Dr. Peter J. Shea Profile

Dr. Peter J. Shea

Staff Engineer at Black River Systems Co

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Author

Publications (15)

Proceedings Article | 14 June 2023 Presentation + Paper

Validation volume reduction with tracking in sensor coordinates

Shida Ye, Yaakov Bar-Shalom, Peter Shea, Chee-Yee Chong

Proceedings Volume 12547, 1254705 (2023) https://doi.org/10.1117/12.2664125

KEYWORDS: Tunable filters, Sensors, Aerodynamics, Antennas, Radar, Simulations, Estimation theory

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Proceedings Article | 21 May 2021 Presentation + Paper

Estimation for a feedback system with a desired final state and intermittent stochastic inputs

Shida Ye, Yaakov Bar-Shalom, Radu Visina, Peter Shea, Chee-yee Chong

Proceedings Volume 11756, 1175605 (2021) https://doi.org/10.1117/12.2588248

KEYWORDS: Stochastic processes

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Proceedings Article | 28 May 2011 Paper

Efficient exchange of information in a distributed tracking environment

Peter Shea, Eric Blake

Proceedings Volume 8050, 80500E (2011) https://doi.org/10.1117/12.887599

KEYWORDS: Sensors, Data transmission, Computer architecture, Distributed computing, Surveillance, Detection and tracking algorithms, Target detection, Telecommunications, Computer simulations, Network architectures

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Proceedings Article | 17 May 2011 Paper

Scheduling of a constellation of imaging satellites with usage constraints

Peter Shea, Nathan Nasgovitz

Proceedings Volume 8044, 804404 (2011) https://doi.org/10.1117/12.883981

KEYWORDS: Sensors, Satellites, Satellite imaging, Sun, Nickel, Imaging systems, Earth observing sensors, Visibility, Algorithm development, Quality measurement

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Proceedings Article | 8 May 2010 Paper

Use of environmental impacts in sensor scheduling

Peter Shea, Marisa Gioioso, Hilary Snell

Proceedings Volume 7691, 769103 (2010) https://doi.org/10.1117/12.852759

KEYWORDS: Sensors, Environmental sensing, Clouds, Target detection, Sensor performance, Genetic algorithms, Atmospheric sensing, Environmental monitoring, Surveillance, Interference (communication)

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Proceedings Article | 6 May 2009 Paper

Adaptive sensor management for multiple missions

Peter Shea, Joe Kirk, David Welchons

Proceedings Volume 7330, 73300M (2009) https://doi.org/10.1117/12.818892

KEYWORDS: Sensors, Missiles, Environmental sensing, Surveillance, Target detection, Genetic algorithms, Environmental management, Sensor performance, Radar, Computer simulations

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Proceedings Article | 21 September 2007 Paper

Data fusion handoff within a federation of fusion systems

Peter Shea, Bryce Roskamp

Proceedings Volume 6699, 66990W (2007) https://doi.org/10.1117/12.735301

KEYWORDS: Sensors, Data fusion, Telecommunications, Filtering (signal processing), Surveillance, MATLAB, Sensor fusion, Environmental sensing, Distance measurement, Target detection

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Proceedings Article | 7 May 2007 Paper

Adaptive sensor tasking using genetic algorithms

Peter Shea, Joe Kirk, Dave Welchons

Proceedings Volume 6567, 65670A (2007) https://doi.org/10.1117/12.721189

KEYWORDS: Sensors, Genetic algorithms, Environmental sensing, Sensor performance, Computer simulations, Synthetic aperture radar, Multispectral imaging, Computer programming, Video acceleration, Video

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Proceedings Article | 25 May 2005 Paper

Tracking groups of detections for use in surveillance tracking problems

Peter Shea

Proceedings Volume 5809, (2005) https://doi.org/10.1117/12.604230

KEYWORDS: Surveillance, Target detection, Radar, Detection and tracking algorithms, Sensors, Roads, Sensor performance, Target recognition, Algorithm development, Signal processing

