mmE-Loc: Facilitating Accurate Drone Landing With Ultra-High-Frequency Localization

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Authors: Haoyang Wang, Jingao Xu, Xinyu Luo, Ting Zhang, Xuecheng Chen, Ruiyang Duan, Y. Liu, Jianfeng Zheng, Weijie Hong, Xiaoqiang Ji, Yuqing Tang, Xinlei Chen
Cited by: 3
References: 59

Abstract

For precise, efficient, and safe drone landings, ground platforms should real-time, accurately locate descending drones and guide them to designated spots. While mmWave sensing combined with cameras improves localization accuracy, lower sampling frequency of traditional frame cameras compared to mmWave radar creates bottlenecks in system throughput. In this work, we upgrade traditional frame camera with event camera, a novel sensor that harmonizes in sampling frequency with mmWave radar within ground platform setup, and introduce mmE-Loc, a high-precision, low-latency ground localization system designed for precise drone landings. To fully exploit thetemporal consistencyandspatial complementaritybetween these two modalities, we propose two innovative modules:(i)the Consistency-instructed Collaborative Tracking module, which further leverages the drone's physical knowledge of periodic micro-motions and structure for accurate measurements extraction, and(ii)the Graph-informed Adaptive Joint Optimization module, which integrates drone motion information for efficient sensor fusion and drone localization. Extensive experiments (30+ hours) demonstrate that mmE-Loc attains 0.083$m$localization accuracy and 5.12$ms$end-to-end latency, outperforming four state-of-the-art methods by over 48% and 62%, respectively.

Fields of Study & Subjects

UAV Applications and Optimization Robotics and Sensor-Based Localization Indoor and Outdoor Localization Technologies

Publication details

Journal / source
IEEE Transactions on Mobile Computing
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Volume
25
Issue
7
Pages
10651–10669
Publication date
19 February 2026