A Novel Bayesian-based Adaptive Algorithm

These data is state estimation accuracy of the proposed algorithm When the equivalent measurement loss probability is 0.1

These data includes the position estimation accuracy and velocity estimation accuracy of the algorithm.

The data are explained below:

save_bikf_pos_p1, save_kf_pos_p1, save_okf_pos_p1, save_bakf_pos_p1, save_vakf_pos_p1 are the position accuracy of the BKF, KF, OKF, the proposed BAKF-GIWM and the VAKF-GIWM, respectively. 

save_bikf_vel_p1, save_kf_vel_p1, save_okf_vel_p1, save_bakf_vel_p1, save_vakf_vel_p1 are the velocity accuracy of the BKF, KF, OKF, the proposed BAKF-GIWM and the VAKF-GIWM, respectively. 

save_nees_bikf_p1, save_nees_kf_p1, save_nees_okf_p1, save_nees_bakf_p1, save_nees_vakf_p1 show the normalized estimation squared (NEES) of the BKF, KF, OKF, the proposed BAKF-GIWM and the VAKF-GIWM, respectively. 

save_srnfn_bakf_q_p1 and save_srnfn_vakf_q_p1 show the modeling accuracy of state noise.

save_srnfn_bakf_r_p1 and save_srnfn_vakf_r_p1 show the modeling accuracy of measurement noise.

save_computation_bakf_p1 and save_computation_vakf_p1 show the Computation Time of the BAKF-GIWM and VAKF-GIWM, respectively.