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Surveillance tracking is rapidly becoming an important application for GMTI radars. Surveillance tracking differs from precision tracking primarily in the scope of the problem being considered. Where precision tracking focuses primarily on the highly accurate location of a few numbers of targets, surveillance tracking is more interested in understanding the general location of large numbers of targets. Several challenges arise as one attempts to directly apply techniques from precision tracking applications to the surveillance realm. In the surveillance problem using GMTI radars, the revisit rate is typically lower due to a larger area that must be considered. As a result, in all but the most benign environments, it is difficult to generate estimates of individual targets. This challenge is further compounded by poor sensor performance which results in large uncertainty in target positions and ambiguity from closely spaced targets. Given these issues, new techniques are required for addressing the surveillance tracking problem. Our approach is to treat the surveillance problem in a slightly different fashion. Rather than attempting to track each of the individual targets in the surveillance region, we will focus on the bigger picture and track the groups of targets. This generalization will result in measurement not being individual radar returns off of a single target but rather a clustered grouping of detections representing a single group detection with both a location and group size. In this way, we are able to provide a true group tracking solution rather than attempting cluster the tracks of individual targets. In order to perform this task it is necessary to cluster detections of targets into group measurements, estimate the size of the group, and to provide an estimate of the location of the group. This paper will describe alternative approaches for clustering of detections and an examination of their performance in the overall group tracking approach. Additionally we will describe a technique for estimating the size of the group using knowledge of sensor performance characteristics and the number of detections that are clustered together. Finally we will describe a method for generating a reasonable estimate of the location of the group. We will conclude the paper with an example that examines the overall system performance on a representative problem.

Proceedings Article | 5 January 2004 Paper

Force aggregation using genetic algortihms

Peter Shea, John Peterson, Kathleen Alexander, Alcino Azevedo

Proceedings Volume 5204, (2004) https://doi.org/10.1117/12.506449

KEYWORDS: Genetic algorithms, Computer programming, Fuzzy logic, Composites, Kinematics, Genetics, Algorithm development, Surveillance systems, Surveillance, Target detection

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Proceedings Article | 25 August 2003 Paper

Data fusion: a conceptual approach to level 2 fusion (situational assessment)

Stephen Stubberud, Peter Shea, Dale Klamer

Proceedings Volume 5096, (2003) https://doi.org/10.1117/12.484887

KEYWORDS: Data fusion, Algorithm development, Filtering (signal processing), Kinematics, Information fusion, Detection and tracking algorithms, Artillery, Manufacturing, Clouds, Mirrors

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Proceedings Article | 13 July 2000 Paper

Improved state estimation through use of roads in ground tracking

Peter Shea, Tim Zadra, Dale Klamer, Ellen Frangione, Rebecca Brouillard

Proceedings Volume 4048, (2000) https://doi.org/10.1117/12.391989

KEYWORDS: Roads, Motion models, Sensors, Detection and tracking algorithms, Motion estimation, Target detection, Filtering (signal processing), Radar, Weapons, Electronic filtering

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Proceedings Article | 27 July 1999 Paper

Fuzzy control in the deployable autonomous distributed system

Peter Shea, Mark Owen, George Chadderdon

Proceedings Volume 3720, (1999) https://doi.org/10.1117/12.357163

KEYWORDS: Sensors, Fuzzy logic, Control systems, Filtering (signal processing), Distributed computing, Magnetic sensors, Data fusion, Motion models, Acquisition tracking and pointing, Detection and tracking algorithms

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Proceedings Article | 3 September 1998 Paper

Computational experiences with hot starts for a moving window implementation of track maintenance

Peter Shea, Aubrey Poore

Proceedings Volume 3373, (1998) https://doi.org/10.1117/12.324636

KEYWORDS: Detection and tracking algorithms, Sensors, Mathematics, Signal processing, Data processing, Information operations, Algorithms, Astatine, Radar, Scientific research

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Proceedings Article | 5 July 1995 Paper

New class of Lagrangian relaxation-based algorithms for fast data association in multiple hypothesis tracking applications

Aubrey Poore, Alexander Robertson, Peter Shea

Proceedings Volume 2484, (1995) https://doi.org/10.1117/12.213069

KEYWORDS: Detection and tracking algorithms, Sensors, Optimization (mathematics), Logic, Radon, Surveillance, Data fusion, Information operations, Manganese, Algorithms

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Showing 5 of 15 publications

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