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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Ling Shi Peng Cheng Jiming Chen |
| Copyright Year | 2010 |
| Description | Author affiliation: Institute of Industrial Process Control, Zhejiang University, Hang Zhou, China (Peng Cheng; Jiming Chen) || Electronic and Computer Engineering, Hong Kong Univ. of Sci & Tech Clear Water Bay, Kowloon, Hong Kong (Ling Shi) |
| Abstract | In this paper, we consider the problem of sensor scheduling with limited resources. Two sensors are used to measure the state of a discrete-time linear process. We assume that each sensor has a maximum duty cycle and at most one sensor can communicate with a remote estimator at each time step due to the limited communication bandwidth. When a sensor is scheduled to send data, it sends the most recent D measurement data to the estimator. Upon receiving the measurement data from the sensors, the estimator computes the optimal estimate of the state of the process. We first present a necessary condition for a sensor scheduling scheme to be optimal. Based on this necessary condition, we construct an optimal scheduling scheme that minimizes the estimation error at the estimator and at the same time satisfies the energy and communication bandwidth constraints. We also provide a sufficient condition on the minimum D such that an optimal scheduling scheme can be constructed. Examples are provided throughout the paper to demonstrate the results developed. |
| Starting Page | 537 |
| Ending Page | 542 |
| File Size | 195247 |
| Page Count | 6 |
| File Format | |
| ISBN | 9781424478149 |
| e-ISBN | 9781424478156 |
| DOI | 10.1109/ICARCV.2010.5707287 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2010-12-07 |
| Publisher Place | Singapore |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Optimal scheduling Schedules Kalman filters Equations Robot sensing systems Estimation error Networked estimation Sensor scheduling Kalman filtering |
| Content Type | Text |
| Resource Type | Article |
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