Probabilistic soft-range estimator for wireless localization in indoor scenarios

Currently, ultra-wideband develops towards a suitable technology for wireless indoor localization with sub-meter accuracy. Still, the indoor channel complicates the correct interpretation of the measurement especially in non-line-of-sight scenarios. This paper deals with the range estimation in challenging indoor channels as a first step of robust indoor localization. Contrary to the classical hard-decision range estimators, we propose a soft-range estimator which outputs a direct-path probability density function with multiple possible distances and corresponding likelihoods. The proposed method is evaluated based on wideband channel measurements and compared with common state-of-the-art threshold methods.