UWB-Based Indoor Human Localization With Time-Delayed Data Using EFIR Filtering

Abstract

An ultra wide band (UWB)-based time-delay indoor human localization scheme is proposed to provide indoor human localization with time-delay measurements. The human position is localized using the UWB-based distance data and the extended finite impulse response (EFIR) estimator employing the timedelay localization model. Only one-step delayed measurements are considered in this paper. We employ the state augmentation method to combine the delayed and not delayed states. To improve the localization robustness for the time-delay localization model, we employ the EFIR filter, which does not require the noise statistics. The experimental results have shown that the EFIR estimator is more robust than the extended Kalman filter-based one for the delayed data.