Design and Calibration of a Grid Prediction Algorithm for the St. Marys River Loran-C Chain

摘要

Semi-empirical grid prediction techniques are used to develop a time difference (TD) grid prediction algorithm for the St. Marys River Loran-C Chain. The semi-empirical grid prediction technique uses classical theory to establish the functional form of a Loran-C signal propagation delay model and then measurement data are used to calibrate this model. The grid prediction effort described herein includes propagation model development, data collection site selection, data collection procedures, data quality analysis, algorithm calibration, algorithm accuracy assessment and TD grid chart production. Additional areas of study include an analysis of the interaction of errors due to temporal grid instability with System Area Monitor (SAM) control of the chain, and the analysis of errors in NOAA and Corps of Engineers charts for the St. Marys River region. The calibrated grid prediction algorithm, used to produce three 30 in x 40 inch TD charts of the region, utilizes a polynomial structure to capture the average spatial characteristics of the signal propagation delay over the coverage area. A residual TD grid prediction level of approximately 100 nsec/TD was achieved over the ensemble of data collection sites. Analysis of a limited amount of data recorded over a time period of four months suggests that this residual grid prediction error is probably due to temporal grid instability. Additional data analysis is required to validate this hypothesis. (Author)