Imperial College London

DrAlastairMoore

Faculty of EngineeringDepartment of Electrical and Electronic Engineering

Research Associate
 
 
 
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Contact

 

alastair.h.moore

 
 
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Location

 

809Electrical EngineeringSouth Kensington Campus

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Summary

 

Publications

Citation

BibTex format

@inproceedings{2018:10.1109/SAM.2018.8448889,
doi = {10.1109/SAM.2018.8448889},
pages = {395--399},
title = {Robust source counting and acoustic DOA estimation using density-based clustering},
url = {http://dx.doi.org/10.1109/SAM.2018.8448889},
year = {2018}
}

RIS format (EndNote, RefMan)

TY  - CPAPER
AB - ©2018 IEEE. Direction-of-Arrival (DOA) estimation for multiple simultaneously active acoustic sources without knowledge of the number of sources and the noise level remains a challenging task.A method of source counting for DOA estimation using density-based clustering is proposed. Multiple Density-based Spatial Clustering of Applications with Noise (DBSCAN) with varying noise sensitivity is applied in an evolutionary procedure to obtain weighted centroids.An autonomous DB-SCAN is finally run on the weighted centroids to extract the final DOA estimates. The results using generated and estimated DOAs show that the proposed technique significantly outperforms the conventional histogram peak picking as well as the original DBSCAN and variations of Kmeans with ≤4°DOA estimation accuracy and improves the source counting.
DO - 10.1109/SAM.2018.8448889
EP - 399
PY - 2018///
SP - 395
TI - Robust source counting and acoustic DOA estimation using density-based clustering
UR - http://dx.doi.org/10.1109/SAM.2018.8448889
ER -