With the time-of-arrival (TOA) range measurements, the moving terminal (MT) usually moves with different dynamic models described in the mixed line-of-sight (LOS) and the non-line-of-sight (NLOS) environments. The measurement noise in the NLOS case is non-Gaussian, especially of a nonzero- mean long-tailed distribution such as the Laplacian noise. The conventional interacting multiple model (IMM) algorithm along with a robust extended Kalman filter has been used to tackle the change of LOS/NLOS models with a Markov chain. To incorporate the second Markov chain describing the change of different dynamic models in the IMM, a concatenated IMM algorithm composed of inner and outer layered IMM processes is developed in this paper. The validity and performance of the proposed algorithm are demonstrated in the cases of hybrid dynamic and measurement models.