Simulation Research on ASF Grid Establishment Methods

The ASF grid is one of the important methods for improving the performance of the eLoran system. When an ASF grid is established, users can calculate ASF through the ASF grid database and bilinear interpolation algorithms, thereby obtaining high-precision ASF values. However, establishing an ASF grid is a complex process, involving not only extensive data collection tasks but also the cumbersome processing of the collected data. This paper investigates and analyzes algorithms for establishing ASF grids under different conditions. When the number of test points exceeds the number of grid vertices, grids built using interpolation algorithms—particularly the inverse bilinear interpolation algorithm—perform the best, while those constructed using the Kriging algorithm perform second best, and the inverse distance interpolation algorithm yields the largest errors. When the number of test points is less than the number of grid vertices, grids constructed using the Kriging algorithm perform the best, while the inverse distance interpolation algorithm produces the largest errors. As a result, the inverse bilinear interpolation algorithm is the best choice, when the test points are more than the grid points. The Kriging algorithm is recommended, when the test points are sparse.