Euclidean distance based algorithm for UAV acoustic detection

Jang, Beomhui; Seo, Yoojeong; On, Baeksan; Im, Sungbin

doi:10.23919/elinfocom.2018.8330557

Cited by 6 publications

(3 citation statements)

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“…Comparison and analysis of the dependencies shown in Figs. 4-6 indicate multiple differences in 𝑇 𝑏 values of the background (sky) for the considered wave ranges, as well as the significant influence of weather conditions on these values. Moreover, the destructive manifestation concerning the influence of weather conditions is especially significant with a shortening of the wavelength, up to the disappearance of the angular dependence of 𝑇 𝑏 in the sky at 3 mm WR due to the saturation effect under intense rain conditions.…”

Section: Resultsmentioning

confidence: 99%

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Radio-Heat Contrasts of UAVs and Their Weather Variability at 12 GHz, 20 GHz, 34 GHz, and 94 GHz Frequencies

et al. 2022

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This work describes the procedure for determining the expected values of UAV radio-heat contrasts () and discusses its angular dependences, as well as the estimation of UAV detection distances at four points cm and mm ranges (12 GHz, 20 GHz, 34 GHz, and 94 GHz). This paper reveals the pronounced frequency dependence on brightness temperature () and of a fiberglass unmanned aerial vehicle (UAV) made from composite fiberglass materials. The quantified experiments are conducted against a sky background under various weather conditions and wave ranges. The qualitative physical interpretation of these properties and their frequency dependence is proposed, reflecting the coefficient values and radio brightness of the background. The weak influence of weather on the observed UAVs in the X and Ku bands are demonstrated along with the multiple decreasing detection characteristics and advantages of the W band under bad weather conditions (the appearance of rain or thick cloud). This work presents data on the values of UAV contrasts, observed against the background of the sky and the regularities noted could be useful for predicting the effectiveness of the proposed radiometric detection and tracking system.

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Section: Resultsmentioning

confidence: 99%

“…The search for appropriate methods for developing airspace control devices is traditionally based on the use of acoustic, optical, infrared, and radar methods for active and passive monitoring [1][2][3][4][5][6][7][8][9][10][11][12][13]. Each of these methods has its own advantages and disadvantages [14][15][16][17][18][19][20].…”

Section: Introductionmentioning

confidence: 99%

Radio-Heat Contrasts of UAVs and Their Weather Variability at 12 GHz, 20 GHz, 34 GHz, and 94 GHz Frequencies

et al. 2022

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“…Jang, B. et al applied the euclidean distance and Scale-Invariant Feature Transform (SIFT) to distinguish the UAV engine sound from the background sound and demonstrated their effectiveness, even though the power spectrum of the noise is larger than that of the UAS sound. However, in practice, their processing efficiency is poor [33].…”

Section: A Acoustic Based Uas Detectionmentioning

confidence: 99%

Counter-Unmanned Aircraft System(s) (C-UAS): State of the Art, Challenges and Future Trends

Wang,

Liu,

Song

2020

Preprint

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Unmanned aircraft systems (UAS), or unmanned aerial vehicles (UAVs), often referred to as drones, have been experiencing healthy growth in the United States and around the world. The positive uses of UAS have the potential to save lives, increase safety and efficiency, and enable more effective science and engineering research. However, UAS are subject to threats stemming from increasing reliance on computer and communication technologies, which place public safety, national security, and individual privacy at risk. To promote safe, secure and privacyrespecting UAS operations, there is an urgent need for innovative technologies for detecting, tracking, identifying and mitigating UAS. A Counter-UAS (C-UAS) system is defined as a system or device capable of lawfully and safely disabling, disrupting, or seizing control of an unmanned aircraft or unmanned aircraft system. Over the past 5 years, significant research efforts have been made to detect, and mitigate UAS: detection technologies are based on acoustic, vision, passive radio frequency, radar, and data fusion; and mitigation technologies include physical capture or jamming. In this paper, we provide a comprehensive survey of existing literature in the area of C-UAS, identify the challenges in countering unauthorized or unsafe UAS, and evaluate the trends of detection and mitigation for protecting against UASbased threats. The objective of this survey paper is to present a systematic introduction of C-UAS technologies, thus fostering a research community committed to the safe integration of UAS into the airspace system.

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