparisons is that CAT I ionosphere analysis performed by worst-case simulation is conservative but not unreasonable.