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Drone Detection using Audio Analysis

Hauzenberger, Louise LU and Holmberg Ohlsson, Emma LU (2015) EITM01 20151
Department 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:
author
Hauzenberger, Louise LU and Holmberg Ohlsson, Emma LU
supervisor
organization
course
EITM01 20151
year
type
H2 - Master's Degree (Two Years)
subject
keywords
Audio analysis, drones, detection
report number
LU/LTH-EIT 2015-448
language
English
id
7362609
date added to LUP
2015-06-17 15:40:35
date last changed
2016-06-16 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},
}