Being at Athens Hackerspece yesterday, I had a discussion with some of the members of the core SatNOGs team on achieving maximum LEO (Lower Earth Orbit) coverage using SatNOGs groundstations. So, our problem was set as stated below:
How many SatNOGS stations do we need to achieve maximum LEO coverage?
This problem has both a mathematical and computational interest. My intuition was to develop an algorithm to calculate the best fitting model while being aware of the physical restrictions of the problem, such as waters etc.
Is anyone interested in investigating it with me? If yes, I am glad to hear so!
PS: Recommendations for web resources, scientific literature and books (or other texts) are always welcome!
I was actually thinking about this the other day, but I’m not really a mathematician.
The other thought I had about it was, how much overlap would we want so that if two readings were wanted at the same time from two different satellites. Or three, etc. Obviously, 100% coverage would only be good enough for a single satellite at a time per station.
I would be happy to work with you on this. It should be a reasonably straightforward problem, except for the input variablility. For example, how close to the horizion each station can reliably see. Or what type of signal you are wanting to decode to what error level. Another variable is the orbit parameters the the LEO you want to track.
I am new to your group and am not sure what you consider your minimum acceptable points are. Please forgive me for not understanding better.
As a start consider Gpredict and any of the Open Source programs on the AMSAT-NA site.
I should be interested in co-operating on this.
FUNcube Team Member
For FUNcube we have
1327 registered users
776 unique ground stations in the distributed network have uploaded data
FC1 has broadcast 1.6GB of data, of which 402MB (25%) of realtime information has been recovered by ground stations around the world, this is collected once every 5 seconds.
As well as realtime, the system also recovers:
Whole Orbit Data (WOD) which is collected every minute and provides us with information about the experiments on board as well as the general health of the satellite. We have recovered 83% of this data
High Resolution Data (HiRes) which is sampled once per second and provides information on the spin rate of the satellite in three axes. We have recovered 20% of the data
Hi, this issue is akin to Handover processes for satellites overpassing ground stations,
with in-built redundancy required for a number of reasons:
(1) handover process itself is not instantaneous, so some margin has to be considered
(2) as a matter of expandable network capacity, ground stations pool must be greater than (1)
(3) as a matter of surviving station failures, ground stations pool must be greater than (2)
There likely will be even more arguments to have a denser network, this challenge shares similarities with cellular network coverage for mobile phones, yet with much more expanded spatial aspects.
It is important to realise that handoff procedures imply good coordination, which itself may need to rely on existing broadband facilities (adsl/fiber networks etc).
What I think would work relatively well, taking Greece as an example, it would be to place the nodes apart in 30-100Kms distance, and deliver a couple of SatNOGs per ground station at capital locations of geographical prefectures (hint: this is to maximize coupling with broadband networks and increase reliability):
trying this out in practice should reveal if/how much denser or not the network should be.
My thought was to develop an algorithm to look for possible arrangements (taking into consideration the actual restrictions) and decide on the most efficient one starting from Greece (as @gef mentioned) and then continue to the globe.
One headstart might be to utilize NASA’s Open Source General Mission Analysis Tool. You can definitely calculate/visualize communications windows based on different orbits. I’m not sure if it’s scriptable enough to be able to calculate ideal positions for those groundstations.
Apologies for late posting. I am very busy for the time being. Yesterday, I was able to sit down for the first time and play with the problem a little bit by setting the mathematical background for it. Nevertheless, the GMAT tool might be a big help to tackling the problem!
I will post updates (I hope) soon!
Since satnogs can rotate with respect to an axis b’b perpendicular to our view passing through C1 we can estimate that the total area covered is a spherical cap with radius HC1 and height FC1 wich can cover a surface area S = 2πh(r+h) where r is the earth radius and h is the given LEO height. A more in depth explanation and a full blog post is being prepared together with the algorithm taking into consideration physical constraints.
Hi folks, I have finally managed (I hope) to approach the solution of this problem and, without taking into consideration, physical constraints we will need 10 to 45 groundstations depending on our altitude. However the situation changes since we refer to a real system - model. This is my attempt:
PS Apologies for typos. In case you have something to add/modify please feel free to tell me!
To some extent it depends on the content of the telemetry. For FUNcube 1 we can capture the housekeeping telemetry for a whole orbit (105 minutes) and transmit it in 2 minutes of download at 1200 baud.
The Data Warehouse statistics as of 09:53 GMT on March 15, 2015 were:
Number of registered users: 1529
Number of active users (data received in last two weeks): 193
Number of active users since launch: 818
Number of packets transmitted by satellite since deployment: 8312304 (2.13 GB)
Number of packets uploaded by users before de-duplication: 8539662(2.19 GB)
Number of packets stored in warehouse: 2000000 (512 MB)
Number of packets recovered & stored – Time – Coverage
Realtime 2M – 115 days – 25%
HiRes 3.9M – 1085 minutes – 19%
WOD 0.56M – 385.78 days – 80%