Feature Extracted DOA Estimation Algorithm Using Acoustic Array for Drone Surveillance

The wide proliferation of drones has posed great threats to personal privacy and public security, which makes it urgent to monitor and locate intruding drones in sensitive areas. In Direction of Arrival (DOA) based localization, the estimation accuracy of DOA directly affects the localization accuracy. In this paper, we propose a novel algorithm to estimate the DOA of an intruding drone by exploiting its acoustic feature, which is mainly reflected in the strength distribution of the harmonics of the received acoustic signal. Specifically, this algorithm first estimates the harmonic frequencies of the drone's acoustic signal in frequency domain. Then, multiple signal classification is used to estimate the DOAs of all the selected harmonics. Furthermore, weighted sum of these DOA estimates will be taken as the drone's DOA estimate, where the weights are in proportional to the energy of the corresponding harmonics. The performance of the proposed algorithm is verified by both simulation and field experiments.

[1]  M. Morf,et al.  The signal subspace approach for multiple wide-band emitter location , 1983 .

[2]  Thomas Kailath,et al.  ESPRIT-A subspace rotation approach to estimation of parameters of cisoids in noise , 1986, IEEE Trans. Acoust. Speech Signal Process..

[3]  M. Viberg,et al.  Two decades of array signal processing research: the parametric approach , 1996, IEEE Signal Process. Mag..

[4]  Surendra Prasad,et al.  DOA estimation of wideband sources using a harmonic source model and uniform linear array , 1999, IEEE Trans. Signal Process..

[5]  Alexander Sutin,et al.  Feature extraction for acoustic classification of small aircraft , 2015, 2015 IEEE Workshop on Applications of Signal Processing to Audio and Acoustics (WASPAA).

[6]  Alexander Sutin,et al.  Acoustic system for Low Flying Aircraft detection , 2015, 2015 IEEE International Symposium on Technologies for Homeland Security (HST).

[7]  Jesper Rindom Jensen,et al.  Computationally Efficient and Noise Robust DOA and Pitch Estimation , 2016, IEEE/ACM Transactions on Audio, Speech, and Language Processing.

[8]  Alastair H. Moore,et al.  Direction of Arrival Estimation in the Spherical Harmonic Domain using Subspace Pseudo-Intensity Vectors , 2016 .

[9]  Alexander Sutin,et al.  Passive acoustic system for tracking low-flying aircraft , 2016 .

[10]  Yu-Hen Hu,et al.  Estimation of low-altitude moving target trajectory using single acoustic array. , 2016, Journal of the Acoustical Society of America.

[11]  Martin Laurenzis,et al.  Optical and acoustical UAV detection , 2016, Security + Defence.

[12]  Andreas Jakobsson,et al.  Sparse Localization of Harmonic Audio Sources , 2016, IEEE/ACM Transactions on Audio, Speech, and Language Processing.

[13]  Jiming Chen,et al.  Robust Localization Using Time Difference of Arrivals , 2016, IEEE Signal Processing Letters.

[14]  József Mezei,et al.  Drone sound detection by correlation , 2016, 2016 IEEE 11th International Symposium on Applied Computational Intelligence and Informatics (SACI).

[15]  Jiming Chen,et al.  Robust Localization Using Range Measurements With Unknown and Bounded Errors , 2017, IEEE Transactions on Wireless Communications.

[16]  Fengzhong Qu,et al.  Source Estimation Using Coprime Array: A Sparse Reconstruction Perspective , 2017, IEEE Sensors Journal.

[17]  Guang Yang,et al.  Promoting Cooperation by the Social Incentive Mechanism in Mobile Crowdsensing , 2017, IEEE Communications Magazine.

[18]  Alastair H. Moore,et al.  Direction of Arrival Estimation in the Spherical Harmonic Domain Using Subspace Pseudointensity Vectors , 2017, IEEE/ACM Transactions on Audio, Speech, and Language Processing.

[19]  Jiming Chen,et al.  Anti-Drone System with Multiple Surveillance Technologies: Architecture, Implementation, and Challenges , 2018, IEEE Communications Magazine.