A New Elliptical Model for Device-Free Localization

Device-free localization (DFL) is a technology that identifies and tracks individuals by analyzing fluctuations in received signal strength (RSS), thus eliminating the requirement for any devices. As a rapidly developing and significant technology within WSNs, radio tomographic imaging (RTI) has garnered growing interest. However, there is significant potential for improving the accuracy of localization in RTI. To address this issue, we propose a novel DFL algorithm to improve the localization accuracy: this algorithm incorporates an enhanced method for channel choosing to gather data, along with a novel weighting model. The distance-based channel choosing method selects channels with stronger Pearson correlation, which enhances resilience to environmental fluctuations. The weighting model that has been proposed is based on the spatial positioning of voxels relative to sensors. The experimental results indicate that the proposed algorithm can enhance positioning accuracy by up to 26% relative to certain leading RTI approaches.