应对复杂环境的“GNSS+”融合导航应用体系设计

Design of "GNSS+" Fusion Navigation Application System for Complex Environment

摘要:

针对复杂环境下全球卫星导航系统（GNSS）面临的抗干扰能力弱、信号遮蔽及动态障碍等挑战，研究基于多源数据融合、低轨卫星增强和人工智能深度学习等多技术融合的导航能力提升方案。采用多模态感知、智能决策与抗干扰技术融合方法，构建“感知-决策-应用-反馈” 闭环体系，设计多层级协同的“GNSS+”融合导航架构，包含信号感知层、分析决策层和应用服务层。通过建立动态权重评价指标体系，量化评估系统性能，实现导航策略动态调整，为复杂环境下智能化导航系统设计提供理论与技术支撑。

Abstract:

To address challenges such as weak anti-interference capability, signal occlusion, and dynamic obstacles faced by the Global Navigation Satellite System (GNSS) in complex environments, this study explores solutions for improving navigation capabilities based on the integration of multiple technologies including multi-source data fusion, low-orbit satellite augmentation, and artificial intelligence deep learning. An integrated approach combining multi-modal perception, intelligent decision-making, and anti-interference technologies is adopted to construct a "perception-decision-application-feedback" closed-loop system, and a multi-level collaborative "GNSS+" fusion navigation architecture is designed, which includes a signal perception layer, an analysis and decision layer, and an application service layer. By establishing a dynamic weight evaluation index system to quantify system performance, dynamic adjustment of navigation strategies is realized, providing theoretical and technical support for the design of intelligent navigation systems in complex environments.