Abstract
Time Difference of Arrival (TDOA) algorithm is a widely used wireless network-based localization algorithm. However, with the increasing complexity of real-life localization environments, the disturbances of noise, perturbations and multi-path effect have limited the performance of the classical TDOA algorithm. In view of these, we design an Interaction-derived Sequence Selection (IDSS) method and an Interaction-derived Sequence Adjustment (IDSA) method to reduce localization error caused by Non Line of Sight (NLOS) environments. Furthermore, an Interacting Multiple Model (IMM) framework is proposed to deal with the localization problem in complex mixed environments. Experimental results demonstrate that the IDSS and IDSA methods can enhance TDOA localization performance in NLOS environments, and the IMM framework can maintain strong adaptability in complex mixed environments.
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