Localization technology for wireless sensor networks

Network localization is a promising technology for providing high-accuracy positional information in GPS-challenged scenarios. The information is crucial in many location-based applications such as autonomous logistics, building security, as well as search-and-rescue. In this chapter, we discuss some effective localization methods of WSNs. In static sensor networks (SSNs), we present hop-count-based expectation of distance algorithm (HCED). In mobile sensor networks (MSNs), we present range-free Voronoi-based Monte Carlo localization algorithm (VMCL) and an optimal region selection strategy of Voronoi diagram based on VMCL (ORSS-VMCL). In anisotropic SSNs with holes, we present Heuristic Multi-dimensional Scaling (HMDS) and an Extended Kalman Filter Multidimensional Scaling (EKF-MDS) localization method. To solve the problem of Voronoi diagrams based localization scheme (VBLS), an optimal region selection strategy based on VBLS (ORSS-VBLS) is also proposed. Finally, We present a Delaunay triangulation based localization scheme (DBLS) and neighbor constraint assisted distributed localization (NCA-DL), which are effective in refining the distances required for localization.