An SDP-based outlier recognition and localization algorithm

For node localization in wireless sensor networks, an optimization algorithm based on semidefinite programming is proposed. For the distance matrix with noise, the low rank matrix is restored by using the automatic outlier identification algorithm based on semidefinite programming. Then, based on the restored distance matrix, two new multi-source node location algorithms based on semidefinite programming, SDP-RLS and SDP-SRLS, are proposed, which effectively transform the non-convex nonlinear location problem into a convex optimal linear location problem. Simulation results show that the proposed algorithm based on SDP has stronger robustness and higher positioning accuracy.