A Reduced Complexity Acoustic-Based 3D DoA Estimation with Zero Cyclic Sum

被引:0
作者
Fernandes, Rigel Procopio [1 ]
Apolinario, Jose Antonio [1 ,2 ]
de Seixas, Jose Manoel [3 ]
机构
[1] Mil Inst Engn IME, Program Def Engn, BR-22290270 Rio de Janeiro, Brazil
[2] Mil Inst Engn IME, Dept Elect Engn, BR-22290270 Rio de Janeiro, Brazil
[3] Fed Univ Rio de Janeiro UFRJ, Technol Ctr, Signal Proc Lab, COPPE POLI, BR-21941914 Rio de Janeiro, Brazil
关键词
DoA estimation; time delay estimation; zero cyclic sum; LOCALIZATION; VECTOR;
D O I
10.3390/s24072344
中图分类号
O65 [分析化学];
学科分类号
070302 ; 081704 ;
摘要
Accurate direction of arrival (DoA) estimation is paramount in various fields, from surveillance and security to spatial audio processing. This work introduces an innovative approach that refines the DoA estimation process and demonstrates its applicability in diverse and critical domains. We propose a two-stage method that capitalizes on the often-overlooked secondary peaks of the cross-correlation function by introducing a reduced complexity DoA estimation method. In the first stage, a low complexity cost function based on the zero cyclic sum (ZCS) condition is used to allow for an exhaustive search of all combinations of time delays between pairs of microphones, including primary peak and secondary peaks of each cross-correlation. For the second stage, only a subset of the time delay combinations with the lowest ZCS cost function need to be tested using a least-squares (LS) solution, which requires more computational effort. To showcase the versatility and effectiveness of our method, we apply it to the challenging acoustic-based drone DoA estimation scenario using an array of four microphones. Through rigorous experimentation with simulated and actual data, our research underscores the potential of our proposed DoA estimation method as an alternative for handling complex acoustic scenarios. The ZCS method demonstrates an accuracy of 89.4%+/- 2.7%, whereas the ZCS with the LS method exhibits a notably higher accuracy of 94.0%+/- 3.1%, showcasing the superior performance of the latter.
引用
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页数:21
相关论文
共 48 条
[1]   A Review of the State of the Art and Future Challenges of Deep Learning-Based Beamforming [J].
Al Kassir, Haya ;
Zaharis, Zaharias D. ;
Lazaridis, Pavlos, I ;
Kantartzis, Nikolaos, V ;
Yioultsis, Traianos, V ;
Xenos, Thomas D. .
IEEE ACCESS, 2022, 10 :80869-80882
[2]  
Borzino AMCR, 2015, INT CONF ACOUST SPEE, P449, DOI 10.1109/ICASSP.2015.7178009
[3]   Estimating Signal-to-Noise Ratio (SNR) [J].
Bosworth, Barry T. ;
Bernecky, W. Robert ;
Nickila, James D. ;
Adal, Berhane ;
Carter, G. Clifford .
IEEE JOURNAL OF OCEANIC ENGINEERING, 2008, 33 (04) :414-418
[4]   TDOA ESTIMATION OF SPEECH SOURCE IN NOISY REVERBERANT ENVIRONMENTS [J].
Bu, Suliang ;
Zhao, Tuo ;
Zhao, Yunxin .
2022 IEEE SPOKEN LANGUAGE TECHNOLOGY WORKSHOP, SLT, 2022, :1059-1066
[5]   Consistent DOA estimation of heavily noisy gunshot signals using a microphone array [J].
Cardoso Ribeiro Borzino, Angelo Marcio ;
Apolinario, Jose Antonio, Jr. ;
Rodrigues de Campos, Marcello Luiz .
IET RADAR SONAR AND NAVIGATION, 2016, 10 (09) :1519-1527
[6]  
Chakrabarty S, 2017, IEEE WORK APPL SIG, P136, DOI 10.1109/WASPAA.2017.8170010
[7]   Acoustic beamforming for noise source localization - Reviews, methodology and applications [J].
Chiariotti, Paolo ;
Martarelli, Milena ;
Castellini, Paolo .
MECHANICAL SYSTEMS AND SIGNAL PROCESSING, 2019, 120 :422-448
[8]  
Chinthamu N., 2023, J. Data Sci. Intell. Syst., V1, P83
[9]   Approximate Closed-Form TDOA-Based Estimator for Acoustic Direction Finding via Constrained Optimization [J].
Cui, Xunxue ;
Yu, Kegen ;
Lu, Songsheng .
IEEE SENSORS JOURNAL, 2018, 18 (08) :3360-3371
[10]  
Daniel J, 2020, INT CONF ACOUST SPEE, P421, DOI [10.1109/ICASSP40776.2020.9054561, 10.1109/icassp40776.2020.9054561]