Hi Milos,
no need to apologize!
> The DFT is a sliding window DFT which gives me the output per each
sample instead of calculating the DFT for the whole N (well it gives
DFT per sample but I take output after 2 samples in my case).
That explains the halfing of numbers from in- to output.
> I then store those peaks in a vector.
Trying to understand what "storing these peaks" means: do you mean
putting the peak's index into a vector element? Or its converted
frequency? Or its amplitude?
> (each input to the vector represents a frequency)
Ah! Ok, that answers the above question.
> So for each pair of input samples (in that 1024 vector above) the
output vector will look something like this - in Hz [0 0 0 2000 2000
2000 -1000 0 0 0 ...]. I now want to take that output vector and
generate a tone for each sample pair at time t (ie it doesnt generate
all the tones at once but each tone at specific time). So e.g. the
first three pairs will have 0Hz, then the 4th pair will have tone at
2000Hz, etc.
Well, the problem that I can see here is that you're switching
frequency - potentially from sample to sample – based on a quantized
frequency estimate:
You have a 1024-FFT, so there's only 1024 frequencies you can
accurately detect (namely, -f_s/2 to +f_s/2 in steps of f_s/1024).
All other frequencies will have leakage into multiple bins, and that
makes the estimate less stable, and of course, can lead to interesting
oscillating estimates if the actual frequency happens to fall in the
middle between two FFT bins.
Other than that, the frequency modulator is generally what you want –
convert a frequency floating point value into a single tone of a single
frequency. Maybe you want to interpolate your frequency estimates prior
to sending them into the frequency mod?
> So I take 1024 vector and perform DFT on each sample and then I find,
lets say, one top frequency after 2 samples as I mentioned above
(because of the nature of my input signal there will be a peak
somewhere in that DFT).
Sounds like you want to estimate a main frequency component – in that
case, have you considered parametric spectrum estimators instead of the
sliding window DFT? They could potentially give you higher frequency
resolution with less input, in some cases (many cases) even with less
computational effort!
Maybe you could tell us a tiny bit more about the larger context of why
you're doing this, so we can advise more appropriately?
Best regards,
Marcus
On Tue, 2018-09-11 at 10:31 +0100, Milos Milosavljevic wrote:
> Hi Marcus,
> Thanks for coming back to me and I apologies for the vague description of my problem. Let me try to clarify what i meant please.
>
> The DFT is a sliding window DFT which gives me the output per each sample instead of calculating the DFT for the whole N (well it gives DFT per sample but I take output after 2 samples in my case).
>
> So I take 1024 vector and perform DFT on each sample and then I find, lets say, one top frequency after 2 samples as I mentioned above (because of the nature of my input signal there will be a peak somewhere in that DFT).
>
> All the above happens in one block.
>
> I then store those peaks in a vector. So for each pair of input samples (in that 1024 vector above) the output vector will look something like this - in Hz [0 0 0 2000 2000 2000 -1000 0 0 0 ...]. I now want to take that output vector and generate a tone for
each sample pair at time t (ie it doesnt generate all the tones at once but each tone at specific time). So e.g. the first three pairs will have 0Hz, then the 4th pair will have tone at 2000Hz, etc.
>
> I tried feeding that output vector above to vector to stream and then freq mod block but that obviously didnt get me very far. It works fine if my signal is ideal. If i introduce frequency error the output is too distorted.
>
> My question is really, is there an efficient way to convert an output vector of samples to frequency (each input to the vector represents a frequency).
>
> Thanks
> Milos
>
>
> On 11 September 2018 at 08:21, Müller, Marcus (CEL) <address@hidden> wrote:
> > Hi Milos,
> >
> > I must admit I don't fully understand what your "DFT block" does – how
> > does it reduce from 1024 to 512 values per item? What does each value
> > mean? why would the frequency mod block deal with these in a way that
> > generates multiple tones?
> >
> > Best regards,
> > Marcus
> >
> > On Mon, 2018-09-10 at 23:57 +0100, Milos Milosavljevic wrote:
> > > Dear All,
> > >
> > > From my own DFT output I am calculating top frequencies. I want to
> > > take each of the calculated frequency (e.g. my calculation gives me
> > > something like -2400, 1024, 0, 0, 0, -2400) and generate a carrier
> > > with the corresponding frequency. The algorithm is correct and the
> > > implementation seems fine.
> > >
> > > But I tried using the Freq Modulator block to give me the carrier but
> > > the output is just too distorted. What would be the best way to go
> > > around this?
> > >
> > > I have something like this:
> > > Input (stream) -> StreamToVector(1024 vlen) --> DFT (out is vector of
> > > top freqs of len 512) --> VectorToStream (512) --> Repeat(Interpolate
> > > by 2) --> FreqMod(sensitivity -1.0/(float(samp_rate)/(2*pi)))
> > >
> > > Any comments will be appreciated.
> > >
> > > Many thanks,
> > > Milos
> > >
> > >
> > > _______________________________________________
> > > Discuss-gnuradio mailing list
> > > address@hidden
> > >
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>
>
>