Abstract
This paper describes information-based approaches to processing and organizing spatially distributed, multimodal sensor data in a sensor network. Energy-constrained networked sensing systems must rely on collaborative signal and information processing (CSIP) to dynamically allocate resources, maintain multiple sensing foci, and attend to new stimuli of interest, all based on task requirements and resource constraints. Target tracking is an essential capability for sensor networks and is used as a canonical problem for studying information organization problems in CSIP. After formulating a CSIP tracking problem in a distributed constrained optimization framework, the paper describes information-driven sensor query and other techniques for tracking individual targets as well as combinatorial tracking problems such as counting targets. Results from simulations and experimental implementations have demonstrated that these information-based approaches are scalable and make efficient use of scarce sensing and communication resources.
| Original language | English |
|---|---|
| Pages (from-to) | 1199-1209 |
| Number of pages | 11 |
| Journal | Proceedings of the IEEE |
| Volume | 91 |
| Issue number | 8 |
| DOIs | |
| State | Published - Aug 2003 |
| Externally published | Yes |
Keywords
- Collaborative signal and information processing (CSIP)
- Constrained optimization
- Distributed sensing
- Information utility
- Sensor networks
- Target tracking
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