Comparing measurement and state vector data fusion algorithms for mobile phone tracking using a-GPS and U-TDOA measurements

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27240%2F15%3A86097025" target="_blank" >RIV/61989100:27240/15:86097025 - isvavai.cz</a>
Result on the web
<a href="http://dx.doi.org/10.1007/978-3-319-19644-2_49" target="_blank" >http://dx.doi.org/10.1007/978-3-319-19644-2_49</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1007/978-3-319-19644-2_49" target="_blank" >10.1007/978-3-319-19644-2_49</a>

Result language
angličtina
Original language name
Comparing measurement and state vector data fusion algorithms for mobile phone tracking using a-GPS and U-TDOA measurements
Original language description
Multi-Sensor Data Fusion (MSDF) becomes one research area in different disciplines including science and engineering. To enhance reliability and accuracy of sensor measurements' multisensory data fusion techniques are applied. The aim of this paper is toevaluate estimation performance of measurement fusion and state vector fusion algorithms in tracking a moving mobile phone along all journey of a vehicle. These two algorithms based on Kalman Filter are implemented in the tracking system. Performance evaluation is computed using MATLAB and the analysis show position and velocity estimation accuracy of measurement fusion algorithm is better than state vector fusion algorithm. (C) Springer International Publishing Switzerland 2015.
Czech name
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Czech description
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Publication year
2015
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

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