SA-M-SBL: An Algorithm for CSI-Based Device-Free Localization With Faulty Prior Information
IEEE Access
Online resource
Moreover, in practice, some faulty prior information (e.g., coarse positions) is usually available. To take advantage of this information for joint sparse recovery, novel support knowledge-aided multiple sparse Bayesian learning (SA-M-SBL) algorithm is introduced, which incorporates the prior information into a three-layer hierarchical prior model.
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