<html><head><style>body{font-family:CMU Sans Serif,Arial;font-size:14px}</style></head><body style="overflow-wrap: break-word; -webkit-nbsp-mode: space; line-break: after-white-space;"><div style="font-family:CMU Sans Serif,Arial;font-size:14px; ">Hi Ulrich,</div><div style="font-family:CMU Sans Serif,Arial;font-size:14px; "><br></div><div style="font-family:CMU Sans Serif,Arial;font-size:14px; ">I suggest you take a look into these recent publications. They have used used obstruction maps to get an idea about which satellite you are currently connecting to. </div><div style="font-family:CMU Sans Serif,Arial;font-size:14px; "><br></div><div style="font-family:CMU Sans Serif,Arial;font-size:14px; ">[1] https://dl.acm.org/doi/abs/10.1145/3624354.3630586</div><div style="font-family:CMU Sans Serif,Arial;font-size:14px; ">[2] https://arxiv.org/abs/2306.07469</div><div style="font-family:CMU Sans Serif,Arial;font-size:14px; "><br></div><div style="font-family:CMU Sans Serif,Arial;font-size:14px; ">We are currently building a reusable framework that maps the obstruction map data with TLE data and gets a (somewhat more) accurate estimate of currently connected satellite — pretty much on the same lines as what you intend to do. However, the work is still underway and I am to chat more if you want to align efforts. </div> <br> <div class="gmail_signature"><font face="CMUSansSerif"><span style="font-style: normal; font-size: 14px;">Thanks and Regards</span></font><div><font face="CMUSansSerif"><span style="font-style: normal; font-size: 14px;"><br></span></font></div><div><font face="CMUSansSerif"><span style="font-style: normal; font-size: 14px;">Nitinder Mohan</span></font></div><div><font face="CMUSansSerif"><span style="font-style: normal; font-size: 14px;">Technical University Munich (TUM)</span></font></div><div><a href="https://www.nitindermohan.com/" style="font-style: normal; font-size: 14px;"><font face="CMUSansSerif">https://www.nitindermohan.com/</font></a></div></div> <div class="airmail_ext_on" style="color:black"><br>From: <span style="color:black">Ulrich Speidel via Starlink</span> <a href="mailto:starlink@lists.bufferbloat.net"><starlink@lists.bufferbloat.net></a><br>Reply: <span style="color:black">Ulrich Speidel</span> <a href="mailto:u.speidel@auckland.ac.nz"><u.speidel@auckland.ac.nz></a><br>Date: <span style="color:black">25. January 2024 at 02:27:44</span><br>To: <span style="color:black">starlink@lists.bufferbloat.net</span> <a href="mailto:starlink@lists.bufferbloat.net"><starlink@lists.bufferbloat.net></a><br>Subject: <span style="color:black"> [Starlink] Dishy GRPC obstruction maps <br></span></div><br> <blockquote type="cite" class="clean_bq"><span><div><div></div><div>
<p>I've been playing a little bit with these:</p>
<p><a class="moz-txt-link-freetext" href="https://github.com/sparky8512/starlink-grpc-tools">https://github.com/sparky8512/starlink-grpc-tools</a></p>
<p>More specifically, I've been playing with the python script
that's getting the obstruction map here. This grabs an array of
123 row tuples with 123 floating point number column entries each,
which represent SNR (signal to noise ratio) data, with the row and
column indices of the data structure being 2D coordinates of the
direction in which this data was observed. A value of -1 meaning
that Dishy hasn't ever seen a satellite in this direction, actual
signal strengths are coded as values between 0.0 and 1.0. You can
output these as PNGs as well, like here (with a slightly changed
colour scheme):</p>
<p><img src="cid:89AB0523-FB47-415C-BC39-F9A145C79398" alt="" width="351" height="355"></p>
<p>What you are looking at is a screenshot (so not exactly 123x123
but very close), with white pixels corresponding to good signal
and anything blueish to impaired signal, and anything black to no
signal. North is top, west is left and east is right. You're
looking at the corner of my house as seen by Dishy on my deck, the
flattish bit on the left is a wooden trellis getting in the way,
and the light blue line crossing the white top part is the
aluminium front bar of my awning (the awning fabric appears to be
transparent to the RF signal).<br>
</p>
<p>My ultimate goal here is to be able to identify which satellite
Dishy is currently talking to, something the grpc interface
doesn't seem to reveal directly (anymore). This is of some
interest in order to see where signals enter the Starlink network,
which ground stations the satellite may relay to in bent pipe
mode, and perhaps for an educated guess as to which ISL hops it's
taking.<br>
</p>
<p>I'm trying to do this essentially by comparing two successive
retrievals of this map and detecting which entry has changed. This
is the easy part.<br>
</p>
<p>The hard part is trying to figure out which satellite this
corresponds to. Essentially, the idea is to translate this pixel
data into a unit vector pointing at the satellite, and then
compare that with the unit vectors from Dishy's location pointing
at the thousands of Starlink sats up there, and picking the one
pair with the smallest angle. All this takes conceptually are a
few coordinate transforms to get everything into the same
coordinate system, with sat positions computed from NORAD two line
elements.</p>
<p>My initial thought was that:</p>
<ol>
<li>Index coordinate (62,62) in the SNR data matrix corresponds to
a satellite that sits on the Dishy surface normal.</li>
<li>Indices minus 62 correspond to some sort of Cartesian x-y
coordinate that should let me derive a unit vector for the
direction to the satellite in a polar coordinate system based on
Dishy's surface and the surface normal.</li>
<li>That then needs transforming into a coordinate system based on
Dishy's location, removing Dishy orientation in the step. Dishy
location and orientation are kindly available from Dishy itself
via grpc.<br>
</li>
<li>Coming the other way, two line elements need to be turned into
global coordinates for satellites at the current time, and these
need to be turned into local coordinates in the system we're
transforming into under 3 above.</li>
</ol>
<p>The crux is at step 1 and 2. If the assumption under 1 is correct
and we assume that the scales in row and column direction are the
same, getting at the azimuth is easy. But what does the distance
of an entry (pixel) to the centre of the map represent?</p>
<ul>
<li>A linear function of the elevation angle?</li>
<li>A cosine projection of the elevation angle?</li>
<li>Would a map position in the middle of each map edge represent
an elevation of 0 or, given the much rumoured phased array
"cone" of 100 degrees, an angle of 40 degrees over Dishy
surface?</li>
<li>Something else?</li>
</ul>
<p>But I'm not even sure that the assumption under 1 is correct.
Note how the area with valid SNR values in the map above is
slightly elliptic and offset a bit towards the bottom? This can't
be due to Dishy's geometry as the long dimension of it is top to
bottom (north to south) rather than east to west. Could this
already be a projection into the coordinate system based on
Dishy's location, such that (62,62) is straight up from the
ground?</p>
<p>Anyone got any insights on this?</p>
<p>Thanks muchly in advance.<br>
</p>
<p>Ulrich<br>
</p>
<pre class="moz-signature" cols="72">--
****************************************************************
Dr. Ulrich Speidel
School of Computer Science
Room 303S.594 (City Campus)
The University of Auckland
<a class="moz-txt-link-abbreviated" href="mailto:u.speidel@auckland.ac.nz">u.speidel@auckland.ac.nz</a>
<a class="moz-txt-link-freetext" href="http://www.cs.auckland.ac.nz/~ulrich/">http://www.cs.auckland.ac.nz/~ulrich/</a>
****************************************************************
</pre>
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