Global Systems for Mobile Position Tracking Using Kalman and Lainiotis Filters
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 t...
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| Format: | Article |
| Language: | English |
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Wiley
2014-01-01
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| Series: | The Scientific World Journal |
| Online Access: | http://dx.doi.org/10.1155/2014/130512 |
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| author | Nicholas Assimakis Maria Adam |
| author_facet | Nicholas Assimakis Maria Adam |
| author_sort | Nicholas Assimakis |
| collection | DOAJ |
| description | 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. |
| format | Article |
| id | doaj-art-69f433b4a40b4b5fa50c1517701f8bdf |
| institution | Kabale University |
| issn | 2356-6140 1537-744X |
| language | English |
| publishDate | 2014-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | The Scientific World Journal |
| spelling | doaj-art-69f433b4a40b4b5fa50c1517701f8bdf2025-08-20T03:34:08ZengWileyThe Scientific World Journal2356-61401537-744X2014-01-01201410.1155/2014/130512130512Global Systems for Mobile Position Tracking Using Kalman and Lainiotis FiltersNicholas Assimakis0Maria Adam1Department of Electronic Engineering, Technological Educational Institute of Central Greece, 3rd km Old National Road Lamia-Athens, 35100 Lamia, GreeceDepartment of Computer Science and Biomedical Informatics, University of Thessaly, 2-4 Papasiopoulou Street, 35100 Lamia, GreeceWe 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.http://dx.doi.org/10.1155/2014/130512 |
| spellingShingle | Nicholas Assimakis Maria Adam Global Systems for Mobile Position Tracking Using Kalman and Lainiotis Filters The Scientific World Journal |
| title | Global Systems for Mobile Position Tracking Using Kalman and Lainiotis Filters |
| title_full | Global Systems for Mobile Position Tracking Using Kalman and Lainiotis Filters |
| title_fullStr | Global Systems for Mobile Position Tracking Using Kalman and Lainiotis Filters |
| title_full_unstemmed | Global Systems for Mobile Position Tracking Using Kalman and Lainiotis Filters |
| title_short | Global Systems for Mobile Position Tracking Using Kalman and Lainiotis Filters |
| title_sort | global systems for mobile position tracking using kalman and lainiotis filters |
| url | http://dx.doi.org/10.1155/2014/130512 |
| work_keys_str_mv | AT nicholasassimakis globalsystemsformobilepositiontrackingusingkalmanandlainiotisfilters AT mariaadam globalsystemsformobilepositiontrackingusingkalmanandlainiotisfilters |