TTCP AG-6: acoustic detection and tracking of UAVs

Pham, Tien; Srour, Nassy

doi:10.1117/12.548194

Cited by 39 publications

(13 citation statements)

References 5 publications

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“…To detect UAVs, acoustic features are extracted and classified. The rotor speed and the altitude can be estimated 7 and detection can be done even if the drone is out of sight. Current methods rely on a single or a limited number of sensors, 8 and basic direction of arrival (DOA) estimation algorithms, which prevent the precise and unambiguous detection and localization of the UAVs, especially if several UAVs are present at the same time.…”

Section: Introductionmentioning

confidence: 99%

Detection and tracking of drones using advanced acoustic cameras

Busset¹,

Perrodin²,

Wellig³

et al. 2015

SPIE Proceedings

100

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Recent events of drones flying over city centers, official buildings and nuclear installations stressed the growing threat of uncontrolled drone proliferation and the lack of real countermeasure. Indeed, detecting and tracking them can be difficult with traditional techniques. A system to acoustically detect and track small moving objects, such as drones or ground robots, using acoustic cameras is presented. The described sensor, is completely passive, and composed of a 120-element microphone array and a video camera. The acoustic imaging algorithm determines in real-time the sound power level coming from all directions, using the phase of the sound signals. A tracking algorithm is then able to follow the sound sources. Additionally, a beamforming algorithm selectively extracts the sound coming from each tracked sound source. This extracted sound signal can be used to identify sound signatures and determine the type of object. The described techniques can detect and track any object that produces noise (engines, propellers, tires, etc). It is a good complementary approach to more traditional techniques such as (i) optical and infrared cameras, for which the object may only represent few pixels and may be hidden by the blooming of a bright background, and (ii) radar or other echo-localization techniques, suffering from the weakness of the echo signal coming back to the sensor. The distance of detection depends on the type (frequency range) and volume of the noise emitted by the object, and on the background noise of the environment. Detection range and resilience to background noise were tested in both, laboratory environments and outdoor conditions. It was determined that drones can be tracked up to 160 to 250 meters, depending on their type. Speech extraction was also experimentally investigated: the speech signal of a person being 80 to 100 meters away can be captured with acceptable speech intelligibility.

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Section: Introductionmentioning

confidence: 99%

Detection and tracking of drones using advanced acoustic cameras

Busset¹,

Perrodin²,

Wellig³

et al. 2015

SPIE Proceedings

100

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show abstract

“…На основі цих явищ активно розробляються різноманітні засоби своєчасного виявлення БПЛА. Це і традиційні засоби радіолокації [4] та радіотехнічної розвідки [5], і давно забуті акустичні засоби [6], і оптико-електронні засоби та засоби розвідки в інфрачервоному діапазоні [7]. Але кожен з означених засобів уособлено не є і не може бути універсальним засобом виявлення таких своєрідних об'єктів, як БПЛА, через слабкість супроводжуючих їх явищ.…”

Section: вступunclassified

Потенційні Можливості РЛС РТВ З Виявлення Оперативно-Тактичних Та Тактичних Безпілотних Літальних Апаратів

Вишневський¹,

Бейліс²,

Klimchenko³

2017

НТПС

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“…There have been no reports of air-to-air detection and localization of another aircraft from either a fixed-wing or rotary-wing UAV. Work in this area has involved either the detection of airborne UAVs from stationary platforms such as ground-based microphone arrays or tethered aerial balloons [2,10,[13][14][15][16], simulating a UAV-based detection system [2,[17][18][19], detecting ground-based impulse sources from fixed-wing UAVs, [20,21], or localizing continuous ground-based sources from stationary low-altitude rotary-wing UAVs [22,23].…”

Section: Introductionmentioning

confidence: 99%

Acoustic Detection of a Fixed-Wing UAV

Harvey

O’Young

2018

Drones

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Abstract:The following paper presents results obtained from experiments conducted to investigate the viability of acoustic sensing to form the basis of a non-cooperative aircraft collision avoidance system. An unmanned aerial vehicle (UAV) fitted with two microphones was flown in the vicinity of another airborne UAV to determine the maximum distance at which the intruding aircraft could be detected. A two-dimensional analytical model to approximate the minimum detection distance required to facilitate an avoidance maneuver for a given spatial configuration is presented. A method to increase detection distances by exploiting the harmonic nature of acoustic signals generated by propeller-driven aircraft is also presented. The method significantly increases the detection distances compared to the commonly used incoherent spectral mean. It was found that a small gasoline-powered UAV could be detected at distances up to 678 m, which is more than double the minimum required to avoid a head-on collision.

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TTCP AG-6: acoustic detection and tracking of UAVs

Cited by 39 publications

References 5 publications

Detection and tracking of drones using advanced acoustic cameras

Detection and tracking of drones using advanced acoustic cameras

Потенційні Можливості РЛС РТВ З Виявлення Оперативно-Тактичних Та Тактичних Безпілотних Літальних Апаратів

Acoustic Detection of a Fixed-Wing UAV

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