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Tracking drone orientation with multiple GPS receivers

Authors:

Justin Manweiler,

Ashutosh Dhekne,

Romit Roy Choudhury,

Justin D. WeiszAuthors Info & Claims

MobiCom '16: Proceedings of the 22nd Annual International Conference on Mobile Computing and Networking

Pages 280 - 293

https://doi.org/10.1145/2973750.2973768

Published: 03 October 2016 Publication History

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Abstract

Inertial sensors continuously track the 3D orientation of a flying drone, serving as the bedrock for maneuvers and stabilization. However, even the best inertial measurement units (IMU) are prone to various types of correlated failures. We consider using multiple GPS receivers on the drone as a fail-safe mechanism for IMU failures. The core challenge is in accurately computing the relative locations between each receiver pair, and translating these measurements into the drone's 3D orientation. Achieving IMU-like orientation requires the relative GPS distances to be accurate to a few centimeters -- a difficult task given that GPS today is only accurate to around 1-4 meters. Moreover, GPS-based orientation needs to be precise even under sharp drone maneuvers, GPS signal blockage, and sudden bouts of missing data. This paper designs SafetyNet, an off-the-shelf GPS-only system that addresses these challenges through a series of techniques, culminating in a novel particle filter framework running over multi-GNSS systems (GPS, GLONASS, and SBAS). Results from 11 sessions of 5-7 minute flights report median orientation accuracies of 2° even under overcast weather conditions. Of course, these improvements arise from an increase in cost due to the multiple GPS receivers, however, when safety is of interest, we believe that tradeoff is worthwhile.

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Index Terms

Tracking drone orientation with multiple GPS receivers
1. Computer systems organization
  1. Embedded and cyber-physical systems

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cover image ACM Other conferences

MobiCom '16: Proceedings of the 22nd Annual International Conference on Mobile Computing and Networking

October 2016

532 pages

ISBN:9781450342261

DOI:10.1145/2973750

General Chairs:
Yingying Chen
Stevens Institute of Technology
,
Marco Gruteser
Rutgers University
,
Program Chairs:
Y. Charlie Hu
Purdue University, USA
,
Karthik Sundaresan
NEC Labs Princeton, USA

Copyright © 2016 ACM.

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Published: 03 October 2016

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MobiCom'16: The 22nd Annual International Conference on Mobile Computing and Networking

October 3 - 7, 2016

New York, New York City

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MobiCom '16 Paper Acceptance Rate 31 of 226 submissions, 14%;

Overall Acceptance Rate 440 of 2,972 submissions, 15%

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https://dl.acm.org/doi/10.1145/3643832.3661881
Zhu YMiao CXue HYu YSu LQiao CGanesan DShi W(2024)Malicious Attacks against Multi-Sensor Fusion in Autonomous DrivingProceedings of the 30th Annual International Conference on Mobile Computing and Networking10.1145/3636534.3649372(436-451)Online publication date: 29-May-2024
https://dl.acm.org/doi/10.1145/3636534.3649372
Srisomboon ILee S(2024)Positioning and Navigation Approaches Using Packet Loss-Based Multilateration for UAVs in GPS-Denied EnvironmentsIEEE Access10.1109/ACCESS.2024.335714812(13355-13369)Online publication date: 2024
https://doi.org/10.1109/ACCESS.2024.3357148
Petrenko DKryvenchuk YYakovyna V(2023)Enhancing Data Discretization for Smoother Drone Input Using GAN-Based IMU Data AugmentationDrones10.3390/drones70704637:7(463)Online publication date: 11-Jul-2023
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