Name
Abstract | ||
|---|---|---|
This paper proposes a Location-Constrained Particle Filter (LC-PF) for Radio Signal Strength Indication (RSSI) based indoor localization system. Based on proposed LC-PF, the RSSI fluctuation problem can be restrained. The proposed methods include location-constrained importance weight updating (LC-WU) and location-constrained propagation model (LC-model). LC-WU eliminates particles in prohibited regions based on the geolocation of the map. The LC-model propagates particles based on different turning probabilities in different regions. These two methods can be applied separately or jointly. The proposed LC-PF has 2.48 m average accuracy improvement over basic PF with 68% error reduction, and results in 2.07 m accuracy with 90% confidence. |
Year | DOI | Venue |
|---|---|---|
2008 | 10.1109/SIPS.2008.4671740 | SiPS |
Keywords | Field | DocType |
particle filtering (numerical methods),rssi indoor localization,tracking filters,location-constrained particle filter,target tracking,location-constrained propagation model,rssi-based human positioning system,rssi based indoor localization system,fluctuation problem,radio signal strength indication,tracking system,location-constrained importance weight updating method,particle filter,probability,indoor radio,accuracy,particle filters,local system,hidden markov models,fingerprint recognition,estimation | Importance Weight,Radio signal strength,Fingerprint recognition,Computer science,Control theory,Particle filter,Geolocation,Algorithm,Tracking system,Real-time computing,Localization system,Hidden Markov model | Conference |
ISSN | ISBN | Citations |
1520-6130 E-ISBN : 978-1-4244-2924-0 | 978-1-4244-2924-0 | 8 |
PageRank | References | Authors |
0.58 | 10 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Chih-Hao Chao | 1 | 182 | 9.90 |
| Chun-Yuan Chu | 2 | 23 | 4.33 |
| An-Yeu Wu | 3 | 801 | 81.68 |