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It is hard to obtain a general error model for range-based wireless indoor target tracking system due to the complicated hybrid LOS/NLOS environment. In this paper, we employ a dynamic Gaussian model (DGM) to describe the indoor ranging error. A general Gaussian distribution is constructed firstly. The instantaneous LOS or NLOS error at a typical time is considered as the drift from this general distribution...
The accuracy of particle filtering estimation for the tracking system is prone to be influenced by the high measurement noise (or errors) in wireless sensor networks (WSNs). We first analyze the impact of instantaneous measurement noise which is introduced into the likelihood function and biases the particle filtering estimation. Based on our analysis, we propose a likelihood adaptation method considering...
In this paper, we propose a robust and efficient particle filtering framework for indoor localization in wireless sensor network (WSN) which searches effective anchors and constructs particle filter dynamically. Within this framework, three algorithms are integrated into the dynamic particle filter: anchor selection algorithm, location constraint resampling and SIR particle filter. The proposed scheme...
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