Abstract
Fast target localization without a map is a challenging problem in search and rescue applications. We propose and evaluate a novel gradient-based method which uses statistical techniques to estimate the position of a stationary target. Mobile nodes can then be directed toward the target using the shortest path. Moreover, localization can be achieved without any assistance from stationary sensor networks. Simulation results demonstrate nearly a 40% reduction in target acquisition time compared to a random walk model. In addition, our method can generate a position prediction map which closely matches the actual distribution in the field. Finally, experiments have been performed using MicaZ motes which further validate our techniques.
Original language | English (US) |
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Pages (from-to) | 37-48 |
Number of pages | 12 |
Journal | Pervasive and Mobile Computing |
Volume | 5 |
Issue number | 1 |
DOIs | |
State | Published - Feb 2009 |
Bibliographical note
Funding Information:Qingquan Zhang is currently a Ph.D. candidate in Department of Electrical and Computer Engineering at University of Minnesota-Twin City. He received the M.S. Degree from Department of Microelectronics, Fudan University, China, in 2003, and the B.S. degree from Department of Electrical Engineering, Fudan University in 2000. He is author and co-author of over 13 publications and received a research award, the best paper awards at the Second International Conference on Mobile Ad-hoc and Sensor Networks in the area of wireless sensor networking. His research includes wireless sensor networks, System Level VLSI Design, Nanoscale electronics and real-time embedded systems, supported by National Science Foundation.
Funding Information:
Dr. Tian He is currently an assistant professor in Department of Computer Science and Engineering at University of Minnesota-Twin City. He received the Ph.D. degree under Professor John A. Stankovic from the University of Virginia, Virginia in 2004, and the M.S. degree from the Institute of Computing Technology, Chinese Academy of Sciences, China, in 2000, and the B.S. degree from the Nanjing University of Science & Technology, Nanjing, China in 1996. Dr. He is author and co-author of over fifty publications in premier sensor network conferences and journals with over a thousand citations. Dr. He has received many research awards in the area of sensor networking, including the best paper awards at the Second International Conference on Mobile Ad-hoc and Sensor Networks and the Fourth ACM Workshop on Security of Ad Hoc and Sensor Networks. Dr. He served several chair positions in international conferences and on many premier program committees such as SenSys and Infocom, and also currently serves as an editorial board member for two international sensor network journals. His research includes wireless sensor networks, intelligent transportation systems, real-time embedded systems and distributed systems, supported by National Science Foundation and other agencies.
Keywords
- Gradient-driven
- Robot
- Signal strength
- Target localization
- Wireless sensor network