eLoran Pulse Optimization and TOA Performance Improvement Using a Transmitter Model-Based Genetic Algorithm

Joonyoung Lee, Euiho Kim*

Global Navigation Satellite System (GNSS) is vulnerable to radio-frequency interference such as jamming and spoofing, which has led to a continued demand for robust alternative navigation systems. In this context, Enhanced Loran (e-Loran) has attracted attention as a ground-based backup navigation system for maritime and aviation applications. However, the ranging performance of e-Loran is degraded by multipath interference and early skywave, which reduce the detection accuracy of the Standard Zero Crossing (SZC) point and consequently degrade positioning accuracy. Previous studies have proposed pulse waveform optimization based on Genetic Algorithm (GA), but most of them assume ideal signal environments without sufficiently considering the hardware characteristics of the actual transmitter, which limits practical applicability. To address this limitation, this study uses MATLAB to perform e-Loran pulse design in an integrated system environment that incorporates a realistic transmitter model. The voltage vector of each half-cycle is defined as a gene for GA-based waveform optimization. In addition, the SAE9990 standard is analyzed to develop a pulse design framework that maintains partial compatibility with existing requirements while allowing extended application. Finally, the Time of Arrival (TOA) estimation algorithm is refined, and the performance of the proposed method is validated through integrated simulations, demonstrating improved robustness against multipath interference compared with conventional designs.
Keywords: e-Loran, genetic algorithm, transmitter, navigation system

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