Layout Optimization of Tunnel Foundation Pseudo-satellite Based on Zone-adaptive Precision Genetic Algorithm

To address positioning failures caused by signal obstruction in tunnel environments for Global Navigation Satellite Systems, we propose a pseudo-satellite layout optimization method based on the Zone-adaptive Precision Genetic Algorithm (ZAP-GA).First, we constructed a tunnel simulation model and sampled the entire tunnel grid.Then, we evaluated the quality of pseudo-satellite layouts using the average position dilution of precision (PDOP) and coverage rate as key metrics at each sampling point.Second, the ZAP-GA partitioning method provided a uniform coverage of the pseudo-satellite and made adaptive adjustments for variable stride lengths and edge regions.At the same time, the fitness function was optimized precisely by balancing the weighted PDOP and the spacing of the pseudo-satellite with the configuration of the mounting surface.Optimization was finally achieved by integrating tournament selection, single-satellite gene segment crossing, and a robust elite retention mechanism.Experimental results demonstrate that the proposed method achieves an average PDOP of 2.7326 across all sampling points with only eight pseudo-satellites, accompanied by 95.82% overall regional coverage and full coverage in the core area.These performance metrics fully meet the requirements for precise positioning in tunnel scenarios.