Classification, positioning, and tracking of drones by HMM using acoustic circular microphone array beamforming is a research paper that addresses issues with identifying and tracking drones.
The paper proposes an acoustic-based method of positioning and tracking drones that include three main focal points:
-Scan the sky with switched beamforming to find sound sources;
– perform classification with a hidden Markov model (HMM); and
– if the sound source is a drone, use the recorded sound as a reference signal for tracking based on adaptive beamforming.
Publication Date- 2020
Classification, positioning, and tracking of drones by HMM using acoustic circular microphone array beamforming contains the following major sections:
- System methodology for acoustic signal-based positioning of illegal drones
- Proposed acoustic signal-based methodology for drone positioning
- Experiments and performance evaluation of the proposed acoustic signal-based methodology for drone positioning
Open Access Paper. This article is distributed under the terms of the Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.
cuashub.com does not own this content and is providing a link for users to access the content in its original location. This provides the author(s) with the opportunity to track important article metrics related to their work. All credit goes to its rightful owner.
Authors- Junfeng Guo, Ishtiaq Ahmad, and KyungHi Chang