Published April 18, 2023 | Version v1

DDL: DATASET AND BASELINE METHODS FOR DRONE DETECTION AND LOCALIZATION USING SOUND

  • 1. University of Surrey
  • 2. DeepX Inc.
  • 3. Airspeed

Description

This dataset contains drone audio sound recorded in the field and also an artificially synthesized version which is rendered by the sound particle software. 

The audio files are placed in separate folders and the naming convention is described below:

For field recording the file name format is as follows:
Filename Indices:

0-12: UTC Timestamp - assumes UNIX epoch (i.e. "2022/01/01 00:00:00.000")

13-16: Sample class - indicating drone model (MINI for DJI Mini2, PRO4 for DJI Phantom Pro 4, and XXXX for no drone.)

17-19: Bearing to Target - ranged from 0-359 degrees with 1 deg increments.

20-22: Range to Target - Distance between microphone array and drone, 1m increments

23-25: Target Altitude - Altitude of the drone AGL, 1m increments

26-29: Ambient Temperature - In Kelvin degrees with 0.1 degrees increments

30: Sample type - Reserved symbols, "R" for real sample and "S" for synthesized sample

31-36: Flight Session ID - metadata

37-42: Recording session ID - metadata 

43-48: Sample Sequence ID, this can be used to merge samples within a recording session (if you would like to have 200ms or larger audio samples)

 

For artificially synthesized data the format is:

 

Files

MLSP_2022_Real_Data.zip

Files (17.3 GB)

Name Size
md5:4a6d4da4e1c732550c1ccd8d29dd16f8
12.6 GB Preview Download
md5:4e7a9b865f3e915aa7700f83e751aa5b
4.6 GB Preview Download