Robust mobility tracking for cellular networks

We propose a robust estimation algorithm for tracking the location and dynamic motion of a mobile unit in a cellular network. The underlying mobility model is a dynamic linear system driven by a discrete command process that determines the mobile unit’s acceleration. The command process is modeled as a semi-Markov process over a finite set of acceleration levels. Previous approaches to mobility estimation based on this model have used a modified Kalman filter with a Bayesian estimator for the command process. However, the Bayesian estimator can lead to inaccuracies in estimating the command process from pilot signal strengths, which can result in significant errors in tracking the mobile trajectory. Our proposed tracking algorithm combines the modified Kalman filter with an efficient hidden semi-Markov model (HSMM) estimation algorithm to estimate the parameters of the command process. Numerical results show that the proposed tracking algorithm performs accurately over a wide range of mobility parameter values.