More Datasets

Experimental Study of Outdoor UAV Localization and Tracking Using Passive RF Sensing

2023
Other Experiments by the AERPAW Team
Non-Canonical Experiments
Passive RF Sensing, UAV Localization

Lead Experimenter

Udita Bhattacherjee, NC State University

Link to Dataset

Equipment and Software Used

Keysight RF Sensors, Keysight Geolocation Software, and commercial UAVs (this is a BYOD experiment)

Description

Commercial UAVs are flown with a random pattern. Four RF sensors capture the wireless signal passively from the drone, and the RF sensor network tracks the location of the drone using TDOA-based localization.

Publications

  1. U. Bhattacherjee, E. Ozturk, O. Ozdemir, I. Guvenc, M. L. Sichitiu, and H. Dai, "Experimental Study of Outdoor UAV Localization and Tracking using Passive RF Sensing", in Proc. ACM WiNTECH Workshop, Feb. 2022.

Representative Results

  • Result figures
    The images below show the experiment area in Dorothea Dix Park with 4 RF sensors and representative results for tracking the location of the drone.
    Screenshot 2023-04-11 at 23 10 06

Potential use cases for this dataset include:

  • Developing UAV Motion Models for UAV Tracking
  • Enhanced UAV Traffic Management
  • Search and Rescue Operations
  • Security and Surveillance