Abstract

Unmanned aerial vehicles (UAV) are growing in popularity, and recent technological advances are fostering the development of new applications for these devices. This paper discusses the use of aerial drones as a platform for deploying a gunshot surveillance system based on an array of microphones. Notwithstanding the difficulties associated with the inherent additive noise from the rotating propellers, this application brings an important advantage: the possibility of estimating the shooter position solely based on the muzzle blast sound, with the support of a digital map of the terrain. This work focuses on direction-of-arrival (DoA) estimation methods applied to audio signals obtained from a microphone array aboard a flying drone. We investigate preprocessing and different DoA estimation techniques in order to obtain the setup that performs better for the application at hand. We use a combination of simulated and actual gunshot signals recorded using a microphone array mounted on a UAV. One of the key insights resulting from the field recordings is the importance of drone positioning, whereby all gunshots recorded in a region outside a cone open from the gun muzzle presented a hit rate close to 96%. Based on experimental results, we claim that reliable bearing estimates can be achieved using a microphone array mounted on a drone.

Highlights

  • The interest in automatic sniper localization systems traces back to the early 1990s, pioneered by countries such as the United States of America, Russia, Canada, France, and more recently, Israel, among others

  • We focus on the details of DoA estimation of gunshot signals obtained from a microphone array aboard a flying drone

  • Angular error can vary from 0◦, when there is no error in DoA estimation, up to 180◦, when DoA estimation points towards the opposite direction of actual DoA

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Summary

Introduction

The interest in automatic sniper localization systems traces back to the early 1990s, pioneered by countries such as the United States of America, Russia, Canada, France, and more recently, Israel, among others. One such system based on a microphone array mounted on an aerial drone brings additional advantages owing to its flexibility to cover wider areas relatively quicker and at a lower cost It opens the opportunity for new important applications, such as search-and-rescue missions [11,12] and environmental monitoring [9]. A novel algorithm to sound source location with UAV-embedded microphone arrays based on time-frequency bins was proposed in Reference [19] This method takes advantage of the fact that ego-noise and target sound (e.g., speech or emergency whistle) mainly consist of harmonic components that usually occupy different time-frequency bins.

DoA Estimation and Shooter Localization
Preprocessing
Gunshot Detection
DoA Estimation Methods
The Data Selection Least Squares DoA Estimation Algorithm
The MBSS Locate
Position Estimation
System Setup and Signal Acquisition
UAV and Avionics
Environmental Conditions and Shooting Site
Data Acquisition
Axis Rotation
Simulated Signals
Field Recordings
Discussion and Conclusions
Full Text
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