Re: Developing KrakenSDR Source

[Jeff Long]

Once this is all working, you could have get_iq_online() work in a separate thread so that you don't have to hit the network every time work() is called. Maybe buffer a small number of frames in a queue.

On Tue, Aug 16, 2022 at 10:13 AM Jeff Long <willcode4@gmail.com> wrote:

Hi Carl,

Use vectors only if data always needs to be grouped in exact quantities, e.g., if the GR flowgraph needs to always handle blocks of 2^20 items. In general, a 5-channel stream would be more flexible. The variation in the number of items would be due to the output buffer sometimes being empty and sometimes not. This depends on what is happening in downstream blocks, and also on random scheduling of threads. Hope that answers some of your questions.

On Tue, Aug 16, 2022 at 9:49 AM Carl Laufer <admin@rtl-sdr.com> wrote:

Hi All,

I'm currently working on a GNU Radio source block for the KrakenSDR. So far my block mostly seems to work as expected, but I'm having some minor issues and questions.

If you didn't know, the KrakenSDR is 5 RTL-SDR receivers, on the same clock with a noise source for coherence calibration of the channels. We're using it for applications like radio direction finding and passive radar, and mostly write our own code in Python. But having a GNU Radio source would be useful for others.

With KrakenSDR there is a DAQ software called "heimdall" which handles all the coherent calibration automatically. In my source block, I'm able to successfully receive the data in the GNU Radio source block from heimdall via a socket connection.

First so you know, the heimdall DAQ buffers an array of "cpi_size" (cpi = coherent processing interval) IQ data per channel, and outputs those arrays on the socket when it's filled. By default the cpi_size = 2^20. So in my GNU Radio source I'm receiving five, 2^20 long arrays of coherent complex IQ data every ~400ms.

I believe in GNU Radio this is considered a vector? So should I make the output of the source block five port vectors, with out_sig=[(np.complex64, cpi_size)] * numChannels and set vlen to cpi_size in the yaml?

Or instead should I have it as an output stream out_sig=[np.complex64] * numChannels, and be using Stream->Vector blocks when needed, with num_items set to cpi_size?

I've tried both methods, and they both work. But I don't understand why when using the vector output implementation, the shape of output_items keeps flipping between (5, 2, 1048576) and (5, 1, 1048576)?

Code is all at https://github.com/krakenrf/gr-krakensdr if anyone would care to take a look. Everything in Python. If anyone has any tips or comments please let me know. Thanks to anyone for your insights.

Regards,

Carl Laufer