The Big Picture on ASFs: the Validity of Predicted ASFs over Long Distances

Recently, the Loran-C system was identified as a possible backup for GPS in en route aircraft navigation to replace the current radar-based systems. In its current state, the Loran-C position determination solution assumes a uniform propagation speed of the Loran signal, regardless of weather, terrain, or ground conductivity. In reality, these factors severely affect the propagation speed and, hence, the Loran position solution- at times offsetting it by more then a mile. Efforts are currently underway to survey major harbors and airports to create ASF correction grids. In addition, a network of Loran ASF monitors is being deployed. However, these correction grids and monitors will be useful only in few select locations; there are no plans for wide area surveys. In this paper we evaluate an alternative method for improving Loran accuracy by using computer generated ASFs. The paper discusses four different ASF modeling methods provided by two different software packages, namely Balor and Lups. The evaluation is based on measured ASFs that were collected on board of an FAA airplane, flying long straight paths between chosen Loran towers. The paper shows graphical and quantitative analysis of the ASF modeling tool’s performance, highlighting specific cases of their fallibility, differences between methods, and a comparison with measured data. To demonstrate what level of improvement in accuracy can be achieved using computer generated ASF grids for CONUS, those ASFs were employed in the Loran position solution of sample Loran data and compared with non-corrected positions. This paper shows that ASF modeling tools do improve Loran accuracy. Further, for the examples tested, the predicted ASFs were able to meet RNP (1.0) requirements; however additional evaluation should be done to prove it for larger navigation areas