Dynamic model-based filtering for mobile terminal location estimation

Mobile terminal location is an important area of research because of its applications in location-sensitive browsing and resource allocation. The paper presents a method for reducing the error in mobile terminal location estimation. A preprocessor using nonparametric estimation is used to reduce the effects of non-line-of-sight and multipath propagation on the location procedure. A model-based dynamic filter is presented that uses an accurate model of mobile terminal motion to combine information from location measurements made at different time instances to create an improved location estimate. The model of mobile terminal motion has a kinematic state space model describing the physical rules governing terminal motion and a control model that describes the human control input into the motion process. Location dependency in the control input model is used to derive a new dynamic filter. This filter provides greatly improved accuracy over previously known location techniques and is much more robust to variations in the mobile terminal motion and nonlinear effects in the propagation environment.