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MicNest: Long-Range Instant Acoustic Localization of Drones in Precise Landing

Published: 24 January 2023 Publication History

Abstract

We present MicNest: an acoustic localization system enabling precise landing of aerial drones. Drone landing is a crucial step in a drone's operation, especially as high-bandwidth wireless networks, such as 5G, enable beyond-line-of-sight operation in a shared airspace and applications such as instant asset delivery with drones gain traction. In MicNest, multiple microphones are deployed on a landing platform in carefully devised configurations. The drone carries a speaker transmitting purposefully-designed acoustic pulses. The drone may be localized as long as the pulses are correctly detected. Doing so is challenging: i) because of limited transmission power, propagation attenuation, background noise, and propeller interference, the Signal-to-Noise Ratio (SNR) of received pulses is intrinsically low; ii) the pulses experience non-linear Doppler distortion due to the physical drone dynamics while airborne; iii) as location information is to be used during landing, the processing latency must be reduced to effectively feed the flight control loop. To tackle these issues, we design a novel pulse detector, Matched Filter Tree (MFT), whose idea is to convert pulse detection to a tree search problem. We further present three practical methods to accelerate tree search jointly. Our real-world experiments show that MicNest is able to localize a drone 120 m away with 0.53% relative localization error at 20 Hz location update frequency.

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Information

Published In

cover image ACM Conferences
SenSys '22: Proceedings of the 20th ACM Conference on Embedded Networked Sensor Systems
November 2022
1280 pages
ISBN:9781450398862
DOI:10.1145/3560905
This work is licensed under a Creative Commons Attribution International 4.0 License.

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Publication History

Published: 24 January 2023

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Author Tags

  1. acoustic localization
  2. drone
  3. microphone array

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  • Research-article

Funding Sources

  • Swedish Science Foundation (SSF)
  • National Science Fund of China
  • Tsinghua University - Meituan Joint Institute for Digital Life
  • Swedish Research Council
  • Digital Futures programme (project Drone Arena)
  • KAW project UPDATE

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SenSys '22 Paper Acceptance Rate 52 of 187 submissions, 28%;
Overall Acceptance Rate 198 of 990 submissions, 20%

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  • (2024)SkyOrbs: A Fast 3-D Directional Neighbor Discovery Algorithm for UAV NetworksIEEE Transactions on Mobile Computing10.1109/TMC.2024.345199123:12(14768-14786)Online publication date: Dec-2024
  • (2024)Indoor Drone Localization and Tracking Based on Acoustic Inertial MeasurementIEEE Transactions on Mobile Computing10.1109/TMC.2023.333586023:6(7537-7551)Online publication date: Jun-2024
  • (2024)Acoustic Localization System for Precise Drone LandingIEEE Transactions on Mobile Computing10.1109/TMC.2023.328829923:5(4126-4144)Online publication date: May-2024
  • (2024)Indoor Drone 3-D Tracking Using Reflected Light From Floor SurfacesIEEE Journal of Indoor and Seamless Positioning and Navigation10.1109/JISPIN.2024.34537752(251-262)Online publication date: 2024
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