Research Article

GNSS/Low-Cost MEMS-INS Integration Using Variational Bayesian Adaptive Cubature Kalman Smoother and Ensemble Regularized ELM

Algorithm 3

GNSS/MEMS-INS integration based on ERELM.
Input: samples .
Output: final Position prediction .
(1)  Initialize:
      initialize the parameter of
      Algorithm 2.
(2) Assign the distribution .
(3) repeat
(4)    for    do ( is the total
   number of samples)
(5)       Use steps (1)–(12) to compute the
   final prediction.
(6)    end for
(7) until GPS outages happen.