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Acoustic Localization System for Precise Drone Landing
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DOI：10.1109/TMC.2023.3288299.png)
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摘要
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We present MicNest: an acoustic localization system enabling precise drone landing. 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; iii) as location information is 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 experiments show that MicNest can localize a drone 120 m away with 0.53% relative localization error at 20 Hz location update frequency. For navigating drone landing, MicNest can achieve a success rate of 94%. The average landing error (distance between landing point and target point) is only 4.3 cm.
Keyword:
Drones
Location awareness
Cameras
Acoustic pulses
Visualization
Mobile computing
Aerospace control
Localization
acoustic
microphone array
drone
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