Global Systems for Mobile Position Tracking Using Kalman and Lainiotis Filters. (23rd February 2014)

• Record Type: Journal Article
• Authors: Assimakis, Nicholas; Adam, Maria
• Other Names: Bourennane S. Academic Editor.; Marot J. Academic Editor.
• Is Part Of: TheScientificWorldjournal. Volume 2014(2014)
• Publication Date: 2014-02-23
• Subjects: Science -- Periodicals; Technology -- Periodicals; Medicine -- Periodicals; 505
• DOI: 10.1155/2014/130512
• Languages: English
• ISSNs: 2356-6140

Abstract

Abstract : We present two time invariant models for Global Systems for Mobile (GSM) position tracking, which describe the movement in x -axis and y -axis simultaneously or separately. We present the time invariant filters as well as the steady state filters: the classical Kalman filter and Lainiotis Filter and the Join Kalman Lainiotis Filter, which consists of the parallel usage of the two classical filters. Various implementations are proposed and compared with respect to their behavior and to their computational burden: all time invariant and steady state filters have the same behavior using both proposed models but have different computational burden. Finally, we propose a Finite Impulse Response (FIR) implementation of the Steady State Kalman, and Lainiotis filters, which does not require previous estimations but requires a well-defined set of previous measurements.