Robust TOA-based Localization with Inaccurate Anchors for MANET
Xinkai Yu, Yang Zheng, Min Sheng, Yan Shi, Jiandong Li
TL;DR
This work tackles accurate localization in GPS-denied MANETs with inaccurate anchors by deriving the CRLB for cascading TOA localization and proposing a two-step, CRLB-based TOA algorithm that relies on local neighbor information. It introduces a dynamic-anchor refinement process using Iterative Chan-PSO (iChan-PSO) and mobility-aware refinements to stabilize estimates in higher-level nodes, improving robustness in multi-hop cascaded localization. Across simulations, the method approaches CRLB accuracy for small ranging errors and remains resilient under larger errors and high mobility, outperforming SDP and conventional PSO-based TOA methods. The approach offers practical benefits for secure, infrastructure-free localization in dynamic MANET deployments.
Abstract
Accurate node localization is vital for mobile ad hoc networks (MANETs). Current methods like Time of Arrival (TOA) can estimate node positions using imprecise baseplates and achieve the Cramér-Rao lower bound (CRLB) accuracy. In multi-hop MANETs, some nodes lack direct links to base anchors, depending on neighbor nodes as dynamic anchors for chain localization. However, the dynamic nature of MANETs challenges TOA's robustness due to the availability and accuracy of base anchors, coupled with ranging errors. To address the issue of cascading positioning error divergence, we first derive the CRLB for any primary node in MANETs as a metric to tackle localization error in cascading scenarios. Second, we propose an advanced two-step TOA method based on CRLB which is able to approximate target node's CRLB with only local neighbor information. Finally, simulation results confirm the robustness of our algorithm, achieving CRLB-level accuracy for small ranging errors and maintaining precision for larger errors compared to existing TOA methods.