Signal threshold estimation in a sensor field for undersea target tracking

Kushal Mukherjee; Asok Ray; Thomas Wettergren; Ishanu Chattopadhyay; Shashi Phoha

doi:10.1109/ACC.2009.5159844

Signal threshold estimation in a sensor field for undersea target tracking

Kushal Mukherjee, Asok Ray, Thomas Wettergren, Ishanu Chattopadhyay, Shashi Phoha

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

1 Scopus citations

Abstract

This paper addresses the problem of online surveillance of undersea targets moving over a deployed sensor field. A real-time algorithm has been formulated to estimate the detection threshold based on the ensemble of sensor time series data collected from the track of a moving target. The probabilistic-state- machine-based algorithm is optimal in the sense of weighted linear least squares. The algorithm has been tested with sensor data from several tracks on a simulation test bed.

Original language	English (US)
Title of host publication	2009 American Control Conference, ACC 2009
Pages	3591-3596
Number of pages	6
DOIs	https://doi.org/10.1109/ACC.2009.5159844
State	Published - 2009
Event	2009 American Control Conference, ACC 2009 - St. Louis, MO, United States Duration: Jun 10 2009 → Jun 12 2009

Publication series

Name	Proceedings of the American Control Conference
ISSN (Print)	0743-1619

Other

Other	2009 American Control Conference, ACC 2009
Country/Territory	United States
City	St. Louis, MO
Period	6/10/09 → 6/12/09

All Science Journal Classification (ASJC) codes

Electrical and Electronic Engineering

Access to Document

10.1109/ACC.2009.5159844

Cite this

@inproceedings{faf0915a82164350bae83c229a5975aa,

title = "Signal threshold estimation in a sensor field for undersea target tracking",

abstract = "This paper addresses the problem of online surveillance of undersea targets moving over a deployed sensor field. A real-time algorithm has been formulated to estimate the detection threshold based on the ensemble of sensor time series data collected from the track of a moving target. The probabilistic-state- machine-based algorithm is optimal in the sense of weighted linear least squares. The algorithm has been tested with sensor data from several tracks on a simulation test bed.",

author = "Kushal Mukherjee and Asok Ray and Thomas Wettergren and Ishanu Chattopadhyay and Shashi Phoha",

year = "2009",

doi = "10.1109/ACC.2009.5159844",

language = "English (US)",

isbn = "9781424445240",

series = "Proceedings of the American Control Conference",

pages = "3591--3596",

booktitle = "2009 American Control Conference, ACC 2009",

}

Mukherjee, K, Ray, A, Wettergren, T, Chattopadhyay, I & Phoha, S 2009, Signal threshold estimation in a sensor field for undersea target tracking. in 2009 American Control Conference, ACC 2009., 5159844, Proceedings of the American Control Conference, pp. 3591-3596, 2009 American Control Conference, ACC 2009, St. Louis, MO, United States, 6/10/09. https://doi.org/10.1109/ACC.2009.5159844

TY - GEN

T1 - Signal threshold estimation in a sensor field for undersea target tracking

AU - Mukherjee, Kushal

AU - Ray, Asok

AU - Wettergren, Thomas

AU - Chattopadhyay, Ishanu

AU - Phoha, Shashi

PY - 2009

Y1 - 2009

N2 - This paper addresses the problem of online surveillance of undersea targets moving over a deployed sensor field. A real-time algorithm has been formulated to estimate the detection threshold based on the ensemble of sensor time series data collected from the track of a moving target. The probabilistic-state- machine-based algorithm is optimal in the sense of weighted linear least squares. The algorithm has been tested with sensor data from several tracks on a simulation test bed.

AB - This paper addresses the problem of online surveillance of undersea targets moving over a deployed sensor field. A real-time algorithm has been formulated to estimate the detection threshold based on the ensemble of sensor time series data collected from the track of a moving target. The probabilistic-state- machine-based algorithm is optimal in the sense of weighted linear least squares. The algorithm has been tested with sensor data from several tracks on a simulation test bed.

UR - http://www.scopus.com/inward/record.url?scp=70449640418&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=70449640418&partnerID=8YFLogxK

U2 - 10.1109/ACC.2009.5159844

DO - 10.1109/ACC.2009.5159844

M3 - Conference contribution

AN - SCOPUS:70449640418

SN - 9781424445240

T3 - Proceedings of the American Control Conference

SP - 3591

EP - 3596

BT - 2009 American Control Conference, ACC 2009

T2 - 2009 American Control Conference, ACC 2009

Y2 - 10 June 2009 through 12 June 2009

ER -

Signal threshold estimation in a sensor field for undersea target tracking

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