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However, using probabilistic method may generate time delay in mobile localization environment.
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This paper focuses on how to maintain the accuracy of the mobile localization in indoor environment mixed with LOS/NLOS conditions.
Therefore, it is significant to cope with the dynamically changing propagation for mobile localization in indoor environment mixed with LOS and NLOS situations.
We describe, design, implement, and evaluate a novel localization scheme based on light scan localization (BLS) by combining grid and light (laser) with mobile localization policy for wireless sensor networks.
Due to complexity of three-dimensional mobile node localization, the three-dimensional environment is meshed into small cubes with a length of l x.
As the mobile node localization algorithm in three-dimensional environment cannot meet the demand of actual application, a hybrid mobile node localization algorithm for a wireless sensor network (WSN) in three-dimensional environment is proposed in this paper, which is based on the least squares support vector regression (LSSVR) and Kalman filter (KF).
This standard provides a mobile environment for the mobile stations (MSs).
In Section 2, a mobile node localization method in three-dimensional environment based on LSSVR algorithm is introduced.
Jianping et al. used the KF algorithm for mobile node localization in the complex mine environment [17].
Figure 1 Movement on mobile computing environment.
The supported environments are largely the development environment and the mobile software environment.
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