Dr. James E. Bevington Profile

Dr. James E. Bevington

Senior Lead Systems Engineer at General Dynamics Mission Systems

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Publications (6)

Proceedings Article | 24 May 2011 Paper

Discovering geospatial networks from ambiguous track data

James Bevington, Michael Evans, Shashi Shekhar

Proceedings Volume 8062, 80620K (2011) https://doi.org/10.1117/12.887007

KEYWORDS: Detection and tracking algorithms, Sensors, Automatic tracking, Surveillance, Data acquisition, Algorithm development, Image sensors, Computer simulations, Roads, Video

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Proceedings Article | 24 May 2011 Paper

Trident Spectre 2010: agile integration and demonstration of a multi-sensor airborne pod

Greg Twaites, Brent Rickenbach, James Bevington, Gary Garceau, Peter Griffin, Jason Rush

Proceedings Volume 8062, 80620J (2011) https://doi.org/10.1117/12.886421

KEYWORDS: Sensors, Cameras, Video, Imaging systems, Fourier transforms, Video surveillance, Electro optical systems, Defense and security, Surveillance

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Proceedings Article | 26 May 2005 Paper

Distributed cluster management techniques for unattended ground sensor networks

Magdi Essawy, Chad Stelzig, James Bevington, Sharon Minor

Proceedings Volume 5820, (2005) https://doi.org/10.1117/12.604009

KEYWORDS: Sensors, Sensor networks, Target detection, Sensor fusion, Telecommunications, Unattended ground sensors, Monte Carlo methods, Data fusion, RF communications, Data communications

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Smart Sensor Networks are becoming important target detection and tracking tools. The challenging problems in such networks include the sensor fusion, data management and communication schemes. This work discusses techniques used to distribute sensor management and multi-target tracking responsibilities across an ad hoc, self-healing cluster of sensor nodes. Although miniaturized computing resources possess the ability to host complex tracking and data fusion algorithms, there still exist inherent bandwidth constraints on the RF channel. Therefore, special attention is placed on the reduction of node-to-node communications within the cluster by minimizing unsolicited messaging, and distributing the sensor fusion and tracking tasks onto local portions of the network. Several challenging problems are addressed in this work including track initialization and conflict resolution, track ownership handling, and communication control optimization. Emphasis is also placed on increasing the overall robustness of the sensor cluster through independent decision capabilities on all sensor nodes. Track initiation is performed using collaborative sensing within a neighborhood of sensor nodes, allowing each node to independently determine if initial track ownership should be assumed. This autonomous track initiation prevents the formation of duplicate tracks while eliminating the need for a central “management” node to assign tracking responsibilities. Track update is performed as an ownership node requests sensor reports from neighboring nodes based on track error covariance and the neighboring nodes geo-positional location. Track ownership is periodically recomputed using propagated track states to determine which sensing node provides the desired coverage characteristics. High fidelity multi-target simulation results are presented, indicating the distribution of sensor management and tracking capabilities to not only reduce communication bandwidth consumption, but to also simplify multi-target tracking within the cluster.

Proceedings Article | 19 July 2004 Paper

Distributed sensor management and target tracking for unattended ground sensor networks

James Bevington

Proceedings Volume 5441, (2004) https://doi.org/10.1117/12.547579

KEYWORDS: Sensors, Target detection, Sensor networks, Telecommunications, Unattended ground sensors, Detection and tracking algorithms, RF communications, Error analysis, Monte Carlo methods, Sensor fusion

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Proceedings Article | 29 August 2001 Paper

Target tracking for heterogeneous smart sensor networks

James Bevington, Timothy McDonnell

Proceedings Volume 4396, (2001) https://doi.org/10.1117/12.438326

KEYWORDS: Sensors, Detection and tracking algorithms, Target detection, Sensor networks, Java, MATLAB, Filtering (signal processing), Cameras, Image sensors, Environmental sensing

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Showing 5 of 6 publications

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