A novel kalman filter based nlos localization method for wireless sensor networks

作者：Cheng Long^*; Shao Yuchao; Wang Yan

来源：3rd International Conference on Cloud Computing and Security, ICCCS 2017, 2017-06-16 To 2017-06-18.

DOI：10.1007/978-3-319-68505-2_42

• Focus of researches
• Kalman filter algorithms
• Localization
• Localization algorithm
• Measurement residual
• Non-line-of-sight
• Positioning accuracy
• Wireless sensor network (WSNs)

Wireless sensor networks (WSNs) have the focus of research in recent years. Moreover, positioning is very important for wireless sensor networks. However, the positioning accuracy still has large error in the case of non-line-of-sight. In this paper, we propose an improved Kalman filter algorithm to reduce the influence of NLOS error. For the case of NLOS, the measurement residual Ei(k) is updated firstly. This method can effectively reduce the NLOS error, which makes the positioning result more accurate. The simulation results show that the proposed localization algorithm can accurately apply to the normal NLOS location problem.

• 出版日期2017
• 单位东北大学; Northeastern university