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Extraction of UAV Sound from a Mixture of Different Sounds

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Abstract

With the rapid advancement of technology of unmanned aerial vehicles (UAVs), security and safety of military and civil infrastructure have been jeopardized. By exploiting the unreliable capabilities of radar to detect low-flying UAVs with small radar cross section, they can be utilized for malicious purposes, e.g., unauthorized surveillance. To detect UAVs, therefore, various other techniques including audio sniffing/analysis of environment have been investigated. It has been shown recently that a UAV can be differentiated from other sound generating objects based on the various features extracted from the sound captured by a single or multiple acoustic sensors. However, features extraction and classification process can only give reliable results if it is fed with a sound generated by a single source. In practice, the captured sound may be a mixture of contribution of two or more different sources. In this paper, we investigate a well-known blind source separation technique, known as projection pursuit, to separate the constituent sounds in a mixture. We have considered a scenario when the different mixed unvoiced sounds are independent and non-Gaussian. The results show that in the given scenario, projection pursuit can be applied successfully to separate UAV sounds from various other unvoiced sounds.

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Authors and Affiliations

  1. Department of Avionics Engineering, Air University, Islamabad, Islamic Republic of Pakistan

    Sana Hikmat Ghani

  2. Department of Electrical Engineering, Air University, Islamabad, Islamic Republic of Pakistan

    Waseem Khan

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  1. Sana Hikmat Ghani
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  2. Waseem Khan
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Correspondence to Waseem Khan.

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Ghani, S.H., Khan, W. Extraction of UAV Sound from a Mixture of Different Sounds. Acoust Aust 48, 363–373 (2020). https://doi.org/10.1007/s40857-020-00197-z

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