Probabilistic Indoor Position Determination via Channel Impulse Response

摘要

Location Fingerprinting (LF) is a promising localization technique that enables many commercial and industrial Location-based Services (LBS). In this paper, a Channel Impulse Response (CIR) based indoor localization system is proposed. To fully exploit the most location-specific multipath information, we first conduct a power-based time tap filtering for the received CIR measurements. Furthermore, we experimentally observe that the filtered CIR data exhibits a multivariate circularly-symmetric Gaussian feature, which hints that fingerprinting positioning can be implemented by using a more accurate probabilistic method with a less computational complexity. In the online position determination phase, the Kullback-Leibler Distance (KLD) is adopted to quantify the similarities between the received measurements of target and the fingerprint database. Afterwards, we employ a probability kernel based regression approach to accurately infer the estimated target's location. Through extensive experiments performed on CRAWDAD database, the efficiency of our proposed scheme is validated.