A New Location Estimation System for Wireless Networks Based on Linear Discriminant Functions and Hidden Markov Models

Location estimation is a recent interesting research area that 0exploits the possibilities of modern communication technology. In this paper, we present a new location system for wireless networks that is especially suitable for indoor terminal-based architectures, as it improves both the speed and the memory requirements. The algorithm is based on the application of linear discriminant functions and Markovian models and its performance has been compared with other systems presented in the literature. Simulation results show a very good performance in reducing the computing time and memory space and displaying an adequate behavior under conditions of few a priori calibration points per position.