VISION-BASED RELATIVE POSITION ESTIMATION AND INTERCEPT TRAJECTORY PLANNING FOR SMALL UNMANNED AIRCRAFT SYSTEMS
Loading...
Authors
Tan, Kang Hao
Subjects
computer vision
object detection
object tracking
position estimation
navigation
trajectory
UAS
drone
object detection
object tracking
position estimation
navigation
trajectory
UAS
drone
Advisors
Yakimenko, Oleg A.
Date of Issue
2019-09
Date
Publisher
Monterey, CA; Naval Postgraduate School
Language
Abstract
The proliferation of unmanned aircraft systems (UAS) has contributed to the asymmetric threat of malevolent actors exploiting this technology for mischief or harm. Existing ground-based solutions are limited by line of sight, while human-operated responder drones can be less responsive and more labor-intensive. Hence, there is a capability requirement for autonomous vision-based pursuit and interception of unauthorized drones. To address this, the author developed a computer vision (CV) algorithm to detect, track and estimate the relative position and range of a hovering and moving airborne small UAS target in field conditions. CV-based measurements were compared against GPS data, to assess the range and angular estimation performance of the CV algorithm. Then, the CV-estimated range and angular information was processed by a flight control algorithm utilizing simple angular guidance principle to pursue and intercept the target. Field tests of the algorithm were done using a prototype drone. This research will inform the conceptual design and choice of hardware implementation for a commercial-off-the-shelf-based counter-UAS capability. More broadly, the research contributes to the body of knowledge in autonomous object tracking applications.
Type
Thesis
Description
Series/Report No
Department
Systems Engineering (SE)
Organization
Identifiers
NPS Report Number
Sponsors
Funder
Format
Citation
Distribution Statement
Approved for public release; distribution is unlimited.
Rights
Copyright is reserved by the copyright owner.