Name
Title | ||
|---|---|---|
A Localization and Tracking Approach in NLOS Environment Based on Distance and Angle Probability Model. |
Abstract | ||
|---|---|---|
In this paper, an optimization algorithm is presented based on a distance and angle probability model for indoor non-line-of-sight (NLOS) environments. By utilizing the sampling information, a distance and angle probability model is proposed so as to identify the NLOS propagation. Based on the established model, the maximum likelihood estimation (MLE) method is employed to reduce the error of distance in the NLOS propagation. In order to reduce the computational complexity, a modified Monte Carlo method is applied to search the optimal position of the target. Moreover, the extended Kalman filtering (EKF) algorithm is introduced to achieve localization. The simulation and experimental results show the effectiveness of the proposed algorithm in the improvement of localization accuracy. |
Year | DOI | Venue |
|---|---|---|
2019 | 10.3390/s19204438 | SENSORS |
Keywords | Field | DocType |
NLOS,EKF,localization,probability model,MLE | Non-line-of-sight propagation,Extended Kalman filter,Monte Carlo method,Probability model,Maximum likelihood,Algorithm,Kalman filter,Electronic engineering,Sampling (statistics),Engineering,Computational complexity theory | Journal |
Volume | Issue | ISSN |
19 | 20 | 1424-8220 |
Citations | PageRank | References |
0 | 0.34 | 0 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Xin Tian | 1 | 0 | 0.34 |
| Guoliang Wei | 2 | 1309 | 71.09 |
| Jianhua Wang | 3 | 0 | 0.34 |
| Dianchen Zhang | 4 | 0 | 0.34 |