Show/Hide Menu
Hide/Show Apps
Logout
Türkçe
Türkçe
Search
Search
Login
Login
OpenMETU
OpenMETU
About
About
Open Science Policy
Open Science Policy
Open Access Guideline
Open Access Guideline
Postgraduate Thesis Guideline
Postgraduate Thesis Guideline
Communities & Collections
Communities & Collections
Help
Help
Frequently Asked Questions
Frequently Asked Questions
Guides
Guides
Thesis submission
Thesis submission
MS without thesis term project submission
MS without thesis term project submission
Publication submission with DOI
Publication submission with DOI
Publication submission
Publication submission
Supporting Information
Supporting Information
General Information
General Information
Copyright, Embargo and License
Copyright, Embargo and License
Contact us
Contact us
WAVELET-BASED ADAPTIVE ARRAY SIGNAL PROCESSING FOR GUNSHOT DETECTION AND DOA ESTIMATION ON UNMANNED AIR VEHICLES
Download
10579482.pdf
Date
2023-9-04
Author
Yılmaz, Murat
Metadata
Show full item record
This work is licensed under a
Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License
.
Item Usage Stats
118
views
0
downloads
Cite This
This study aims for detection and Direction of Arrival estimation of muzzle blast and shock wave components of gunshot sound onboard a drone, despite the excessive ego-noise of the vehicle. The method depends on using the whole array data, Array Correlation Map, for improved detection and adaptive usage of Continuous Wavelet Transform scales for tuning to transient events of varying frequency. Although studied specifically for the processing of gunshot sounds on drones, the three novelties this study offers may be generalized to other array processing applications. The first is that low signal-to-noise ratio can be remedied in a detection problem with the help of the directionality of the sound source as compared to the ego noise. This is achieved by introducing the “Array Correlation Map” of the microphone array and using it to emphasize the unanimity among the array sensors. Using a simple mean value of the correlation map revealed successful results for very low signal-to-noise-ratio muzzle and shock wave scenarios, although other geometries and array processing problems may use the correlation map differently. Secondly, the help of CWT analysis is maximized by a self-adaptive selection of CWT scales. Thirdly, the tune-like feature of scales-selection is presented, which is demonstrated by automatically focusing on either muzzle or shock wave scales/frequencies. Results reveal signal-to-noise-ratio enhancement, successful muzzle and shock wave signal detection, and DOA estimation performance improvement.
Subject Keywords
Acoustic event detection
,
Gunshot DOA estimation
,
Signal denoising
,
Wavelet-based signal processing
,
Array signal processing
,
Adaptive Denoising
URI
https://hdl.handle.net/11511/105446
Collections
Graduate School of Informatics, Thesis
Citation Formats
IEEE
ACM
APA
CHICAGO
MLA
BibTeX
M. Yılmaz, “WAVELET-BASED ADAPTIVE ARRAY SIGNAL PROCESSING FOR GUNSHOT DETECTION AND DOA ESTIMATION ON UNMANNED AIR VEHICLES,” Ph.D. - Doctoral Program, Middle East Technical University, 2023.