Three-Dimensional Localization of RF Emitters: A Semantic Segmentation-based Image Processing Approach

Localization is an important issue in wireless sensor networks (WSNs). Aimed at the shortcomings of low localization accuracy of the existing 3D localization algorithms, in this paper, we develop a three-dimensional localization scheme of RF emitters which combines collaborative spectrum sensing with deep learning. We propose a semantic segmentation approach to identify the coverage range of the RF emitters which converts the three-dimensional sensing data into a series of two-dimensional image slices. Then, we design a weighted localization algorithm to accurately locate the RF emitters. The simulation results show that the proposed method is accurate in positioning under various parameter configurations.