TY - GEN
T1 - On Tracking Realistic Targets in a Megacity with Contested Domain Access
AU - Lee, Jongdeog
AU - Abdelzaher, Tarek
AU - Qiu, Hang
AU - Govindan, Ramesh
AU - Marcus, Kelvin
AU - Hobbs, Reginald
AU - Suri, Niranjan
AU - Dron, Will
N1 - Funding Information:
Research reported in this paper was sponsored in part by the Army Research Laboratory under Cooperative Agreements W911NF-09-2-0053 and W911NF-17-2-0196, and in part by NSF under grants CNS 16-18627 and CNS 13-20209. The views and conclusions contained in this document are those of the authors and should not be interpreted as representing the official policies, either expressed or implied, of the Army Research Laboratory, NSF, or the U.S. Government. The U.S. Government is authorized to reproduce and distribute reprints for Government purposes notwithstanding any copyright notation here on.
Publisher Copyright:
© 2018 IEEE.
PY - 2019/1/2
Y1 - 2019/1/2
N2 - An increasing emphasis of the US Army lies in supporting efficient operation in contested environments, where access to air (e.g., aerial surveillance and pictures) and access to the spectrum (e.g., wireless communication) are highly reduced or denied. A data fusion system, called Athena, was recently developed to optimize information collection for decision making in this context [1]. In this paper, we discuss the use of Athena to track realistic targets on city blocks using deployed security cameras. The work has two objectives: (i) investigate the efficacy of monitoring with sensors available in a city environment (e.g., security cameras, as opposed to, say, aerial imagery), and (ii) minimize communication needs among sensors to better handle bandwidth limitations. 284 vehicle trajectories were collected by inspecting USC campus security cameras to emulate realistic targets. Predictors were trained to anticipate future locations of targets based on past observations. We evaluate the efficacy of such predictors regarding tracking accuracy versus resource savings (e.g., size of footage collected for tracking).
AB - An increasing emphasis of the US Army lies in supporting efficient operation in contested environments, where access to air (e.g., aerial surveillance and pictures) and access to the spectrum (e.g., wireless communication) are highly reduced or denied. A data fusion system, called Athena, was recently developed to optimize information collection for decision making in this context [1]. In this paper, we discuss the use of Athena to track realistic targets on city blocks using deployed security cameras. The work has two objectives: (i) investigate the efficacy of monitoring with sensors available in a city environment (e.g., security cameras, as opposed to, say, aerial imagery), and (ii) minimize communication needs among sensors to better handle bandwidth limitations. 284 vehicle trajectories were collected by inspecting USC campus security cameras to emulate realistic targets. Predictors were trained to anticipate future locations of targets based on past observations. We evaluate the efficacy of such predictors regarding tracking accuracy versus resource savings (e.g., size of footage collected for tracking).
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U2 - 10.1109/MILCOM.2018.8599773
DO - 10.1109/MILCOM.2018.8599773
M3 - Conference contribution
AN - SCOPUS:85061444820
T3 - Proceedings - IEEE Military Communications Conference MILCOM
SP - 743
EP - 748
BT - 2018 IEEE Military Communications Conference, MILCOM 2018
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2018 IEEE Military Communications Conference, MILCOM 2018
Y2 - 29 October 2018 through 31 October 2018
ER -