Beginner question about rtlsdr

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Michel Pelletier pelletier.michel at gmail.com
Sun Oct 21 22:24:11 UTC 2012


Scott,

Thanks so much for your detailed reply.  As an optical amateur I am
really excited to be immersed in a new world of very interesting
concepts related to radio astronomy.  Thanks for patiently explaining
to me how I was getting it wrong.  I've read the wikipedia pages on
FFT and some of the history and I think I get, at least abstractly,
the distinction now.

On Sun, Oct 21, 2012 at 1:12 PM, Scott Cutler <scott at scottcutler.net> wrote:
> To get from the time domain (the raw samples) to the frequency domain
> (waterfall display, etc.), you need an FFT.  The FFT operates on some given
> buffer size, and outputs a buffer of the same size filled with complex
> frequency levels (where the magnitude squared is the signal energy).

I don't think I want a waterfall "frequency domain" display however (I
didn't know that, until I read the references you pointed me toward),
I suspect that what I want is the time domain.  From a very simple
perspective, and initially to recreate the Jansky experiment, I just
want the signal strength over a wide bandwidth plotted over time.
Jansky used a simple pen plotter of signal strength (again, according
to wikipedia) to chart the passage of a strong radio signal across his
local zenith.  After discovering the period was a sidereal day he
consulted a sky chart and realized it was Sagittarius.

> The FFT width determines your frequency resolution, not the bandwidth.  The
> bandwidth is determined by the sample rate--in your case, 1.4 MHz.
>
> So you choose your FFT based on your resolution and performance
> requirements.  In your case, the FFT will return frequencies from -0.7 to
> 0.7 MHz around the center frequency--no matter what the FFT width.  The FFT
> results store the positive frequencies from 1..(N/2-1) and the negative ones
> from (N/2+1)..(N-1).  Sample 0 is 0 Hz and N/2 is 0.7 MHz (you can't really
> use this last one since it aliases).  The other frequencies scale linearly
> between these points (sample N/4 is 0.35 MHz, etc.).  For a waterfall
> display, this generally means you want to swap the left and right halves of
> a buffer.
>
> You can read as many samples as you want from the device. Conceptually, it's
> similar to an audio device--if you need more samples, you just wait longer.
> You could collect 64M samples if you wanted, and get some nice sub-Hz
> resolution, but it would take 45 s to record at your settings.

Ok, I think I'm getting the picture of this, and it's very
enlightening.  I think that I just want the signal strength of the
entire bandwidth over time.  Which I believe I can get by simply
summing the magnitude squared of all my samples taken, and plot that
over time.  Does that sound right to you?

I eventually plan to try and do some basic interferometry, where
multiple observations are taken and combined to synthesize an aperture
capable of resolving point sources.  But I'm way far away from doing
that or even really understanding it other than from a high level.
There is an excellent python package called aipy that is developed by
a group of radio astronomers that is used for a large scale 64 antenna
array in southern Australia that I would eventually like to use to
combine multiple sources.  The whole sky images they have developed so
far from cheap (compared to multi-meter dishes) crossed dipole arrays
are very impressive.  This may be utterly foolish thinking, but I
really hope something like rtlsdr, or something like it terms of
price, can bring large scale interferometry to the masses.

> Incidentally, none of this is peculiar to rtl-sdr--even the fanciest and
> most expensive units operate the same way, though they have higher sample
> rates and such.  In fact, the stuff I said is fundamental to all signal
> processing--if you're willing to get your hands dirty with math, you might
> want to read the wiki articles on Fourier Transforms and other signal
> processing subjects.

Thanks Scott, I'm digging deep and consuming as much information on
the subject as I can.  Can you recommend any standard works on signal
processing I should dig into?

-Michel




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