![](/images/graphics-bg.png)
Global Systems for Mobile Position Tracking Using Kalman and Lainiotis Filters
Joint Authors
Assimakis, Nicholas
Adam, Maria
Source
Issue
Vol. 2014, Issue 2014 (31 Dec. 2014), pp.1-8, 8 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2014-02-23
Country of Publication
Egypt
No. of Pages
8
Main Subjects
Medicine
Information Technology and Computer Science
Abstract EN
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.
American Psychological Association (APA)
Assimakis, Nicholas& Adam, Maria. 2014. Global Systems for Mobile Position Tracking Using Kalman and Lainiotis Filters. The Scientific World Journal،Vol. 2014, no. 2014, pp.1-8.
https://search.emarefa.net/detail/BIM-1048397
Modern Language Association (MLA)
Assimakis, Nicholas& Adam, Maria. Global Systems for Mobile Position Tracking Using Kalman and Lainiotis Filters. The Scientific World Journal No. 2014 (2014), pp.1-8.
https://search.emarefa.net/detail/BIM-1048397
American Medical Association (AMA)
Assimakis, Nicholas& Adam, Maria. Global Systems for Mobile Position Tracking Using Kalman and Lainiotis Filters. The Scientific World Journal. 2014. Vol. 2014, no. 2014, pp.1-8.
https://search.emarefa.net/detail/BIM-1048397
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1048397