Byzantine Fault-Tolerant Distributed Passive Localization with Dual-Layer Data Fusion
Zijian Song, Jing Zhu · 2024
This paper proposes a distributed passive localization system that utilizes dual-layer data fusion through smart contracts to enhance the accuracy and security of positioning in the presence of Byzantine nodes. Firstly, the system groups sensors based on distance and utilizes passive sensors for Angle of Arrival (AOA) measurements, ensuring both precise localization and operational concealment. Communication between nodes is based on blockchain technology, with encryption algorithms and hash signatures safeguarding data security. Subsequently, the proposed method sequentially carries out intra-group and inter-group data fusion, effectively detecting and mitigating the influence of Byzantine nodes, leading to highly accurate position estimations. Finally, the Practical Byzantine Fault Tolerance (PBFT) algorithm ensures consensus on the positioning results across all nodes. Experimental validation and analysis demonstrate that the proposed approach significantly enhances the accuracy, robustness, and security of distributed localization in adversarial environments, offering a reliable solution for applications requiring high levels of trust and precision.