Accuracy enhancement of integrated systems based on intelligent information fusion technology

Aims at enhancing the accuracy of land vehicular navigation systems by integrating GPS and inertial measurement units, a new data fusion method based on particle filter inspired by biological evolution is proposed. In the standard particle filter, a resampling scheme is used to decrease the degeneracy phenomenon and improve estimation performance. Unfortunately, however, it could cause the undesired the particle deprivation problem, as well. In order to overcome this problem of the particle filter, we propose a novel filtering method called the genetic filter. In the proposed filter, we embed the genetic algorithm into the particle filter and overcome the problems of the standard particle filter. The proposed scheme will enhance the estimation performance in comparison with generic Kalman filter specially in the case of facing modeling uncertainty. It will also give us more reliable solution when encountering satellite signal blockage as a probable problem in land navigation. The results have clearly demonstrated that the novel data fusion approach would improve the guidance from the point of accuracy and robustness to the mentioned problems.