Fixed top margin of algo float
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@@ -81,9 +81,12 @@
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\usepackage{algorithm}
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\usepackage{algorithm}
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\usepackage{algpseudocode}
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\usepackage{algpseudocode}
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\usepackage{subcaption}
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\usepackage{caption}
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\usepackage{bm} % bold math symbols with \bm
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\usepackage{bm} % bold math symbols with \bm
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%\usepackage{showframe}
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% replacement for the SI package
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% replacement for the SI package
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\newcommand{\SI}[2]{\ensuremath{#1}\text{\,#2}}
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\newcommand{\SI}[2]{\ensuremath{#1}\text{\,#2}}
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@@ -173,8 +176,23 @@
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}%
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}%
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\ps@headings%
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\ps@headings%
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}
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}
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\newcommand\fs@spaceruled{%
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\def\@fs@cfont{\bfseries}
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% \let\@fs@capt\floatc@ruled
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\def\@fs@pre{\vspace*{5pt}\hrule height.8pt depth0pt \kern2pt}%
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\def\@fs@post{\kern2pt\hrule\relax}%
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\def\@fs@mid{\kern2pt\hrule\kern2pt}%
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\let\@fs@iftopcapt\iftrue}
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\floatstyle{spaceruled}
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\restylefloat{algorithm}
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\captionsetup[algorithm]{labelfont=bf,textfont=normalfont,singlelinecheck=false}
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\makeatother
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\makeatother
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%\confheader{2017 International Conference on Indoor Positioning and Indoor Navigation (IPIN), 18-21 September 2017, Sapporo, Japan}
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%\confheader{2017 International Conference on Indoor Positioning and Indoor Navigation (IPIN), 18-21 September 2017, Sapporo, Japan}
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@@ -7,10 +7,10 @@ At a given time $t$ the system estimates a state providing the most probable pos
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It is implemented using a particle filter with sample importance resampling and \SI{5000} particles.
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It is implemented using a particle filter with sample importance resampling and \SI{5000} particles.
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The dynamics are modelled realistically, which constrains the movement according to walls, doors and stairs.
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The dynamics are modelled realistically, which constrains the movement according to walls, doors and stairs.
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We arranged a \SI{223}{\meter} long walk within the first floor of a \mbox{\SI{76}{} $\times$ \SI{71}{\meter}} sized museum, which was built in the 13th century and therefore offers non-optimal conditions for localization.
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We arranged a \SI{223}{\meter} long walk within the first floor of a \mbox{\SI{76}{} $\times$ \SI{71}{\meter}} sized museum, which was built in the 13th century and offers non-optimal conditions for localization.
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%The measurements for the walks were recorded using a Motorola Nexus 6 at 2.4 GHz band only.
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%The measurements for the walks were recorded using a Motorola Nexus 6 at 2.4 GHz band only.
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%
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%
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Since this work only focuses on processing a given sample set, further details of the localisation system and the described scenario can be looked up in \cite{Ebner17} and \cite{Fetzer17}.
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Since this work only focuses on processing a given sample set, further details of the localization system and the described scenario can be looked up in \cite{Ebner17} and \cite{Fetzer17}.
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The spacing $\delta$ of the grid was set to \SI{27}{\centimeter} for $x$ and $y$-direction, resulting in a grid size of $G=74019$.
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The spacing $\delta$ of the grid was set to \SI{27}{\centimeter} for $x$ and $y$-direction, resulting in a grid size of $G=74019$.
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The bivariate state estimation was calculated whenever a step was recognized, about every \SI{500}{\milli \second}.
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The bivariate state estimation was calculated whenever a step was recognized, about every \SI{500}{\milli \second}.
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%The intention of a real world experiment is to investigate the advantages and disadvantages of the here proposed method for finding a best estimate of the pedestrian's position in the wild, compared to conventional used methods like the weighted-average or choosing the maximum weighted particle.
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%The intention of a real world experiment is to investigate the advantages and disadvantages of the here proposed method for finding a best estimate of the pedestrian's position in the wild, compared to conventional used methods like the weighted-average or choosing the maximum weighted particle.
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