Measurement and Mean Power Estimation in Indoor Wireless Channel Based on Higher Order Kalman Filtering

This paper presents theoretical model and experimental results of the mean signal power measurements and estimation in real-time based on higher order Kalman filter (KF) application. The theoretical model and algorithms are developed for the first- and second-order KF and applied to estimate mean value of the data obtained by measurements. The method applied is compared with the existing moving average and scalar KF methods. The measurements are performed at different distances, antenna positions, and space resolutions. In particular, power measurements that kept constant the antenna separation to eliminate the distance dependence in power measurements are carried out. The obtained results show that the second-order KF outperforms the first-order filter and is almost same as the moving average filter with advantage of getting rid of optimum window length problem.