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POGPS Track, computing height difference
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  1. POGPS Track, computing height difference
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    copied!<p>I have implemented a GPS Tracker for Android. So far it is working quite nice but I have problems computing the <strong>right</strong> height difference for the track. I want to sum up all meters the device "climbed" and "descended". I do this in a background service comparing the current location object with the previous one and store the difference directly as a column in the database. If I sum this up after the track is finished I get a value that is approximately 2.5 times as high (1500m vs 650m) as measured with a bicycle speedometer that uses a barometer. </p> <p>I know the measured altitude of the GPS device is inaccurate. Is there any way to "normalize" the measured altitude? Should I, for example, ignore all altitude changes below 2 meters? Another possibility would be to use additional sensors as some devices also have a barometer. But that would only help on some devices. </p> <p>Thanks for any advice or hints on this issue!</p> <p>EDIT 28.05.2013: The answer of Bryce got me on the right track. I started searching the web and found a very simple low pass filter that is easy to implement. I did this in c++</p> <p>A node class representing one waypoint:</p> <pre><code>class Node { private: double distance; double altitude; double altitudeup; double altitudedown; double latitude; double longitude; long timestamp; public: Node(double dist, double alti, double altiup, double altidown, double lat, double lon, long ts); double getAltitude(); double getAltitudeup(); double getAltitudedown(); }; </code></pre> <p>Here is the function that does the actual work and computes the values for total ascend and descend:</p> <pre><code>void SimpleLowPass::applySLP() { double altiUp = 0; double altiDown = 0; double prevAlti = this-&gt;nodeList[0]-&gt;getAltitude(); double newAlti = prevAlti; for (auto n : this-&gt;nodeList) { double cur = n-&gt;getAltitude(); // All the power of the filter is in the line // newAlti += (cur - newAlti) / smoothing. // This finds the difference between the new value and the current (smoothed) // value, shrinks it based on the strength of the filter, and then adds it // to the smoothed value. You can see that if smoothing is set to 1 then the // smoothed value always becomes the next value. If the smoothing is set to // 2 then the smoothed value moves halfway to each new point on each new // frame. The larger the smoothing value, the less the smoothed line is // perturbed by new changes. newAlti += (cur - newAlti) / 20.0; std::cout &lt;&lt; "newAlti: " &lt;&lt; newAlti &lt;&lt; std::endl; if (prevAlti &gt; newAlti) { altiDown += prevAlti - newAlti; } if (newAlti &gt; prevAlti) { altiUp += newAlti - prevAlti; } prevAlti = newAlti; } std::cout &lt;&lt; "Alti UP total: " &lt;&lt; altiUp &lt;&lt; std::endl; std::cout &lt;&lt; "Alti DOWN total: " &lt;&lt; altiDown &lt;&lt; std::endl; } </code></pre> <p>This is a quick and dirty implementation. But with a value of 20 for smoothing I get pretty good results. Still I will need to record more tracks and compare the results. Also there is Frame-Rate independent implementation on the website where I found this low-pass filter and I want to play with a moving average implementation. </p> <p><a href="http://phrogz.net/js/framerate-independent-low-pass-filter.html" rel="nofollow">simple low-pass filter</a></p> <p>Thanks for all your answers!</p>
 

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