Abstract
Sensor networks for the assessment of physical threats in critical infrastructure have the potential to provide continuous and reliable information on illegal activity over wide areas. In order to reach that potential, it is essential for the sensor network to operate efficiently by conducting processing and communication operations on a very limited power budget. In this work, it is shown that when sequentially assessing physical threats using a sensor network, the required processing and communication load is directly related to estimation uncertainty. It is, furthermore, shown that the processing and communications rate required for sequential estimation using a sensor network is much less than the rate required for processing and transmitting all data available at the nodes. This result can be used to reduce hardware cost and power requirements of the sensor network.
This work was co-funded by the European Regional Development Fund and the Republic of Cyprus through the Research Promotion Foundation (Project \(TEXNO \varLambda O\varGamma IA/MHXAN/0311(BIE)/03\)).
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References
Rago, C., Willett, P., Bar-Shalom, Y.: Detection-tracking performance with combined waveforms. IEEE Trans. Aerosp. Electron. Syst. 34(6), 612–624 (1998)
Kyriakides, I., Konstantinidis, I., Morrell, D., Benedetto, J.J., Papandreou-Suppappola, A.: Target tracking using particle filtering and CAZAC sequences. In: Waveform Diversity and Design, pp. 367–371 (2007)
Muise, R., Mahalanobis, A.: Recent results of integrated sensing and processing using a programmable hyperspectral imaging sensor. In: Proceedings of SPIE, Optical Pattern Recognition XVII, vol. 6245, April 2006
Priebe, C.E., Marchette, D.J., Healy, D.M.: Integrated sensing and processing decision trees. IEEE Trans. Pattern Anal. Mach. Intell. 26(6), 699–708 (2004)
Waagen, D., Schmitt, H.A., Shah, N.: Activities in integrated sensing and processing. In: Proceedings of the Intelligent Sensors, Sensor Networks and Information Processing Conference, pp. 295–300, December 2004
Sira, S.P., Papandreou-Suppappola, A., Morrell, D.: Time-varying waveform selection and configuration for agile sensors in tracking applications. In: Proceedings of IEEE ICASSP, Philadelphia, April 2005
Arulampalam, M.S., Maskell, S., Gordon, N., Clapp, T.: A tutorial on particle filters for online nonlinear/non-Gaussian Bayesian tracking. IEEE Trans. Sig. Process. 50(2), 174–188 (2002)
Kyriakides, I., Morrell, D., Papandreou-Suppappola, A.: Sequential Monte Carlo methods for tracking multiple targets with deterministic and stochastic constraints. IEEE Trans. Sig. Process. 56(3), 937–948 (2008)
Kyriakides, I.: A configurable compressive acquisition matrix for radar tracking using particle filtering. In: European Radar Conference (2012)
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Kyriakides, I., Neophytou, S., Kounoudes, A., Michail, K., Argyrou, Y., Wieland, T. (2016). Processing and Communications Rate Requirements in Sensor Networks for Physical Thread Assessment. In: Panayiotou, C., Ellinas, G., Kyriakides, E., Polycarpou, M. (eds) Critical Information Infrastructures Security. CRITIS 2014. Lecture Notes in Computer Science(), vol 8985. Springer, Cham. https://doi.org/10.1007/978-3-319-31664-2_4
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DOI: https://doi.org/10.1007/978-3-319-31664-2_4
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