An HMM-based coarse-to-fine framework constructs radio maps from unlabeled RSS sequences in unidirectional corridor environments, reporting 8.96 dB MAE and enabling 3.33 m KNN localization accuracy.
Bayesian cooperative localization using received signal strength with unknown path loss exponent: Message passing approaches
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Survey-Free Radio Map Construction via HMM-Based Coarse-to-Fine Inference
An HMM-based coarse-to-fine framework constructs radio maps from unlabeled RSS sequences in unidirectional corridor environments, reporting 8.96 dB MAE and enabling 3.33 m KNN localization accuracy.