Global Systems for Mobile Position Tracking Using Kalman and Lainiotis Filters

<table class="table-group" id="tab6"><tr><td><table class="table"><tr><td class="thead-hr" colspan="3"><hr/></td></tr><tr class="thead"><td align="left"> </td><td align="center">Model A</td><td align="center">Model B</td></tr><tr><td class="thead-hr" colspan="3"><hr/></td></tr><tr><td align="left">SSKF/SSLF</td><td align="center">44</td><td align="center">20</td></tr><tr><td align="left">FIR SSKF/SSLF</td><td align="center"><span style="width: 59.487499px;"><svg height="11.375" id="M148" style="vertical-align:-0.51414pt" version="1.1" viewbox="0 0 59.487499 11.375" width="59.487499" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink">
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Calculation burden of classical and FIR steady state filters implementations.

The Scientific World Journal

tab6

Table 6

Table 6: Global Systems for Mobile Position Tracking Using Kalman and Lainiotis Filters 