一种RFID数据中位置参数的Bayes估计方法

RFID设备固有的限制和环境噪声的影响,造成RFID原始数据的不确定性。为了估计RFID冗余数据中位置参数,提出了利用多阅读器观测到的冗余数据反演目标符号位置参数的Bayes方法。该方法以3-态识别模型为基础建立了Bayes推论模型,通过融合监测区域中的先验知识和约束条件,采用Markov Chain Monte Carlo(MCMC)的方法求解Bayes联合概率分布,进而得到符号位置参数的后验概率分布。模拟实验结果表明,符号位置参数的估计方法可以获得较好的效率和准确性。

A Bayesian estimation method for the location parameter in RFID data

Because RFID readings are inherently noisy due to the hardware limitations and the environmental interference, the applications of the RFID are restricted in many areas. In order to estimate the parameter of target symbol location, a Bayesian model was developed to inverse the parameter of target symbol location by taking use of observed RFID readings in multiple readers. The inference of the Bayesian model is based on 3-state detection model. A Markov Chain Monte Carlo (MCMC) method is used to sample the Bayesian joint posterior probability function to get the marginal posterior distributions of the target symbol location parameters, by compromising prior knowledge and constraints in RFID detection region. Simulated experiments have demonstrated the validity and accuracy of the method proposed to estimate symbol location.