Fusion solution for soldier wearable gunfire detection systems

Cakiades, George; Desai, Sachi; Deligeorges, Socrates; Buckland, Bruce E.; George, Jemin

doi:10.1117/12.924733

Cited by 4 publications

(6 citation statements)

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“…Motivated by mobile acoustic event localization applications such as the PinPoint TM event localization sensor network [26], [28], we consider a localization sensor network divided into m clusters (cf. Fig.…”

Section: Problem Statementmentioning

confidence: 99%

“…It is worth noting that both PPM and PONLM can reach very high accuracies. However, in practical applications like gunfire localization, the accuracy of 10 0 is sufficient [28]. Remark 4.…”

Section: Convergence Performancementioning

confidence: 99%

“…, N i ). Still motivated by acoustic event localization applications (e.g., the PinPoint TM event localization sensor network [26], [28]), we assume that a cluster head exists in each cluster i, which can gather range measurements r i,k from all sensors within the cluster. In addition, a cluster head can communicate and exchange information with the cluster head of a neighboring cluster if there is a communication link between them (cf.…”

Section: Problem Statementmentioning

confidence: 99%

“…In this paper, we propose two distributed event localization approaches based on a clustered architecture motivated by mobile acoustic localization applications such as the PinPoint TM system from BioMimetics Systems Inc. The PinPoint TM mobile localization sensor network can be deployed as a mobile infrastructure for impulsive threat event detection and localization [26], [28]. Each PinPoint TM sensor is a small omnidirectional microphone array which localizes impulsive acoustic events by correlating the ToA measurements among its microphone cells.…”

Section: Introductionmentioning

confidence: 99%

“…In fact, since each sensor has an integrated microphone array, individual sensors are able to identify and localize a target event without assistance or cooperation with other sensors. However, due to close distances between the microphone cells, the accuracy of individual sensors is very limited and unsatisfactory, and collaboration among the sensors is necessary to improve localization accuracy [26], [28].…”

Section: Introductionmentioning

confidence: 99%

See 4 more Smart Citations

Distributed Event Localization via Alternating Direction Method of Multipliers

Zhang

Wang

2018

IEEE Trans. on Mobile Comput.

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This paper addresses the problem of distributed event localization using noisy range measurements with respect to sensors with known positions. Event localization is fundamental in many wireless sensor network applications such as homeland security, law enforcement, and environmental studies. However, most existing distributed algorithms require the target event to be within the convex hull of the deployed sensors. Based on the alternating direction method of multipliers (ADMM), we propose two scalable distributed algorithms named GS-ADMM and J-ADMM which do not require the target event to be within the convex hull of the deployed sensors. More specifically, the two algorithms can be implemented in a scenario in which the entire sensor network is divided into several clusters with cluster heads collecting measurements within each cluster and exchanging intermediate computation information to achieve localization consistency (consensus) across all clusters. This scenario is important in many applications such as homeland security and law enforcement. Simulation results confirm effectiveness of the proposed algorithms.

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Section: Problem Statementmentioning

confidence: 99%

“…It is worth noting that both PPM and PONLM can reach very high accuracies. However, in practical applications like gunfire localization, the accuracy of 10 0 is sufficient [28]. Remark 4.…”

Section: Convergence Performancementioning

confidence: 99%