The NLOS Localization Algorithm Based on the Linear Regression Model of Hybrid Filter
| Autor: | Ziyi Zhang, Yinhong Guo, Nan Hu, Xin Yang |
|---|---|
| Rok vydání: | 2019 |
| Předmět: |
Computer science
020208 electrical & electronic engineering Hybrid filter 020206 networking & telecommunications 02 engineering and technology Residual Non-line-of-sight propagation Extended Kalman filter Robustness (computer science) Linear regression Computer Science::Networking and Internet Architecture 0202 electrical engineering electronic engineering information engineering Algorithm Wireless sensor network |
| Zdroj: | 2019 Chinese Control And Decision Conference (CCDC). |
| DOI: | 10.1109/ccdc.2019.8832987 |
| Popis: | The location of the mobile node is an important issue in wireless sensor network (WSN). In WSN area, the NLOS (Non-line-of-sight) propagation of signal is ubiquitous and has a significant influence on the localization accuracy. Based on the Linear Regression Model of Extended Kalman Filter (EKF), the beacon node status is identified and the distance residual is produced in this paper. Then the H-Infinity filter algorithm is used to filter the NLOS distance measurement values. Finally the maximum likelihood localization method is used to locate the position. Simulation results demonstrate that the proposed algorithm have a higher localization accuracy than other methods in different environments and have strong robustness in terms of inhibit NLOS errors. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|