Fusion Localization Algorithm Based on Robust IMM Model Combined with Semi-Definite Programming

With the continuous development of wireless sensor network (WSN) technology, WSN has gradually become one of the key technologies of the Internet, and is widely used in indoor target location technology. However, the obstacles will have a great influence on the distance measurement, and it will result in a large positioning error. Therefore, how to deal with the non-line-of-sight (NLOS) error becomes an important problem. In this paper, Interacting Multiple Model (IMM) was used to identify NOLS/LOS. The NLOS probability was calculated by Markov transform probability, and the likelihood function was calculated by extended Kalman filter (EKF). The NLOS probability was compared with the LOS probability to judge whether the measurement contained the NLOS error. A robust algorithm combining IMM model with semidefinite programming (IMM-SDP) was proposed. The improved convex programming algorithm was proposed to reduce the NLOS error. Simulation and experimental results showed that the proposed algorithm can effectively reduce the influence of NLOS error and achieve higher positioning accuracy compared with the existing positioning methods.