Effect of Outlier Removal from Temporal ASF Corrections on Multichain Loran Positioning Accuracy

TL;DR

This study investigates how removing outliers from temporal ASF correction data can improve the accuracy of multichain Loran positioning, a terrestrial navigation system that enhances traditional Loran performance.

Contribution

The paper presents an experimental analysis demonstrating the impact of outlier removal on improving multichain Loran positioning accuracy.

Findings

Outlier removal improves positioning accuracy.

Temporal correction data quality significantly affects performance.

Enhanced accuracy achieved through outlier mitigation.

Abstract

The widely used global navigation satellite systems (GNSSs) are vulnerable to radio frequency interference (RFI). Long-range navigation (Loran), a terrestrial navigation system, can compensate for this weakness; however, it suffers from low positioning accuracy, and studies are under way to improve its positioning performance. One such study has proposed the multichain Loran positioning method that uses the signals of transmitting stations belonging to different chains. Although the multichain Loran positioning performance is superior to the performance of conventional methods, the additional secondary factor (ASF) can still degrade its positioning accuracy. To mitigate the effects of temporal ASF, which is one of the ASF components, it is necessary to obtain temporal correction data from a nearby reference station at a known location. In this study, an experiment is performed to verify the effect of removing the outliers in the temporal correction data on the multichain Loran positioning accuracy.