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transition

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k-a-z-u
2018-10-16 17:30:34 +02:00
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20
tex_review/chapters/transition.tex
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@@ -194,14 +194,20 @@
that might be reachable. Increasing $\sigma_\text{step}$ and $\sigma_\text{turn}$ for those cases might also be a viable choice.
Likewise, just using some random position, omitting heading/steps might be viable as well.
The detected steps $\mObsSteps$ and the heading change $\mObsHeading$ are obtained using the smartphone's IMU.
To provide a robust heading change, we first need to rotate the gyroscope onto the east-north-up frame using a suitable transformation matrix.
After the rotation, integrating over the gyros $z$-axis for a predefined time interval provides the user’s heading change (yaw) \cite{Ebner-15}.
To obtain the matrix in the first place, we assume that the acceleration during walking is cyclic and thus the average acceleration over several cycles has to be almost zero.
This enables to measure the direction of gravity and use it to construct the transformation matrix.
It should be noted, that especially for cheap IMUs, as they can be found in most smartphones, the matrix has to be updated at very short intervals of one or two seconds to preserve good results \cite{davidson2017survey}.
The detected steps $\mObsSteps$ and the heading change $\mObsHeading$ \add{used within above transition} are obtained by the smartphone's IMU.
For the change in heading, we first need to rotate the gyroscope's readings onto the east-north-up frame using a suitable rotation matrix,
\add{
to determined, what the readings would look like, if the smartphone was placed parallel to the ground.
The matrix is thus used to undo the rotation introduced by the pedestrian holding the phone.
This rotation matrix is given by the matrix that rotates the current gravity readings from the accelerometer to
the $(0,0,\SI{9.81}{\meter\per\square\second})^T$ vector.
After applying the matrix to the gyroscope's readings,
the pedestrian's change in heading (yaw) is given by integrating over the gyroscope's $z$-axis \cite{Ebner-15}.
}
It should be noted, that especially for cheap IMUs, as they can be found in most smartphones,
the matrix has to be updated at very short intervals of one or two seconds to preserve good results \cite{davidson2017survey}.
To receive the number of steps, we use a very simple step detection based on the accelerometer magnitude.
To receive the number of steps, we use a very simple step detection based on the accelerometer's magnitude.
For this, we calculated the difference between the average magnitude over the last \SI{200}{\milli\second} and the gravity vector.
If this difference is above a certain threshold ($> \SI{0.32}{\m\per\square\s}$), a step is detected.
To prevent multiple detections within an unrealistic short interval, we block the complete process for \SI{250}{\milli\second} \cite{Koeping14}.

6
tex_review/review/03_review.txt
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@@ -67,10 +67,8 @@ Ln 228: "If the destination is unreachable, e.g. due to the walls or other obsta
-> Thank you for noticing! We adjusted the sentence accordingly.
Ln 237: "...the average acceleration..." This includes both linear acceleration and gravity, use "linear acceleration".
-> TODO: @Frank?
hier gehts um die gravity. wir müssen die lage des phones erkennen. hervorheben.
die >>linear<< acceleration interessiert hier nicht.
das ganze wird sehr oft aktualisiert um die richtige lage zu haben
-> we rephrased the complete paragraph. It should now be clear how the current gravity readings are used to
determined the phone's current orientation, to undo the rotation, present within the gyroscope's readings.
Ln 258 - This equation needs revision. Should it be "p(s_i|p) ~ N(u_i,p , std²_wifi)" ? Also the wall-attenuation-factor-model only takes into account attenuation by floors, not walls.
-> TODO: Eigentlich passt das mit der NV, für Ihn tdz ändern? Und das model nimmt keine wände, weil wir keine wände nehmen :D.