Paper

{
  "raw_xml": "<entry>\n    <id>http://arxiv.org/abs/2602.23760v1</id>\n    <title>PLA for Drone RID Frames via Motion Estimation and Consistency Verification</title>\n    <updated>2026-02-27T07:37:34Z</updated>\n    <link href='https://arxiv.org/abs/2602.23760v1' rel='alternate' type='text/html'/>\n    <link href='https://arxiv.org/pdf/2602.23760v1' rel='related' title='pdf' type='application/pdf'/>\n    <summary>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.</summary>\n    <category scheme='http://arxiv.org/schemas/atom' term='cs.CR'/>\n    <published>2026-02-27T07:37:34Z</published>\n    <arxiv:primary_category term='cs.CR'/>\n    <author>\n      <name>Jie Li</name>\n    </author>\n    <author>\n      <name>Jing Li</name>\n    </author>\n    <author>\n      <name>Lu Lv</name>\n    </author>\n    <author>\n      <name>Zhanyu Ju</name>\n    </author>\n    <author>\n      <name>Fengkui Gong</name>\n    </author>\n  </entry>"
}