Name
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. |
Year | DOI | Venue |
|---|---|---|
2009 | 10.1109/ACC.2009.5159844 | ACC'09 Proceedings of the 2009 conference on American Control Conference |
Keywords | DocType | ISSN |
least squares approximations,probability,signal detection,surveillance,target tracking,time series,underwater sound,detection threshold,moving target,online surveillance,probabilistic-state-machine-based algorithm,real-time algorithm,sensor field,sensor time series data,signal threshold estimation,undersea target tracking,weighted linear least squares,Formal language construction,Symbolic Time Series Analysis,Tracking before detection | Conference | 0743-1619 E-ISBN : 978-1-4244-4524-0 |
ISBN | Citations | PageRank |
978-1-4244-4524-0 | 0 | 0.34 |
References | Authors | |
7 | 4 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Kushal Mukherjee | 1 | 105 | 12.83 |
| Ray, A. | 2 | 832 | 184.32 |
| Thomas A. Wettergren | 3 | 85 | 12.11 |
| Chattopadhyay, I. | 4 | 43 | 4.32 |