Accession Number:

ADA607559

Title:

Localization with Sparse Acoustic Sensor Network Using UAVs as Information-Seeking Data Mules

Descriptive Note:

Journal article

Corporate Author:

CALIFORNIA UNIV SANTA BARBARA DEPT OF ELECTRICAL AND COMPUTER ENGINEERING

Report Date:

2013-05-01

Pagination or Media Count:

32.0

Abstract:

We propose and demonstrate a novel architecture for on-the-fly inference while collecting data from sparse sensor networks. In particular, we consider source localization using acoustic sensors dispersed over a large area, with the individual sensors located too far apart for direct connectivity. An Unmanned Aerial Vehicle UAV is employed for collecting sensor data, with the UAV route adaptively adjusted based on data from sensors already visited, in order to minimize the time to localize events of interest. The UAV therefore acts as a information-seeking data mule, not only providing connectivity, but also making Bayesian inferences from the data gathered in order to guide its future actions. The system we demonstrate has a modular architecture, comprising efficient algorithms for acoustic signal processing, routing the UAV to the sensors, and source localization.We report on extensive field tests which not only demonstrate the effectiveness of our general approach, but also yield specific practical insights into GPS time synchronization and localization accuracy, acoustic signal and channel characteristics, and the effects of environmental phenomena.

Subject Categories:

  • Pilotless Aircraft
  • Information Science
  • Miscellaneous Detection and Detectors

Distribution Statement:

APPROVED FOR PUBLIC RELEASE