PLA for Drone RID Frames via Motion Estimation and Consistency Verification

• URL: http://arxiv.org/abs/2602.23760v1
• Date: Fri, 27 Feb 2026 07:37:34 GMT
• Title: PLA for Drone RID Frames via Motion Estimation and Consistency Verification
• Authors: Jie Li, Jing Li, Lu Lv, Zhanyu Ju, Fengkui Gong,
• Abstract summary: Drone Remote Identification (RID) plays a critical role in low-altitude airspace supervision.<n>Lack of cryptographic protection makes it vulnerable to spoofing and replay attacks.<n>We propose a consistency verification-based physical-layer authentication (PLA) algorithm for drone RID frames.
• Score: 12.735651073414452
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Drone Remote Identification (RID) plays a critical role in low-altitude airspace supervision, yet its broadcast nature and lack of cryptographic protection make it vulnerable to spoofing and replay attacks. In this paper, we propose a consistency verification-based physical-layer authentication (PLA) algorithm for drone RID frames. A RID-aware sensing and decoding module is first developed to extract communication-derived sensing parameters, including angle-of-arrival, Doppler shift, average channel gain, and the number of transmit antennas, together with the identity and motion-related information decoded from previously authenticated RID frames. Rather than fusing all heterogeneous information into a single representation, different types of information are selectively utilized according to their physical relevance and reliability. Specifically, real-time wireless sensing parameter constraints and previously authenticated motion states are incorporated in a yaw-augmented constant-acceleration extended Kalman filter (CA-EKF) to estimate the three-dimensional position and motion states of the drone. To further enhance authentication reliability under highly maneuverable and non-stationary flight scenarios, a data-driven long short-term memory-based motion estimator is employed, and its predictions are adaptively combined with the CA-EKF via an error-aware fusion strategy. Finally, RID frames are authenticated by verifying consistency in the number of transmit antennas, motion estimates, and no-fly-zone constraints. Simulation results demonstrate that the proposed algorithm significantly improves authentication reliability and robustness under realistic wireless impairments and complex drone maneuvers, outperforming existing RF feature-based and motion model-based PLA schemes.

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