Improved DoA estimation with application to bearings-only acoustic source localization

Ribeiro, Juliano G. C.; Serrenho, Felipe G.; Apolinario, J.A.; Ramos, Antônio L. L.

doi:10.1109/isspit.2017.8388624

“…( 29). As in [8] and [27], the Newton-Raphson method is used here. We define vector v, with unknown variables, as v = x⊺ λ⊺ ⊺ , where λ = λ1 .…”

Section: Nonlinearly Constrained Least Squarementioning

confidence: 99%

Consistent Volumetric Search for Accurate Passive Coherent Location

RODRIGUEZ¹,

Martins²,

Apolinario³

et al. 2023

Preprint

0

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<p>This paper addresses the problem of selecting suitable time difference of arrival (TDOA) measurements for passive coherent location with multiple-transmitters/receivers. Firstly, we propose a unified mathematical framework for the following target location algorithms: spherical interpolation (SI), spherical intersection (SX), and nonlinearly constrained least squares (NLCLS). This paper generalizes the currently available models for scenarios with multiple-transmitters/one-receiver and one-transmitter/multiple-receivers. The SI/SX algorithms use closed-form expressions to tackle the location problem without considering all the nonlinear relationships among the optimization variables. As for the NLCLS algorithm, such nonlinearities are taken into account with the help of nonlinear constraints. Effects like multipath propagation and shadow fading increase TDOA measurement values resulting in outliers. To remove the outliers, we propose three TDOA selection processes. The first one uses a simple comparison rule. The second approach iteratively detects outliers based on cost function comparisons. The last approach divides the search region into cuboids. The cuboid-based approach separates consistent TDOAs from outliers, and its centroid represents a new location estimate. The numerical experiments show that the proposed cuboid-based method has greater robustness when increasing the probability of outliers.</p>

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“…( 29). As in [8] and [27], the Newton-Raphson method is used here. We define vector v, with unknown variables, as v = x⊺ λ⊺ ⊺ , where λ = λ1 .…”

Section: Nonlinearly Constrained Least Squarementioning

confidence: 99%

TDOA Data Selection for Accurate Passive Coherent Location

RODRIGUEZ¹,

Martins²,

Apolinario³

et al. 2022

Preprint

1

0

View full text Add to dashboard Cite

<p>This paper addresses the problem of selecting suitable time difference of arrival (TDOA) measurements for passive coherent location with multiple-transmitters/receivers. Firstly, we propose a unified mathematical framework for the following target location algorithms: spherical interpolation (SI), spherical intersection (SX), and nonlinearly constrained least squares (NLCLS). This paper generalizes the currently available models for scenarios with multiple-transmitters/one-receiver and one-transmitter/multiple-receivers. The SI/SX algorithms use closed-form expressions to tackle the location problem without considering all the nonlinear relationships among the optimization variables. As for the NLCLS algorithm, such nonlinearities are taken into account with the help of nonlinear constraints. Effects like multipath propagation and shadow fading increase TDOA measurement values resulting in outliers. To remove the outliers, we propose three TDOA selection processes. The first one uses a simple comparison rule. The second approach iteratively detects outliers based on cost function comparisons. The last approach divides the search region into cuboids. The cuboid-based approach separates consistent TDOAs from outliers, and its centroid represents a new location estimate. The numerical experiments show that the proposed cuboid-based method has greater robustness when increasing the probability of outliers.</p>

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“…Using the Exhaustive Search algorithm ES( n ) [7], we choose the n combination from the set of N pairs of microphones that minimizes the cost function ξ in Equation (12). We need to be cautious when choosing the number of pairs of microphones to be used, parameter “ n ” in ES( n ), once it can generate ill-conditioned matrices [55]. The appropriate choice for “ n ” can be obtained according to a decision tree as done in Reference [6].…”

Section: Doa Estimation and Shooter Localizationmentioning

confidence: 99%

Gunshot Airborne Surveillance with Rotary Wing UAV-Embedded Microphone Array

Serrenho

¹

,

Apolinario

²

,

Ramos

³

et al. 2019

Sensors

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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.

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Improved DoA estimation with application to bearings-only acoustic source localization

Cited by 5 publications

References 16 publications

Consistent Volumetric Search for Accurate Passive Coherent Location

Consistent Volumetric Search for Accurate Passive Coherent Location

TDOA Data Selection for Accurate Passive Coherent Location

Gunshot Airborne Surveillance with Rotary Wing UAV-Embedded Microphone Array

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