Evolutionary Algorithms Approach for Errors High-Precision Modeling in Single-Frequency GPS Receivers

要旨

The stand-alone GPS accuracy is low due to multiple error sources including multi-path effects, atmospheric effects, clock inaccuracies, unexpected interference, and weak signal applications. Because of the above mentioned error sources, GPS receivers have certain amount of errors and hence error reduction in GPS system is one of the main branches of researchers. Evolutionary Algorithms (EAs) such as Genetic Algorithm (GA), Simulated Annealing (SA), and Particle Swarm Optimization (PSO) are algorithms for optimization and learning based loosely on several features of biological evolution. In this paper, a new approach is presented for standard GPS receiver\'s accuracy improvement using EAs. Method validity is verified with experimental data from an actual data collection, before and after Selective Availability (S/A) error. The results are a highly effective technique for errors high-precision modeling in single-frequency GPS receivers; so that RMS error reduces to less than 0.8 m.