Environment-Aware Regression for Indoor Localization Based on WiFi Fingerprinting

Data enrichment through interpolation or regression is a common approach to deal with sample collection for Indoor Localization WiFi fingerprinting. This paper provides guidelines on where collect samples and proposes new model received signal strength regression. The creates vectors that describe the presence of obstacles between an access point collected samples. vectors, distance positions samples, collected, are used train Support Vector Regression. experiments included some relevant analyses showed proposed improves in terms residuals positioning accuracy.