Mr. John C. Whitson Profile

John C. Whitson

Cyber Technology Specialist

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Proceedings Article | 21 February 2001 Paper

Self-organizing cooperative sensor network for remote surveillance: improved target tracking results

Richard Burne, Ivan Kadar, John Whitson, Anna Buczak

Proceedings Volume 4232, (2001) https://doi.org/10.1117/12.417546

KEYWORDS: Sensors, Surveillance, Acoustics, Unattended ground sensors, Kinematics, Sensor networks, Detection and tracking algorithms, Target recognition, Taxonomy, Magnetic sensors

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The current trend to develop low cost, miniature unattended ground sensors will enable a cost-effective, covert means for surveillance in both urban and remote border areas. Whereas the functionality (e.g., sensing range and life in the field) of these smaller UGS (i.e., acoustic, seismic, magnetic, chemical or biological) may be limited due to size and cost constraints, a network of these sensors working cooperatively together can provide an effective surveillance capability. A key factor is the ability of these sensors to work cooperatively to achieve a `collective' functionality that can meet the surveillance objective. This paper describes results of using target identification (ID) features (i.e., the ID feature space of the target) to improve the tracking of closely spaced targets (i.e., the kinematic space of the targets). A Multiple Level Identification (MLID) approach was used to determine and maintain confidences for multiple target identifications for each target. These confidences were incorporated into the processing of kinematic data (i.e., target bearing reports) to improve the tracker's estimated position of the target's location. Results describing the effectiveness of using MLID on target tracking performance are reported using simulated target trajectory and ID data.

Proceedings Article | 21 July 2000 Paper

Self-organizing cooperative UGS network for target tracking

Richard Burne, Ivan Kadar, John Whitson, Eitan Eadan

Proceedings Volume 4040, (2000) https://doi.org/10.1117/12.392565

KEYWORDS: Sensors, Acoustics, Unattended ground sensors, Surveillance, Detection and tracking algorithms, Error analysis, Sensor networks, Target detection, Roads, Magnetic sensors

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The current trend to develop low cost, miniature unattended ground sensor (UGS) will enable a cost-effective, covert means for surveillance in both urban and remote border areas. Whereas the functionality (e.g., sensing range and life in the field) of these individual UGS (i.e., acoustic, seismic, magnetic, chemical or biological) are limited due to size and cost constraints, a network of these sensors working cooperatively together can provide an effective surveillance capability. A key factor is the ability of these sensors to work cooperatively to achieve a `collective' functionality that can meet the surveillance objective. For example, a realistic mission objective would be to use the minimum number of sensors necessary (i.e., preserve the life of the network) to detect, identify and track vehicles in a desert canyon area that has variable wind and temperature conditions. The network would have to assess the effect of the wind direction and temperature on the sensing range of its acoustic sensors, turn on those sensors that can initially detect the target and dynamically activate other appropriate sensors (e.g., seismic, acoustic or imaging sensors) that can identify and track the vehicle as it moves into and across the canyon area covered by the sensor network. To achieve this type of functionality requires system algorithms that are capable of optimizing the utilization of the sensors. This paper describes results that show improved target tracking accuracy by optimizing the selection of acoustic sensors that measure bearing angles to the target. Also, recent results are described from testing the tracking algorithm with real data.

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