Citation

Shi Z, Chang X, Yang C, Wu Z, Wu J. IEEE Trans. Vehicular Tech. 2020; 69(3): 2731-2739.

Copyright

(Copyright © 2020, IEEE (Institute of Electrical and Electronics Engineers))

DOI

10.1109/TVT.2020.2964110

PMID

unavailable

Abstract

Due to cost reduction and device miniaturization, amateur drones are now widely used in numerous civilian and commercial applications. However, the abuse of amateur drones has resulted in emerging threats to personal privacy and public security. To alleviate these threats, we design an acoustic-based surveillance system, which can achieve the capacity of amateur drones detection and localization with 24/7 (24 hours per day and 7 days per week under normal circumstances) availability. In the designed system, a detection fusion algorithm and a TDOA estimation algorithm based on the Bayesian filter are applied to improve the performance of drone detection and localization. Field experiments are carried out, and the results demonstrate that the designed system can detect and locate an amateur drone in real time with high accuracy and 24/7 availability.

Language: en

Keywords

Acoustic arrays; acoustic-based surveillance system; Acoustics; amateur drones detection; amateur drones localization; Bayes methods; Bayesian filter; detection fusion; detection fusion algorithm; direction-of-arrival estimation; drone detection; drone localization; drone surveillance; Drones; Feature extraction; image filtering; image fusion; Microphones; mobile robots; Real-time systems; robot vision; SLAM (robots); surveillance; Surveillance; TDOA estimation; TDOA estimation algorithm; Time-frequency analysis; time-of-arrival estimation