Exploring the spatial correlation in radio tomographic imaging by block‐structured sparse Bayesian learning

Radio Tomographic Imaging (RTI) is a low-cost computational imaging method realised by the Frequency (RF) signal sensing. The target-induced shadowing effect in RF sensing network reconstructed as probability image to estimate target's position. Then, RTI-based Device-free Localization (DFL) becoming promising research topic Location-based Services applications Internet of Things (IoT). However, multipath interference often induces degradation and decreases DFL accuracy. To deal with multipath-induced degradation, considering that occupies small spatial range expresses some structure, this article explores correlation shadowing. new RTI reconstruction based on Structured Sparse Bayesian Learning proposed model implied sparse image. Further, localisation experiments actual scenes are conducted validate utilisation able improve quality system enhancing robustness towards degradation.