Efficient Cross-View Localization in 6G Space-Air-Ground Integrated Network

arXiv:2603.11398 · cs.NI, cs.AI · Submitted 2026-03-12 · Read on arXiv

cs.NI, cs.AI

Submitted: 2026-03-12

Updated: 2026-08-31

Code: https://github.com/xuyanbing11/cross

License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/

Terminology

• Feature Extraction — 16× in this paper · explained in 2 episodes
• Accuracy — 13× in this paper · explained in 1 episode
• Robustness — 9× in this paper · explained in 5 episodes
• Actor — 7× in this paper · explained in 3 episodes
• Alignment — 4× in this paper · explained in 1 episode
• Core — 4× in this paper · explained in 2 episodes
• Adaptability — 3× in this paper · explained in 1 episode
• Digital Twin — 3× in this paper · explained in 4 episodes
• Q-learning — 3× in this paper · explained in 3 episodes
• Adaptation — 2× in this paper · explained in 1 episode
• Augmented Reality — 2× in this paper
• Benchmark — 2× in this paper · explained in 2 episodes
• Reinforcement Learning — 2× in this paper · explained in 4 episodes
• Transformer — 2× in this paper · explained in 2 episodes
• Accountability — 1× in this paper · explained in 2 episodes
• Actor-Critic Model — 1× in this paper · explained in 1 episode
• Adversarial Attacks — 1× in this paper · explained in 1 episode
• Calibration — 1× in this paper · explained in 7 episodes
• Cosine Similarity — 1× in this paper · explained in 3 episodes
• Distillation — 1× in this paper · explained in 2 episodes
• Dynamic Adaptation — 1× in this paper · explained in 2 episodes
• Feature Selection — 1× in this paper · explained in 4 episodes
• Generalization — 1× in this paper · explained in 13 episodes
• Interpretability — 1× in this paper · explained in 15 episodes
• Modality Gap — 1× in this paper · explained in 4 episodes
• Redundancy — 1× in this paper · explained in 2 episodes
• Reinforcement Learning (RL) — 1× in this paper · explained in 25 episodes
• Reward Function — 1× in this paper · explained in 2 episodes
• Self-distillation — 1× in this paper · explained in 6 episodes

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