The PCRB-GMSPPF algorithm is proposed in order to achieve the computation of posterior Cramer-Rao bound in magnetic target tracking issues. In the proposed method, the GMSPPF algorithm is adopted to perform the sampling toward the actual posterior distribution of target state, hence the Fisher information matrix at each observation time in PCRB computation can be approximated using Monte Carlo integral method. The proposed method overcomes the depletion and degeneracy problem which causes the failure to correctly sample in posterior distribution. The simulation analysis is performed on the basis of the establishment of magnetic target tracking state model and observation model. The proposed PCRB is compared with the mean square error performance of tracking using GMSPPF and PF algorithm to validate correctness of proposed PCRB computation algorithm. The results exhibits that PCRB-GMSPPF outperforms the PCRB-PF in accuracy for magnetic target tracking issues, and can be generalized for general non-linear tracking model analysis for error lower bound.