Investigation of target tracking performance for unattended ground sensor networks employing distributed cluster management

Chad A. Stelzig; Magdi A. Essawy; Sharon Minor

doi:10.1117/12.666008

18 April 2006 Investigation of target tracking performance for unattended ground sensor networks employing distributed cluster management

Chad A. Stelzig, Magdi A. Essawy, Sharon Minor

Author Affiliations +

Proceedings Volume 6242, Multisensor, Multisource Information Fusion: Architectures, Algorithms, and Applications 2006; 62420F (2006) https://doi.org/10.1117/12.666008
Event: Defense and Security Symposium, 2006, Orlando (Kissimmee), Florida, United States

Abstract

Interest in the distribution of processing in unattended ground sensing (UGS) networks has resulted in new technologies and system designs targeted at reduction of communication bandwidth and resource consumption through managed sensor interactions. A successful management algorithm should not only address the conservation of resources, but also attempt to optimize the information gained through each sensor interaction so as to not significantly deteriorate target tracking performance. This paper investigates the effects of Distributed Cluster Management (DCM) on tracking performance when operating in a deployed UGS cluster. Originally designed to reduce communications bandwidth and allow for sensor field scalability, the DCM has also been shown to simplify the target tracking problem through reduction of redundant information. It is this redundant information that in some circumstances results in secondary false tracks due to multiple intersections and increased uncertainty during track initiation periods. A combination of field test data playback and Monte Carlo simulations are used to analyze and compare the performance of a distributed UGS cluster to that of an unmanaged centralized cluster.

Citation Download Citation

Chad A. Stelzig, Magdi A. Essawy, and Sharon Minor "Investigation of target tracking performance for unattended ground sensor networks employing distributed cluster management", Proc. SPIE 6242, Multisensor, Multisource Information Fusion: Architectures, Algorithms, and Applications 2006, 62420F (18 April 2006); https://doi.org/10.1117/12.666008

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