Name
Abstract | ||
|---|---|---|
This paper proposes an approximate message passing cooperative localizer (AMP-CL) for wireless sensor networks (WSNs) with angle-of-arrival (AOA) ranging measurements and unknown orientation angles. At first, an incremental localizer is developed to provide initial position estimations. Subsequently, orientation angles of WSN nodes are separately estimated based on current node position estimations and AOA observations by maximum-likelihood (ML) method. Based on the current orientation estimations, cooperative localization problem is converted as a generalized linear mixing problem, and resolved by AMP algorithm. Finally, AMP-CL will iterate between AMP-based positioning recovery and ML orientation angle estimation until convergence conditions are satisfied. It is featured on low-computational complexity, and distributed implementation manner. Simulation results also validate the state-of-the-art positioning performance and cooperative gains of AMP-CL after comparing itself with some main-stream localizers under different communication ranges and noise contaminations. |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1109/INFCOMW.2018.8406856 | IEEE INFOCOM 2018 - IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS) |
Keywords | Field | DocType |
approximate message-passing cooperative localization,ML orientation angle estimation,generalized linear mixing problem,maximum-likelihood method,current node position estimations,WSN nodes,initial position estimations,incremental localizer,unknown orientation angles,angle-of-arrival ranging measurements,wireless sensor networks,AMP-CL,approximate message passing cooperative localizer,AOA measurements | Convergence (routing),Distance measurement,Computer science,Maximum likelihood,Algorithm,Ranging,Wireless sensor network,Message passing | Conference |
ISSN | ISBN | Citations |
2159-4228 | 978-1-5386-5980-9 | 0 |
PageRank | References | Authors |
0.34 | 12 | 5 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Mingyue Ding | 1 | 261 | 41.04 |
| Shengchu Wang | 2 | 81 | 7.92 |
| Zhongyan Huang | 3 | 0 | 0.34 |
| Konglin Zhu | 4 | 71 | 13.19 |
| Ling Zhang | 5 | 13 | 3.02 |