Bearings-only aerial shooter localization using a microphone array mounted on a drone

Accurate direction of arrival (DoA) estimation is paramount in various fields, from surveillance and security to spatial audio processing. This work introduces an innovative approach that refines the DoA estimation process and demonstrates its applicability in diverse and critical domains. We propose a two-stage method that capitalizes on the often-overlooked secondary peaks of the cross-correlation function by introducing a reduced complexity DoA estimation method. In the first stage, a low complexity cost function based on the zero cyclic sum (ZCS) condition is used to allow for an exhaustive search of all combinations of time delays between pairs of microphones, including primary peak and secondary peaks of each cross-correlation. For the second stage, only a subset of the time delay combinations with the lowest ZCS cost function need to be tested using a least-squares (LS) solution, which requires more computational effort. To showcase the versatility and effectiveness of our method, we apply it to the challenging acoustic-based drone DoA estimation scenario using an array of four microphones. Through rigorous experimentation with simulated and actual data, our research underscores the potential of our proposed DoA estimation method as an alternative for handling complex acoustic scenarios. The ZCS method demonstrates an accuracy of 89.4%±2.7%, whereas the ZCS with the LS method exhibits a notably higher accuracy of 94.0%±3.1%, showcasing the superior performance of the latter.

Section: Time-delay Estimation Approachesmentioning

confidence: 98%

“…The proposed scheme is evaluated using experimental data from both simulated and recorded gunshot signals. Another application used to estimate the DoA of gunshots-using the same algorithms but with the microphone array embedded in a drone-can be seen in [4,9,21,22].…”

Section: Time-delay Estimation Approachesmentioning

confidence: 99%

A Reduced Complexity Acoustic-Based 3D DoA Estimation with Zero Cyclic Sum

Fernandes,

Apolinário,

de Seixas

2024

“…In contrast, for works falling into the LA and AA categories, UAVs have to be adapted to carry out the microphone arrays; hence, custom UAVs may be more convenient. [59] AR drone [60] 3DR IRIS [61] Quad [24] Hexa [24] Hexa [62] Ballon [23] Bebop [23] Pelican [23] Zion [23] Quad [63] 2018 * Matrice 600 pro [47] AR drone [64] Fixed-Wing [65] Bebop [66] Quad [21] Quad [20] Quad [67] Hexa [68] 2019 Fixed-Wing [69] Quad [70] Quad [71] Bebop [72] Bebop [14] Bebop 2 [15] Matrice 100 [15] MK-Quadro [73]…”

Section: On the Number Of Microphones And Uav Modelsmentioning

confidence: 99%

“…It is important to note that in a considerable number of non-MUSIC approaches reported in Table 3 , the UAV’s ego-noise is removed by exploiting the harmonic structure of its rotors’ acoustic spectral signature. This seems to be effective, since techniques that are sensitive to noise (such as GCC-PHAT used in [ 60 ] and cosine distance between signals in [ 70 ]) provide a moderate to good performance after noise removal.…”

Section: Auditory Perception From a Uav (Land To Air)mentioning

confidence: 99%

A Review on Auditory Perception for Unmanned Aerial Vehicles

Martínez-Carranza

Rascón

2020

Although a significant amount of work has been carried out for visual perception in the context of unmanned aerial vehicles (UAVs), not so much has been done regarding auditory perception. The latter can complement the observation of the environment that surrounds a UAV by providing additional information that can be used to detect, classify, and localize audio sources of interest. Motivated by the usefulness of auditory perception for UAVs, we present a literature review that discusses the audio techniques and microphone configurations reported in the literature. A categorization of techniques is proposed based on the role a UAV plays in the auditory perception (is it the one being perceived or is it the perceiver?), as well as a set of objectives that are more popularly aimed to be accomplished in the current literature (detection, classification, and localization). This literature review aims to provide a concise landscape of the most relevant works on auditory perception in the context of UAVs to date and provides insights into future avenues of research as a guide to those who are beginning to work in this field.

“…Fortunately, microphone arrays bring new potential solutions to deal with these problems. Microphone arrays are widely used in civilian and military fields, such as noise reduction and signal enhancement [ 1 , 2 , 3 , 4 ], hearing aid [ 5 , 6 ], outdoor wind noise measurement [ 7 , 8 ], acoustic source localization and tracking [ 9 , 10 , 11 , 12 ], weapon classification and shooter localization [ 13 , 14 ], and so on. In the last few years, due to the development of the micro-electro-mechanical system (MEMS) technology, small aperture arrays have shown their potential superiority in terms of portability and easy deployment, especially in the field.…”

Section: Introductionmentioning

confidence: 99%

A Robust Real Time Direction-of-Arrival Estimation Method for Sequential Movement Events of Vehicles

Liu

Zhou

et al. 2018

Parameters estimation of sequential movement events of vehicles is facing the challenges of noise interferences and the demands of portable implementation. In this paper, we propose a robust direction-of-arrival (DOA) estimation method for the sequential movement events of vehicles based on a small Micro-Electro-Mechanical System (MEMS) microphone array system. Inspired by the incoherent signal-subspace method (ISM), the method that is proposed in this work employs multiple sub-bands, which are selected from the wideband signals with high magnitude-squared coherence to track moving vehicles in the presence of wind noise. The field test results demonstrate that the proposed method has a better performance in emulating the DOA of a moving vehicle even in the case of severe wind interference than the narrowband multiple signal classification (MUSIC) method, the sub-band DOA estimation method, and the classical two-sided correlation transformation (TCT) method.