Magnetic Dipole Tracking Based on Nonlinear Filtering Algorithm

To realize the magnetic dipole tracking with high nonlinearity characteristic, the estimation of magnetic di-pole′s position, magnetic moment, and velocity is formulated as a Bayesian estimation problem for dynamic systems. A recursive approach is proposed to evaluate the state parameter of the target. Based on the proposed method, the Gaus-sian-mixture sigma-point particle filter(GMSPPF) is adopted to realize the magnetic dipole tracking. The performance of the proposed method is verified through experiment. The results indicate that the proposed method can achieve higher tracking performance, and GMSPPF performs better in both estimation and computational efficiency than the particle filtering and sigma-point particle filtering algorithms.