Drone Detection using Audio Analysis
(2015) EITM01 20151Department of Electrical and Information Technology
 Abstract
 Drones used for illegal purposes is a growing problem and a way to detect these is needed. This thesis has evaluated the possibility of using sound analysis as the detection mechanism. A solution using linear predictive coding, the slope of the frequency spectrum and the zero crossing rate was evaluated. The results showed that a solution using linear predictive coding and the slope of the frequency spectrum give a good result for the distance it is calibrated for. The zero crossing rate on the other hand does not improve the result and was not part of the final solution. The amount of false positives increases when calibrating for longer distances, and a compromise between detecting drones at long distances and the number of false... (More)
 Drones used for illegal purposes is a growing problem and a way to detect these is needed. This thesis has evaluated the possibility of using sound analysis as the detection mechanism. A solution using linear predictive coding, the slope of the frequency spectrum and the zero crossing rate was evaluated. The results showed that a solution using linear predictive coding and the slope of the frequency spectrum give a good result for the distance it is calibrated for. The zero crossing rate on the other hand does not improve the result and was not part of the final solution. The amount of false positives increases when calibrating for longer distances, and a compromise between detecting drones at long distances and the number of false positives need to be made in the implemented solution. It was concluded that drone detection using audio analysis is possible, and that the implemented solution, with linear predictive coding and slope of the frequency spectrum, could with further improvements become a useable product. (Less)
Please use this url to cite or link to this publication:
http://lup.lub.lu.se/studentpapers/record/7362609
 author
 Hauzenberger, Louise ^{LU} and Holmberg Ohlsson, Emma ^{LU}
 supervisor

 Mikael Swartling ^{LU}
 organization
 course
 EITM01 20151
 year
 2015
 type
 H2  Master's Degree (Two Years)
 subject
 keywords
 Audio analysis, drones, detection
 report number
 LU/LTHEIT 2015448
 language
 English
 id
 7362609
 date added to LUP
 20150617 15:40:35
 date last changed
 20160616 04:07:29
@misc{7362609, abstract = {Drones used for illegal purposes is a growing problem and a way to detect these is needed. This thesis has evaluated the possibility of using sound analysis as the detection mechanism. A solution using linear predictive coding, the slope of the frequency spectrum and the zero crossing rate was evaluated. The results showed that a solution using linear predictive coding and the slope of the frequency spectrum give a good result for the distance it is calibrated for. The zero crossing rate on the other hand does not improve the result and was not part of the final solution. The amount of false positives increases when calibrating for longer distances, and a compromise between detecting drones at long distances and the number of false positives need to be made in the implemented solution. It was concluded that drone detection using audio analysis is possible, and that the implemented solution, with linear predictive coding and slope of the frequency spectrum, could with further improvements become a useable product.}, author = {Hauzenberger, Louise and Holmberg Ohlsson, Emma}, keyword = {Audio analysis,drones,detection}, language = {eng}, note = {Student Paper}, title = {Drone Detection using Audio Analysis}, year = {2015}, }