Abstract

With the growing utilization of unmanned aerial vehicles (UAVs), low-altitude airspace is becoming increasingly congested, posing significant challenges to Air Traffic Control (ATC). The Automatic Dependent Surveillance-Broadcast (ADS-B) system is used to report the location of UAVs. However, due to channel noise and adversarial interference, ADS-B data may be inaccurate. To address this issue, a position estimation method based on Bidirectional Long Short-Term Memory Multi-Layer Perceptron (BiLSTM-MLP) was proposed. In this method, ADS-B signal power is used to estimate the position of UAVs as a baseline approach. Experimental results demonstrate that the BiLSTM-MLP based method significantly improves estimation accuracy. Moreover, a blockchain-based dynamic reputation mechanism, aligned with the position estimation method, was proposed. The mechanism integrates information from the third-party UAV and the location data provided by the UAV itself to dynamically update the credibility of the UAV, and thus achieves decentralized access control of UAVs in low-altitude airspace.

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