Conference proceeding
Toward an Evaluation Framework for Gap Filling Radars in Adaptive Distributed Sensor Networks
2011 IEEE INTERNATIONAL CONFERENCE ON SYSTEMS, MAN, AND CYBERNETICS (SMC), pp 1998-2003
01 Jan 2011
Featured in Collection : UN Sustainable Development Goals @ Drexel
Abstract
A framework is presented for comparing sensor coverage between networks of different spatial and temporal resolutions (long-range vs. short-range adaptive), in the context of their operational constraints. A simulation case study evaluates five levels of spacing between adaptive sensors (30km, 35km, 40km, 45km, 50km) in the context of neighboring long-range sensors that provide complementary data. Total system performance is assessed with measures of sensor coverage quality based on the number of radar nodes, tilts and cycles and the fraction of the analysis region's horizontal and vertical domain scanned. Using a squall line weather scenario, results show that 3D scanning performance is significantly lower with 45km and 50km spaced adaptive sensors than with 30km spaced nodes. Comparison with complementary long-range sensors shows that short-range adaptive sensors perform significantly greater at altitudes below 20000 ft. Network performance at all altitudes is shown to be significantly improved by considering both network types together when compared to either network alone. T he analysis framework presented can help inform decision makers of the expected value added by deploying sensors relative to their type and quantity, for the context in which they will be operating.
Metrics
Details
- Title
- Toward an Evaluation Framework for Gap Filling Radars in Adaptive Distributed Sensor Networks
- Creators
- Brendan Hogan - University of VirginiaEllen J. Bass - University of VirginiaIEEE
- Publication Details
- 2011 IEEE INTERNATIONAL CONFERENCE ON SYSTEMS, MAN, AND CYBERNETICS (SMC), pp 1998-2003
- Series
- IEEE International Conference on Systems Man and Cybernetics Conference Proceedings
- Publisher
- IEEE
- Number of pages
- 6
- Resource Type
- Conference proceeding
- Language
- English
- Academic Unit
- Information Science
- Web of Science ID
- WOS:000298615102047
- Scopus ID
- 2-s2.0-83755225488
- Other Identifier
- 991019292227904721
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InCites Highlights
Data related to this publication, from InCites Benchmarking & Analytics tool:
- Web of Science research areas
- Computer Science, Artificial Intelligence
- Computer Science, Cybernetics
- Computer Science, Information Systems