Prediction Modeling of Propagation Delay in eLoran System Based on Meteorological Factors

The study in this paper centers on the prediction of the propagation delay of the eLoran system on the Xi’an-Chengdu path, focusing on the influence of meteorological factors on the propagation delay. First, the significant correlation between meteorological factors and propagation delay is verified by correlation analysis. Subsequently, a propagation delay prediction model based on BP neural network and long short-term memory (LSTM) network is constructed, and a PSO-LSTM model combined with particle swarm optimization (PSO) algorithm is further proposed to enhance the prediction accuracy. The prediction models are evaluated and compared through experiments, and the results show that the PSO-LSTM model outperforms the other models in terms of prediction accuracy, and provides an effective solution for the prediction of the propagation delay of the eLoran system.