KL-DIVERGENCE KERNEL REGRESSION FOR NON-GAUSSIAN FINGERPRINT BASED LOCALIZATION

摘要

Embodiments are directed to mobile localization, and more specifically, but not exclusively, to tracking mobile devices. Embodiments include methods that consider probability kernels with distance-like metrics between distributions. Also described are probabilistic kernels that can be used for a regression of location, which can achieve up to about 1m accuracy in an office environment.