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Optimal Data Fusion in Multiple Sensor Detection Systems
Abstract
There is an increasing interest in employing multiple sensors for surveillance and communications. Some of the motivating factors are reliability, survivability, increase in the number of targets under consideration, and increase in required coverage. Tenney and Sandell have recently treated the Bayesian detection problem with distributed sensors. They did not consider the design of data fusion algorithms. We present an optimum data fusion structure given the detectors. Individual decisions are weighted according to the reliability of the detector and then a threshold comparison is performed to obtain the global decision.
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Cited by
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Yucek, T., & Arslan, H. (2009) · IEEE Communications Surveys & Tutorials · doi:10.1109/surv.2009.090109 · Cited by 4,801
Toward detecting emotions in spoken dialogs
Lee, C. M., & Narayanan, S. S. (2005) · IEEE Transactions on Speech and Audio Processing · doi:10.1109/tsa.2004.838534 · Cited by 988
Cell-Free Massive MIMO: A Survey
Elhoushy, S., Ibrahim, M., & Hamouda, W. (2022) · IEEE Communications Surveys & Tutorials · doi:10.1109/comst.2021.3123267 · Cited by 448
Distributed Fusion Architectures and Algorithms for Target Tracking
Liggins, M. E., Chong, C.-Y., Kadar, I., Alford, M. G., Vannicola, V., & Thomopoulos, S. (1997) · Proceedings of the IEEE · doi:10.1109/jproc.1997.554211 · Cited by 353
Two-Stage Approach for Detection and Reduction of Motion Artifacts in Photoplethysmographic Data
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Metadata
- Authors
- Chair, Z., & Varshney, P. K.
- Venue
- IEEE Transactions on Aerospace and Electronic Systems
- Published
- 1986-01
- Volume
- AES-22
- Issue
- 1
- Pages
- 98-101
- ISSN
- 0018-9251 (ISSN-L)
- OpenAlex
- W2004215803
- Cited by
- 1,130
- References
- 0
- FWCI
- 12.26
- Type
- journal article
- Language
- en
- Open access
- closed
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