Detection and tracking of drones using advanced acoustic cameras

Abstract

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.

Empirical study of drone sound detection in real-life environment with deep neural networks

“…Our recorded drone sound indicated a noticeable harmonic shape below a frequency of 1500 Hz. In addition, we also observed a noticeable influence area on the spectrogram between 5000 Hz and 7000 Hz ( Figure 1) as was previously pointed out [1], [2]. However, these characteristics were not exhibited by all the drone models used in our experiments.…”

“…Existing work. Even though few studies have been concerned with the problem of drone sound detection, previous work was conducted in isolated or calm places rather than in a real-life environment without the polyphonic sound environment typical of outside areas, such as on the rooftop of a building in a calm place or isolated environment [1], [2], [3]. However, considering our target problem, which is to detect drones used for malicious purposes, the system inevitably needs to be utilized in a real-life environment, and this requires us to consider polyphonic sound data.…”

PiNcH: An effective, efficient, and robust solution to drone detection via network traffic analysis

“…Visual detection mainly relies on the distribution of camera equipment in the area to be protected and the implementation of video processing techniques to identify anomalies in the video stream [11]. Audio detection resorts to the generation of an audio signature of the drone propellers to be used to train a classifier [12]; such a technique further requires arrays of microphones to be deployed in the area to be monitored [13]. Conversely, radar detection involves the transmission of RF signals to receive an RF echo that can be identified and tracked [14].…”

Pixel-Level and Robust Vibration Source Sensing in High-Frame-Rate Video Analysis

“…For sound source localization, numerous acoustic-signal-processing methodologies have been proposed for applications such as robot auditory systems [61] and industrial applications [62]. Recently, several audio-signal-based drone surveillance systems have been developed [63,64,65,66], because the detection of illegal or abnormal objects is a growing concern following the recent popularization of flying drones. However, the localization accuracy of these acoustic methods remains limited, because of the low directivity in sound propagation.…”