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Bayesian estimation methods are widely used for wireless localization systems. They employ priori information and current measurement error distribution models to derive the state of a mobile target. Cramér-Rao lower bound (CRLB) is a fundamental tool to analyze the performance of Bayesian estimators. Although CRLB is derived based on the measurement error distribution, only a few works have investigated...
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...
Sensor devices suffer severe interference due to multi path effect, non line of sight (NLOS) and variations of the wireless propagation environment in indoor positioning systems. These interferences lead to measurement error during sensor measurement. Kalman filter (KF) and extended Kalman filter (EKF) have been widely used in tracking systems to reduce measurement noise. However, KF and EKF assume...
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