Fast Bayesian tracking for location estimation by grid-based method

With increasing demand on location estimation, Bayesian tracking algorithm for mobile devices that requires low computing power is needed. By nonlinear/non-Gaussian Bayesian methods, grid-based methods are considered inefficient compared with the particle filters. We propose fast grid-based Markov localization algorithm by reducing the computational complexity of grid-based method. The fusion of dead reckoning and GPS location simulation shows that fast grid-based algorithm shows better performance on both location accuracy and time requirement.