Presentation + Paper
12 June 2023 On the role of uncertainty in Poisson target models used for placement of spatial sensors
Author Affiliations +
Abstract
This paper addresses the role of uncertainty in spatial point-process models, such as those that might arise in modelling ship traffic. We consider a doubly stochastic Poisson point process where the intensity function is uncertain. To assess the role of uncertainty, we conduct a large set of numerical trials where we estimate a doubly stochastic Poisson point-process model from historical target data, and the evaluate the model by assessing the target detection performance of a set of sensors whose locations are selected using the model. Our work is motivated by seabed sensors that detect ship traffic, and we conduct numerical trials using historical ship traffic data near the mouth of the Chesapeake Bay, Virginia, USA, that was recorded by the Automated Identification System.
Conference Presentation
© (2023) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Mingyu Kim, Harun Yetkin, Daniel J. Stilwell, and Jorge Jimenez "On the role of uncertainty in Poisson target models used for placement of spatial sensors", Proc. SPIE 12543, Ocean Sensing and Monitoring XV, 1254308 (12 June 2023); https://doi.org/10.1117/12.2663630
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KEYWORDS
Sensors

Data modeling

Sensor networks

Target detection

Stochastic processes

Process modeling

Performance modeling

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