Abstract
In this paper, we study the problem of sensor placement for field estimation, where the best subset of potential sensor locations is chosen to strike a balance between the number of deployed sensors and estimation accuracy. Potential sensor locations are generated by sampling a continuous field of interest. We investigate the impact of sampling strategies on sensor placement, and show that compared to other commonly-used sampling strategies, the Poisson disk sampling method can provide a more accurate (discretized) representation of the random field. Based on the sampled locations, we propose an efficient placement algorithm that scales gracefully with problem size using the alternating direction method of multipliers and the accelerated gradient descent method. Numerical results are provided to demonstrate the effectiveness of our approach for sensor placement.
| Original language | English (US) |
|---|---|
| Title of host publication | 2016 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2016 - Proceedings |
| Publisher | Institute of Electrical and Electronics Engineers Inc. |
| Pages | 520-524 |
| Number of pages | 5 |
| ISBN (Electronic) | 9781509045457 |
| DOIs | |
| State | Published - Apr 19 2017 |
| Event | 2016 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2016 - Washington, United States Duration: Dec 7 2016 → Dec 9 2016 |
Other
| Other | 2016 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2016 |
|---|---|
| Country | United States |
| City | Washington |
| Period | 12/7/16 → 12/9/16 |
Keywords
- Alternating direction method of multipliers
- Field estimation
- Poisson disk sampling
- Sensor placement
- Sparsity
ASJC Scopus subject areas
- Signal Processing
- Computer Networks and Communications